CN119555697B - Copper foil surface defect detection method, device, computer equipment and storage medium - Google Patents
Copper foil surface defect detection method, device, computer equipment and storage mediumInfo
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- CN119555697B CN119555697B CN202411593576.3A CN202411593576A CN119555697B CN 119555697 B CN119555697 B CN 119555697B CN 202411593576 A CN202411593576 A CN 202411593576A CN 119555697 B CN119555697 B CN 119555697B
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Abstract
本申请涉及铜箔检测技术领域，提供了一种铜箔表面缺陷检测方法、装置、计算机设备及存储介质，本申请根据待测铜箔的实时移动速度及预设基准采集速度调整相机的实时采集速度并获取待测铜箔的上下表面图像；获取上下表面图像中相对应的特征点对；根据相对应的特征点对识别上下表面图像中的潜在缺陷区域；对潜在缺陷区域进行表面缺陷检测，得到隐藏缺陷检测结果；对上下表面图像进行表面缺陷检测，得到上下表面缺陷检测结果；根据隐藏缺陷检测结果及上下表面缺陷检测结果生成铜箔表面缺陷检测结果。本申请能够同时对铜箔的上下表面及隐藏的缺陷进行检测，提高了检测效果的准确性和全面性。
The present application relates to the technical field of copper foil inspection and provides a copper foil surface defect inspection method, apparatus, computer equipment, and storage medium. The present application adjusts the real-time acquisition speed of a camera based on the real-time movement speed of the copper foil to be inspected and a preset baseline acquisition speed, and acquires images of the upper and lower surfaces of the copper foil to be inspected; obtains corresponding feature point pairs in the upper and lower surface images; identifies potential defect areas in the upper and lower surface images based on the corresponding feature point pairs; performs surface defect inspection on the potential defect areas to obtain hidden defect detection results; performs surface defect inspection on the upper and lower surface images to obtain upper and lower surface defect detection results; and generates copper foil surface defect detection results based on the hidden defect detection results and the upper and lower surface defect detection results. The present application can simultaneously inspect the upper and lower surfaces of the copper foil and hidden defects, thereby improving the accuracy and comprehensiveness of the inspection results.
Description
Technical Field
The present application relates to the field of copper foil detection technology, and in particular, to a method and apparatus for detecting a surface defect of a copper foil, a computer device, and a storage medium.
Background
In the production process of copper foil, surface defects are one of important indexes for measuring the quality and performance of the copper foil. With the rapid development of image processing technology, an automatic detection system for the surface defects of the copper foil based on the technology has been developed, so that the burden of manual detection is reduced, and the detection efficiency is improved.
However, most of the existing copper foil detection methods based on the image processing technology only focus on a single surface image of the copper foil, that is, only perform defect detection on the upper surface image or only perform defect detection on the lower surface image, and ignore possible association information between the upper surface and the lower surface of the copper foil. The detection mode limited to a single visual angle cannot comprehensively capture all defect characteristics of the copper foil surface, and further accuracy and comprehensiveness of a detection effect are affected.
Disclosure of Invention
Based on the detection, a copper foil surface defect detection method, a device, computer equipment and a storage medium are provided, and the technical problem that all defects on the copper foil surface cannot be comprehensively captured in a single-view detection mode in the prior art is solved.
The first aspect of the application provides a method for detecting surface defects of a copper foil, which comprises the following steps:
adjusting the real-time acquisition speeds of the first group of linear array CCD cameras and the second group of linear array CCD cameras according to the real-time movement speed of the copper foil to be tested and the preset reference acquisition speed;
acquiring an upper surface image of the copper foil to be tested acquired by the first group of linear array CCD cameras at the real-time acquisition speed, and acquiring a lower surface image acquired by the second group of linear array CCD cameras at the real-time acquisition speed;
acquiring corresponding characteristic point pairs in the upper surface image and the lower surface image;
identifying potential defect areas in the upper surface image and the lower surface image according to the corresponding characteristic point pairs;
performing surface defect detection on the potential defect area to obtain a hidden defect detection result;
Performing surface defect detection on the upper surface image to obtain an upper surface defect detection result, and performing surface defect detection on the lower surface image to obtain a lower surface defect detection result;
and generating a copper foil surface defect detection result according to the hidden defect detection result, the upper surface defect detection result and the lower surface defect detection result.
Optionally, the adjusting the real-time acquisition speeds of the first group of linear array CCD cameras and the second group of linear array CCD cameras according to the real-time movement speed of the copper foil to be tested and the preset reference acquisition speed includes:
calculating to obtain a moving speed ratio according to the real-time moving speed of the copper foil to be tested and a preset reference moving speed;
determining a quality grade according to the model parameters of the copper foil to be tested;
acquiring the microscopic texture change rate of the copper foil to be tested;
And adjusting the real-time acquisition speeds of the first group of linear array CCD cameras and the second group of linear array CCD cameras according to the moving speed ratio, the quality grade, the microscopic texture change rate and the preset reference acquisition speed.
Optionally, the acquiring the corresponding feature point pairs in the upper surface image and the lower surface image includes:
detecting feature points of the upper surface image to obtain first key feature points;
detecting the feature points of the lower surface image to obtain second key feature points;
And performing feature matching on the first key feature points and the second key feature points to obtain corresponding feature point pairs.
Optionally, the identifying potential defect areas in the upper surface image and the lower surface image according to the corresponding feature point pairs includes:
Calculating displacement vectors between the corresponding feature point pairs;
Judging whether displacement exists between the upper surface image and the lower surface image according to the displacement vector;
when it is determined that there is displacement, the areas of the upper surface image and the lower surface image corresponding to the displacement vectors are identified as potential defect areas.
Optionally, the performing surface defect detection on the upper surface image to obtain an upper surface defect detection result, and performing surface defect detection on the lower surface image to obtain a lower surface defect detection result includes:
performing differential processing on the upper surface image and a reference upper surface image to obtain a first differential image;
Performing surface defect detection based on the upper surface image to obtain a first upper surface defect detection result;
Performing surface defect detection based on the first differential image to obtain a second upper surface defect detection result;
correcting the first upper surface defect detection result according to the second upper surface defect detection result to obtain the upper surface defect detection result;
performing differential processing on the lower surface image and the reference lower surface image to obtain a second differential image;
Performing surface defect detection based on the lower surface image to obtain a first lower surface defect detection result;
performing surface defect detection based on the second differential image to obtain a second lower surface defect detection result;
And correcting the first lower surface defect detection result according to the second lower surface defect detection result to obtain the lower surface defect detection result.
Optionally, the method further comprises:
Determining a defect position according to the detection result of the surface defect of the copper foil;
and sending the defect position to a labeling machine, so that the labeling machine labels the region, corresponding to the defect position, on the copper foil to be tested.
Optionally, the first group of linear array CCD cameras are used for acquiring the upper surface of the copper foil to be tested to obtain the upper surface image under the condition that the upper surface detection light source and the high brightness backlight source provide illumination, and the second group of linear array CCD cameras are used for acquiring the lower surface of the copper foil to be tested to obtain the lower surface image under the condition that the lower surface detection light source provides illumination.
A second aspect of the present application provides a copper foil surface defect detecting apparatus, the apparatus comprising:
The camera adjusting module is used for adjusting the real-time acquisition speeds of the first group of linear array CCD cameras and the second group of linear array CCD cameras according to the real-time movement speed of the copper foil to be detected and the preset reference acquisition speed;
The image acquisition module is used for acquiring an upper surface image of the copper foil to be tested acquired by the first group of linear array CCD cameras at the real-time acquisition speed and acquiring a lower surface image acquired by the second group of linear array CCD cameras at the real-time acquisition speed;
the feature acquisition module is used for acquiring corresponding feature point pairs in the upper surface image and the lower surface image;
The region identification module is used for identifying potential defect regions in the upper surface image and the lower surface image according to the corresponding characteristic point pairs;
The first detection module is used for carrying out surface defect detection on the potential defect area to obtain a hidden defect detection result;
The second detection module is used for carrying out surface defect detection on the upper surface image to obtain an upper surface defect detection result, and carrying out surface defect detection on the lower surface image to obtain a lower surface defect detection result;
and the result generation module is used for generating a copper foil surface defect detection result according to the hidden defect detection result, the upper surface defect detection result and the lower surface defect detection result.
A third aspect of the present application provides a computer apparatus comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the copper foil surface defect detection method when executing the computer program.
A fourth aspect of the present application provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the copper foil surface defect detection method.
According to the embodiment of the application, the real-time acquisition speeds of the first group and the second group of linear array CCD cameras can be dynamically adjusted according to the real-time movement speed of the copper foil to be detected and the preset reference acquisition speed. The dynamic adjustment mechanism ensures that the camera can always capture images at the optimal frame rate, avoids the phenomenon of image blurring or frame loss, thereby improving the acquisition quality of the copper foil surface images, avoiding unnecessary image acquisition and storage, and reducing the waste of calculation resources and storage space. The upper surface and the lower surface images of the copper foil are respectively acquired by using the two groups of linear array CCD cameras, so that the upper surface and the lower surface images of the copper foil are ensured to be synchronous in time, the whole surface of the copper foil can be covered in the detection process, and the comprehensiveness of detection is improved. Corresponding characteristic point pairs in the upper surface image and the lower surface image are obtained through an image processing algorithm, and the characteristic point pairs can accurately capture small changes of the upper surface and the lower surface of the copper foil, so that potential defect areas can be identified more accurately. And respectively carrying out surface defect detection on the potential defect area, the upper surface image and the lower surface image to obtain a hidden defect detection result, an upper surface defect detection result and a lower surface defect detection result, wherein the multi-dimensional detection can more comprehensively find various defect types on the surface of the copper foil, and the detection precision and reliability are improved. And finally, comprehensively generating a copper foil surface defect detection result according to the hidden defect detection result, the upper surface defect detection result and the lower surface defect detection result. The comprehensive detection result can comprehensively reflect the quality condition of the copper foil surface.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of a method for detecting surface defects of a copper foil according to an embodiment of the present application.
Fig. 2 is an interface schematic diagram of copper foil surface defect detection according to an embodiment of the present application.
Fig. 3 is a functional block diagram of a copper foil surface defect detecting device according to an embodiment of the present application.
Fig. 4 is a schematic structural diagram of a computer device according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Fig. 1 is a flow chart of a method for detecting surface defects of a copper foil according to an embodiment of the present application, wherein the method for detecting surface defects of a copper foil includes the following steps.
S11, adjusting the real-time acquisition speeds of the first group of linear array CCD cameras and the second group of linear array CCD cameras according to the real-time movement speed of the copper foil to be tested and the preset reference acquisition speed.
The copper foil to be tested refers to a copper foil material which needs to be subjected to surface defect detection. In the production process of the copper foil, defects or pollution may exist on the upper and lower surfaces of the copper foil, so that defect detection needs to be performed on the upper and lower surface images of the copper foil at the same time. The first group of linear array CCD cameras are used for acquiring upper surface images of the copper foil to be tested, and the second group of linear array CCD cameras are used for acquiring lower surface images of the copper foil to be tested.
In an alternative embodiment, the first set of linear array CCD cameras is used for acquiring the upper surface of the copper foil to be tested under the condition that the upper surface detection light source and the high brightness backlight source provide illumination environments, and the second set of linear array CCD cameras is used for acquiring the lower surface of the copper foil to be tested under the condition that the lower surface detection light source provides illumination environments, so as to acquire the lower surface image.
During the copper foil manufacturing process, the copper foil may be moved through the inspection system at a certain speed. This speed may be variable or constant, and it is necessary to acquire the moving speed of the copper foil in real time (real-time moving speed). A speed sensor or an encoder can be arranged at a proper position of the copper foil moving path to monitor the moving speed of the copper foil on the production line in real time. The speed sensor may be a photoelectric sensor, a laser sensor, or the like.
The preset reference acquisition speed is set according to the optimal performance or detection requirement of the system design, and is the default acquisition speed of the system when the difference of the actual movement speeds of the copper foils is not considered.
The real-time acquisition speed of the line CCD camera refers to the number of image Frames Per Second (FPS) that the line CCD camera can acquire. The relationship between the acquisition speed of the camera and the movement speed of the copper foil directly affects the quality of the surface image and the integrity of the information. When the acquisition speed of the camera is too slow and the movement speed of the copper foil is too fast, the shutter of the camera is too long, and the copper foil has moved a certain distance in the time, so that the phenomenon of image tailing or blurring occurs. In addition, due to the too slow acquisition speed, the camera may not capture all details during the movement of the copper foil, resulting in information loss. When the acquisition speed of the camera is too high and the movement speed of the copper foil is too slow, since the camera takes a large number of images in a short time, many of the images may be similar or repeated, resulting in a waste of a large amount of data storage space and processing resources. Therefore, in order to obtain high-quality images and complete information, and save storage space and processing resources, the real-time acquisition speeds of the first group of linear array CCD cameras and the second group of linear array CCD cameras need to be adjusted according to the real-time movement speed of the copper foil to be detected and the preset reference acquisition speed.
In an optional embodiment, the adjusting the real-time collecting speeds of the first group of linear array CCD cameras and the second group of linear array CCD cameras according to the real-time moving speed of the copper foil to be tested and the preset reference collecting speed includes:
calculating to obtain a moving speed ratio according to the real-time moving speed of the copper foil to be tested and a preset reference moving speed;
determining a quality grade according to the model parameters of the copper foil to be tested;
acquiring the microscopic texture change rate of the copper foil to be tested;
And adjusting the real-time acquisition speeds of the first group of linear array CCD cameras and the second group of linear array CCD cameras according to the moving speed ratio, the quality grade, the microscopic texture change rate and the preset reference acquisition speed.
In the case that the production line is stably operated and the quality of the copper foil is stable, the average moving speed of the copper foil over a period of time is measured and recorded using a speed sensor, and this speed is taken as a reference moving speed. The reference movement speed represents a standard or desired movement speed on the production line. The preset reference acquisition speed is the default acquisition speed of the system when the factors such as the actual movement speed, quality grade, microscopic texture change rate and the like of the copper foil are not considered. A matched reference acquisition speed (F_reference) is determined according to the performance parameters (such as maximum frame rate, resolution and the like) of the linear array CCD camera. The reference acquisition speed is matched with the performance of the linear array CCD camera, so that high-quality images can be captured at the reference moving speed.
During the running process of the production line, the real-time moving speed of the copper foil is monitored by a speed sensor or an encoder, and the real-time moving speed is transmitted to a control system of the camera. The control system calculates the ratio between the real-time moving speed of the copper foil and the reference moving speed. The ratio reflects the difference between the actual moving speed of the copper foil and the moving speed (reference moving speed) expected at the time of system design. If the ratio is greater than 1, it means that the real-time moving speed is faster than the reference moving speed, and if the ratio is less than 1, it means that the real-time moving speed is slower than the reference moving speed.
The corresponding database can be searched according to the model parameters of the copper foil to be tested, and the quality grade and the microscopic texture change rate of the copper foil to be tested are determined.
The quality grade refers to a grade determined by the degree to which the same variety of commodity reaches the commodity quality standard. Copper foils of different quality grades differ in physical and chemical properties such as hardness, strength, corrosion resistance, conductivity, etc. These differences may cause the copper foil to exhibit different reflectivity, transmissivity, or scattering characteristics during image acquisition, thereby affecting the sharpness and contrast of the image acquisition. High quality grade copper foil generally has a smoother surface, reducing image distortion or noise due to surface irregularities. In contrast, low quality grades of copper foil may be blurred or distorted during image acquisition due to surface irregularities.
The micro-texture change rate is an index for describing the micro-texture change speed of the surface of the copper foil to be tested. The surface texture of the copper foil with high microscopic texture change rate is more complex and variable, and the texture characteristics can be difficult to accurately capture and identify during image acquisition. Copper foil with high micro-texture change rate may generate more noise such as surface defects, scratches, contamination, etc. during the image acquisition process. These noises may reduce the sharpness and contrast of the image, making it difficult for the image to accurately reflect the actual state of the copper foil.
Therefore, the copper foil with different types has different quality grades and micro texture change rates, so that the quality of image acquisition can be obviously affected. Therefore, when the image acquisition is performed on the upper surface and the lower surface of the copper foil, the real-time acquisition speeds of the first group of linear array CCD cameras and the second group of linear array CCD cameras need to be adjusted simultaneously according to the moving speed ratio, the quality grade, the microscopic texture change rate and the preset reference acquisition speed.
In an alternative embodiment, the real-time acquisition speed may be calculated using the following formula:
Vsampling=v base x R x P x (1+γ·m);
Wherein V is the real-time acquisition speed of the linear array CCD camera, V base is the preset reference acquisition speed, R is the moving speed ratio, P is the quality grade, M is the microscopic texture change rate, and gamma is the influence coefficient of the microscopic texture change rate, and is determined empirically. The influence coefficient reflects the sensitivity of the microscopic texture change rate to acquisition speed adjustment.
After the real-time acquisition speeds of the cameras (the first group of linear array CCD cameras and the second group of linear array CCD cameras) are calculated, the change of the real-time acquisition speeds can be realized by adjusting internal parameters (such as shutter speed, frame rate and the like) of the cameras. After the real-time acquisition speed of the camera is adjusted, images in a period of time can be acquired first, whether the images are clear and stable or not can be judged, and no key information is omitted. If the image quality is found to be poor or information is missed, the real-time acquisition speed needs to be adjusted again.
According to the optional implementation mode, the real-time acquisition speed is adjusted according to the ratio of the real-time movement speed of the copper foil to the reference movement speed, so that the acquisition speed of the camera is matched with the movement speed of the copper foil, the acquisition efficiency is improved, and the image overlapping or losing is avoided. The acquisition speed of the camera is adjusted according to the quality grade and the microscopic texture change rate of the copper foil, so that high-quality images can be obtained on copper foils with different quality grades and texture complexity. For the copper foil with high quality grade, a clearer image can be acquired, and for the copper foil with high micro texture change rate, the image can be ensured to capture more details. This alternative embodiment enhances the adaptability of the image acquisition system to copper foil of different models, different quality grades and different micro-texture rates of change. Through dynamic adjustment of the acquisition speed, the system can automatically adapt to different copper foil characteristics without manual intervention, so that the automation level of the whole image acquisition process is improved, the production cost is reduced, the production efficiency is improved, and the possibility of human errors is reduced.
S12, acquiring an upper surface image of the copper foil to be tested acquired by the first group of linear array CCD cameras at the real-time acquisition speed, and acquiring a lower surface image acquired by the second group of linear array CCD cameras at the real-time acquisition speed.
In a large-scale and high-efficiency production line detection scene, a linear array CCD (Charge-Coupled Device) camera is adopted to rapidly capture images of continuously moving objects. According to the embodiment of the application, the first group of linear array CCD cameras are used for collecting the upper surface of the copper foil to be tested, and an upper surface image is obtained. And simultaneously, a second group of linear array CCD cameras are used for collecting the lower surface of the copper foil to be tested, and a lower surface image is obtained.
S13, acquiring corresponding characteristic point pairs in the upper surface image and the lower surface image.
The upper and lower surfaces of the copper foil are not completely independent from the physical characteristics of the copper foil. The copper foil as a whole may have an influence on the morphology of the upper and lower surfaces due to its internal stress and microstructure. For example, copper foil may be subjected to forces such as stretching, compression, or bending during production, which may cause the upper and lower surfaces to be morphologically related. In addition, the microstructure (e.g., grain size, arrangement, etc.) of the copper foil may also affect the image characteristics of the upper and lower surfaces. Therefore, it is necessary to acquire corresponding pairs of feature points in the upper surface image and the lower surface image.
Feature points are points in an image that have unique properties, such as corner points, edge points, or areas of rich texture. Feature points in the upper surface image and feature points in the lower surface image may be detected using a feature point detection algorithm, resulting in feature point pairs.
The feature point detection algorithm may include Harris corner detection, SIFT (Scale-INVARIANT FEATURE TRANSFORM ), SURF (Speeded Up Robust Features, accelerated robust feature), and the like.
In an alternative embodiment, the acquiring the corresponding pairs of feature points in the upper surface image and the lower surface image includes:
detecting feature points of the upper surface image to obtain first key feature points;
detecting the feature points of the lower surface image to obtain second key feature points;
And performing feature matching on the first key feature points and the second key feature points to obtain corresponding feature point pairs.
And detecting feature points, such as edges, corner points, texture features and the like, in the upper surface image by using a feature point detection algorithm to obtain a plurality of first key feature points. And detecting the feature points corresponding to the upper surface image in the lower surface image by using the same feature point detection algorithm to obtain a plurality of second key feature points.
And matching the first key feature points with the second key feature points through a feature matching algorithm. The matching process is to calculate the similarity (such as euclidean distance, hamming distance, etc.) between feature descriptors, and select the point pair with the highest similarity as the matching pair. The result is a set of corresponding pairs of feature points that correspond to the same physical location or feature in the upper surface image and the lower surface image, respectively.
S14, identifying potential defect areas in the upper surface image and the lower surface image according to the corresponding characteristic point pairs.
In an alternative embodiment, the identifying potential defect areas in the upper surface image and the lower surface image according to the corresponding pairs of feature points includes:
Calculating displacement vectors between the corresponding feature point pairs;
Judging whether displacement exists between the upper surface image and the lower surface image according to the displacement vector;
when it is determined that there is displacement, the areas of the upper surface image and the lower surface image corresponding to the displacement vectors are identified as potential defect areas.
For each pair of matched feature points, their displacement vectors between the upper surface image and the lower surface image are calculated. The displacement vector represents a change in position from a feature point in the upper surface image to a corresponding feature point in the lower surface image. And carrying out statistical analysis on the calculated displacement vector, wherein the statistical analysis comprises calculation of a mean value, a variance, a maximum and minimum value, vector direction distribution and the like. These statistics help reveal possible global deformations or local defects of the copper foil between the upper and lower surfaces. One or more thresholds are set for determining whether a pair of feature points indicates a potential defect region based on the statistical properties of the displacement vector. For example, a maximum allowable value of the displacement vector may be set, and pairs of feature points exceeding this value may represent defects. This is because if the copper foil is not deformed or abnormally moved during the transfer, the corresponding feature points of the upper and lower surfaces thereof should be maintained in a relatively fixed positional relationship in theory. An abnormal increase in displacement vector may mean that the copper foil has defects such as bending, twisting or internal stress, which may not be apparent when the upper surface or the lower surface is observed alone, but can be revealed by analyzing the correlation of the upper and lower surfaces.
For pairs of feature points indicating potential defects, their positions in the upper and lower surface images are marked. These locations may form one or more continuous areas that are primarily considered potential defect areas. Specifically, regarding the feature point having displacement, a region is marked as a potential defect region in the upper surface image and the lower surface image, respectively, based on the magnitude and direction of the displacement vector, with the feature point as the center. The potential defect region refers to an actual region which should theoretically appear in the lower surface image but be shifted in position after shifting from the feature points in the upper surface image.
S15, carrying out surface defect detection on the potential defect area to obtain a hidden defect detection result.
Since the potential defect area of the mark is determined based on the displacement of the feature points, the potential defect area may not completely correspond to the actual defect position or shape. Therefore, there is also a need to verify these potential defect areas by finer defect detection algorithms and determine if there are real defects and the specific type and severity of the defects.
The hidden defect detection model can be trained in advance based on machine learning, the potential defect area is used as the input of the hidden defect detection model, and the hidden defect detection result is detected and output through the hidden defect detection model.
S16, performing surface defect detection on the upper surface image to obtain an upper surface defect detection result, and performing surface defect detection on the lower surface image to obtain a lower surface defect detection result.
Hidden defect detection results, while providing information about potential defective areas, may not capture defects in non-potential defective areas. Complete surface defect detection of the upper and lower surfaces ensures that all possible defects are detected, thereby providing a more comprehensive quality assessment.
In an optional embodiment, the performing surface defect detection on the upper surface image to obtain an upper surface defect detection result, and performing surface defect detection on the lower surface image to obtain a lower surface defect detection result includes:
performing differential processing on the upper surface image and a reference upper surface image to obtain a first differential image;
Performing surface defect detection based on the upper surface image to obtain a first upper surface defect detection result;
Performing surface defect detection based on the first differential image to obtain a second upper surface defect detection result;
correcting the first upper surface defect detection result according to the second upper surface defect detection result to obtain the upper surface defect detection result;
performing differential processing on the lower surface image and the reference lower surface image to obtain a second differential image;
Performing surface defect detection based on the lower surface image to obtain a first lower surface defect detection result;
performing surface defect detection based on the second differential image to obtain a second lower surface defect detection result;
And correcting the first lower surface defect detection result according to the second lower surface defect detection result to obtain the lower surface defect detection result.
The reference upper surface image, the reference lower surface image is an image of a known, defect-free or standard-looking copper foil surface. The reference upper surface image and the reference lower surface image are used as references for comparison so as to identify any deviation or defect of the upper and lower surfaces of the copper foil to be tested. Surface defects of a copper foil refer to any physical characteristic that appears on the upper and lower surfaces of the copper foil that does not meet the desired standard or specification, such as scratches, dents, cracks, stains, oxidation, etc. These defects may affect the performance, reliability and service life of the copper foil.
Any non-standard or expected deviations, which tend to be indicative of potential defects, can be more easily identified by comparing the upper/lower surface images of the copper foil to be tested to known reference upper/lower surface images. By using the reference upper/lower surface images as references, false positives and false negatives caused by factors such as illumination changes, texture differences or imaging equipment errors can be reduced. The reference upper/lower surface image provides a stable comparison reference that helps to distinguish between true defects and false defects.
The difference between the two images can be highlighted by the difference processing, so that the defect on the surface of the copper foil can be identified. In addition, the differential processing has certain robustness to interference factors such as illumination change, shadow and the like. The present embodiment calculates a new image obtained by pixel difference between the upper/lower surface image and the reference upper/lower surface image, i.e., a difference image. The difference image may be obtained by subtracting gray values or color values of corresponding pixels in the upper/lower surface image and the reference upper/lower surface image. The value of each pixel in the difference image represents the degree of difference in the two images at that location. The differential image is capable of highlighting areas of variation between the two images, which may correspond to imperfections, movements or variations of the object surface, etc.
The differential image may contain a large amount of noise and small variations that may not correspond to actual defects. To filter out these noises, thresholding may be applied to the differential image. I.e. the pixel values in the differential image are divided into two classes, pixels above the threshold are regarded as defective areas and pixels below the threshold are regarded as background or noise.
Since there may be a difference in position or angle between the upper/lower surface image and the reference upper/lower surface image at the time of photographing, it is necessary to perform image alignment of the upper/lower surface image and the reference upper/lower surface image to ensure that both are spatially coincident. Alignment of the top surface image and the reference top surface image may be achieved by feature matching, affine transformation, or other image registration algorithms.
In order to improve the image alignment effect, the denoising processing can be performed on the upper/lower surface image first, and then the denoising processing can be performed on the upper/lower surface image and the reference upper/lower surface image after denoising.
Features associated with defects, such as texture features, shape features, color features, etc., may be first extracted from the top/bottom surface images, the reference top/bottom surface images. And detecting surface defects based on the extracted features by using a defect detection model. Surface defect detection may also be performed based on the upper/lower surface images and the reference upper/lower surface images using a defect detection model. The defect detection model is a machine learning model which is trained in advance and can identify and locate defects on the surface of the copper foil. The defect detection result (first upper surface defect detection result/second upper surface defect detection result) is outputted by the defect detection model using the feature related to the defect extracted from the upper/lower surface image, the reference upper/lower surface image, or directly using the upper/lower surface image, the reference upper/lower surface image as an input of the defect detection model. The surface defect detection results include all defect information detected, such as location, size, shape, type of defect, and one or more images or visual markers representing the defect. Defect information may be presented using numbers, images, or a combination of both.
After the first upper surface defect detection result and the second upper surface defect detection result are obtained, the second upper surface defect detection result may be used to correct errors or uncertainties in the first upper surface defect detection result. For example, the defect positions, sizes, and types in the first upper surface defect detection result and the second upper surface defect detection result are matched, combined, or screened to generate a final upper surface defect detection result.
Similarly, after the first subsurface defect detection result and the second subsurface defect detection result are obtained, the second subsurface defect detection result may be used to correct errors or uncertainties in the first subsurface defect detection result. For example, the defect locations, sizes, and types in the first subsurface defect detection result and the second subsurface defect detection result are matched, combined, or screened to generate a final subsurface defect detection result.
It can be appreciated that denoising, contrast enhancement processing, etc. may be performed before the differential image is input to the defect detection model, so as to enhance the quality of the differential image and improve the accuracy of the detection result.
It can be appreciated that, in order to further improve accuracy of the detection result, post-processing may be performed on the output of the defect detection model, for example, removing isolated points, filling holes, and the like.
It will be appreciated that the defect detection model used for defect detection on the lower surface image may be the same model or different models as the defect detection model used for defect detection on the lower surface image, and the present application is not limited in this respect.
In the above alternative embodiments, the direct defect detection of the upper/lower surface image may be affected by various factors, such as illumination variation, image noise, surface texture difference, etc., resulting in false alarm (misjudging the non-defective area as a defect) or false alarm (failing to detect a true defect). While the reference upper/lower surface image represents a non-defective or normal state copper foil upper/lower surface. By the differential processing, the influence of the above-described factors on the upper/lower surface detection result can be eliminated or reduced because the differential image mainly reflects the difference between the upper/lower surface image and the reference upper/lower surface image. The detection result of the upper surface image is corrected by using the detection result of the first differential image, and the detection result of the lower surface image is corrected by using the detection result of the second differential image, so that false alarm and false alarm can be further reduced, and the detection accuracy is improved. In addition, the difference processing can highlight areas where the upper/lower surface image does not coincide with the reference upper/lower surface image, which are more likely to be defective. By focusing on these inconsistent areas, the focus on non-critical areas in the image can be reduced, thereby reducing the interference of external factors on the detection result and enhancing the robustness of detection.
S17, generating a copper foil surface defect detection result according to the hidden defect detection result, the upper surface defect detection result and the lower surface defect detection result.
The defects in the hidden defect detection result, the upper surface defect detection result and the lower surface defect detection result can be considered to be all real, and information (such as position, size, shape and the like) about the defect characteristics in the hidden defect detection result, the upper surface defect detection result and the lower surface defect detection result are combined to generate a more comprehensive defect description, so that the quality and the severity of the defects can be judged more accurately. And taking the fused result of the three defect detection results as a final copper foil surface defect detection result.
In an alternative embodiment, the method further comprises:
Determining a defect position according to the detection result of the surface defect of the copper foil;
and sending the defect position to a labeling machine, so that the labeling machine labels the region, corresponding to the defect position, on the copper foil to be tested.
After detecting the defect, the system records the position of the defect in the image and sends the position of the defect to the labeling machine.
After the labeling machine receives the defect position, labeling is carried out on the copper foil according to the region corresponding to the defect position on the copper foil. Labeling machines typically have a high precision positioning system and reliable actuators to ensure that labels are accurately attached to defective locations.
In some alternative embodiments, the system may select an appropriate label type (e.g., color, shape, size, etc.) based on the type, severity, etc. of defect prior to labeling and print or prepare to facilitate rapid identification and handling of different types of defects during the manufacturing process.
After the labeling is completed, production personnel can quickly position the defective copper foil area according to the label information and take corresponding treatment measures (such as reworking, scrapping and the like).
The optional implementation mode not only improves the automation level of the detection process, but also helps to quickly identify and process the defective copper foil in actual production by introducing accurate marks of defect positions in the copper foil surface defect detection process.
In an alternative embodiment, classification statistics may be further performed on the surface defect detection result of the copper foil, and the result of classification statistics may be visually displayed through a defect detection display interface as shown in fig. 2. The defect detection display interface may include basic information of the copper foil, detection means, detection time, type of detected defect, characteristics, position, priority, and the like.
The number of upper surface defects, the number of lower surface defects, and the total number of defects may be counted. The average size of the defect, the trend of the change of the analyzed defect, and the like can be calculated. The defect distribution diagram can be displayed, so that the distribution situation of various defects on the surface of the copper foil and the influence degree of the defects on the quality of the copper foil can be known.
A set of standardized report templates may be designed in advance, and a copper foil quality inspection report may be generated based on the standardized report templates. The template comprises the basic information (such as report number, detection date, detection personnel, etc.), detection results (such as the number, distribution condition, etc. of various defects), data analysis results (such as the average size, variation trend, etc. of the defects), suggested quality control measures, etc.
According to the optional implementation mode, the copper foil surface defect detection results are classified and counted, and the copper foil quality detection report is generated, so that the detection results are clearer and more visual, enterprise management staff and production staff can know the quality condition of the copper foil more comprehensively, and accordingly more effective quality control measures are adopted.
According to the method for detecting the surface defects of the copper foil, provided by the embodiment of the application, the real-time acquisition speeds of the first group and the second group of linear array CCD cameras can be dynamically adjusted according to the real-time movement speed of the copper foil to be detected and the preset reference acquisition speed. The dynamic adjustment mechanism ensures that the camera can always capture images at the optimal frame rate, avoids the phenomenon of image blurring or frame loss, thereby improving the acquisition quality of the copper foil surface images, avoiding unnecessary image acquisition and storage, and reducing the waste of calculation resources and storage space. The upper surface and the lower surface images of the copper foil are respectively acquired by using the two groups of linear array CCD cameras, so that the upper surface and the lower surface images of the copper foil are ensured to be synchronous in time, the whole surface of the copper foil can be covered in the detection process, and the comprehensiveness of detection is improved. Corresponding characteristic point pairs in the upper surface image and the lower surface image are obtained through an image processing algorithm, and the characteristic point pairs can accurately capture small changes of the upper surface and the lower surface of the copper foil, so that potential defect areas can be identified more accurately. And respectively carrying out surface defect detection on the potential defect area, the upper surface image and the lower surface image to obtain a hidden defect detection result, an upper surface defect detection result and a lower surface defect detection result, wherein the multi-dimensional detection can more comprehensively find various defect types on the surface of the copper foil, and the detection precision and reliability are improved. And finally, comprehensively generating a copper foil surface defect detection result according to the hidden defect detection result, the upper surface defect detection result and the lower surface defect detection result. The comprehensive detection result can comprehensively reflect the quality condition of the copper foil surface.
Fig. 3 is a functional block diagram of a copper foil surface defect detecting device according to an embodiment of the present application.
In some embodiments, the copper foil surface defect detection device 30 may include a plurality of functional modules composed of program code segments. The program code of each program segment in the copper foil surface defect detecting device 30 may be stored in a memory of a computer apparatus and executed by at least one processor to perform the function of copper foil surface defect detection (described in detail with reference to fig. 1).
In this embodiment, the copper foil surface defect detecting device 30 may be divided into a plurality of functional modules according to the functions performed by the device. The functional modules may include a camera adjustment module 301, an image acquisition module 302, a feature acquisition module 303, a region identification module 304, a first detection module 305, a second detection module 306, a result generation module 307, and a copper foil labeling module 308. The module referred to herein is a series of computer readable instructions capable of being executed by at least one processor and of performing a fixed function, stored in a memory. In the present embodiment, the functions of the respective modules will be described in detail in the following embodiments.
The camera adjusting module 301 is configured to adjust the real-time acquisition speeds of the first set of linear array CCD cameras and the second set of linear array CCD cameras according to the real-time movement speed of the copper foil to be tested and a preset reference acquisition speed;
The image acquisition module 302 is configured to acquire an upper surface image of the copper foil to be tested acquired by the first set of linear array CCD cameras at the real-time acquisition speed, and acquire a lower surface image acquired by the second set of linear array CCD cameras at the real-time acquisition speed;
The feature obtaining module 303 is configured to obtain corresponding feature point pairs in the upper surface image and the lower surface image;
the region identifying module 304 is configured to identify potential defect regions in the upper surface image and the lower surface image according to the corresponding feature point pairs;
The first detection module 305 is configured to perform surface defect detection on the potential defect area to obtain a hidden defect detection result;
the second detection module 306 is configured to perform surface defect detection on the upper surface image to obtain an upper surface defect detection result, and perform surface defect detection on the lower surface image to obtain a lower surface defect detection result;
The result generating module 307 is configured to generate a copper foil surface defect detection result according to the hidden defect detection result, the upper surface defect detection result, and the lower surface defect detection result.
The copper foil labeling module 308 is configured to determine a defect position according to the detection result of the surface defect of the copper foil, and send the defect position to a labeling machine, so that the labeling machine labels an area corresponding to the defect position on the copper foil to be tested.
The copper foil surface defect detection device provided by the embodiment of the application can dynamically adjust the real-time acquisition speeds of the first group and the second group of linear array CCD cameras according to the real-time movement speed of the copper foil to be detected and the preset reference acquisition speed. The dynamic adjustment mechanism ensures that the camera can always capture images at the optimal frame rate, avoids the phenomenon of image blurring or frame loss, thereby improving the acquisition quality of the copper foil surface images, avoiding unnecessary image acquisition and storage, and reducing the waste of calculation resources and storage space. The upper surface and the lower surface images of the copper foil are respectively acquired by using the two groups of linear array CCD cameras, so that the upper surface and the lower surface images of the copper foil are ensured to be synchronous in time, the whole surface of the copper foil can be covered in the detection process, and the comprehensiveness of detection is improved. Corresponding characteristic point pairs in the upper surface image and the lower surface image are obtained through an image processing algorithm, and the characteristic point pairs can accurately capture small changes of the upper surface and the lower surface of the copper foil, so that potential defect areas can be identified more accurately. And respectively carrying out surface defect detection on the potential defect area, the upper surface image and the lower surface image to obtain a hidden defect detection result, an upper surface defect detection result and a lower surface defect detection result, wherein the multi-dimensional detection can more comprehensively find various defect types on the surface of the copper foil, and the detection precision and reliability are improved. And finally, comprehensively generating a copper foil surface defect detection result according to the hidden defect detection result, the upper surface defect detection result and the lower surface defect detection result. The comprehensive detection result can comprehensively reflect the quality condition of the copper foil surface.
It should be understood that the various modifications and embodiments of the method for detecting a surface defect of a copper foil according to the foregoing embodiment are equally applicable to the apparatus for detecting a surface defect of a copper foil according to the present embodiment, and those skilled in the art will be aware of the implementation procedure of the apparatus for detecting a surface defect of a copper foil according to the foregoing detailed description of the method for detecting a surface defect of a copper foil, which is not described in detail herein for brevity of description.
The embodiment of the application also provides a computer readable storage medium, on which a computer program is stored, the computer program realizing all or part of the steps of the copper foil surface defect detection method when being executed by a processor.
Fig. 4 is a schematic structural diagram of a computer device according to an embodiment of the present application. In a preferred embodiment of the application, the computer device 4 comprises a memory 401, at least one processor 402, at least one communication bus 403.
It should be appreciated by those skilled in the art that the configuration of the computer device illustrated in FIG. 4 is not a limitation of embodiments of the present application. The computer device 4 may also include more or less other hardware or software than shown, or a different arrangement of components.
In some embodiments, the computer device 4 is a device capable of automatically performing numerical calculation and/or information processing according to preset or stored instructions, and its hardware includes, but is not limited to, a microprocessor, an application specific integrated circuit, a programmable gate array, a digital processor, an embedded device, and the like. The computer device 4 may also include a client device, including but not limited to any electronic product that can interact with a client by way of a keyboard, mouse, remote control, touch pad, or voice control device, such as a personal computer, tablet, smart phone, digital camera, etc.
It should be noted that the computer device 4 is only used as an example, and other electronic products that may be present in the present application or may be present in the future are also included in the scope of the present application by way of reference.
In some embodiments, the memory 401 stores a computer program that, when executed by the at least one processor 402, performs all or part of the steps in the copper foil surface defect detection method as described. The Memory 401 includes Read-Only Memory (ROM), programmable Read-Only Memory (PROM), erasable programmable Read-Only Memory (ErasabSeProgrammable Read-Only Memory, EPROM), one-time programmable Read-Only Memory (One-time Programmable Read-Ony Memory, OTPROM), electrically erasable rewritable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disc Memory, magnetic disk Memory, magnetic tape Memory, or any other medium that can be used for computer readable storage or carrying data. Further, the computer-readable storage medium may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like.
In some embodiments, the at least one processor 402 is a control core (Crol Unit) of the computer device 4, connects the various components of the entire computer device 4 using various interfaces and lines, runs or executes programs or modules stored in the memory 401, and invokes data stored in the memory 401 to perform various functions of the computer device 4 and process data. For example, the at least one processor 402 may perform all or part of the steps of the method for detecting a surface defect of a copper foil according to the embodiment of the present application, or may perform all or part of the functions of the device for detecting a surface defect of a copper foil when executing a computer program stored in the memory. The at least one processor 402 may be comprised of integrated circuits, such as a single packaged integrated circuit, or may be comprised of multiple integrated circuits packaged with the same or different functionality, including one or more central processing units (Central Processing Unit, CPU), microprocessors, digital processing chips, graphics processors, combinations of various control chips, and the like.
In some embodiments, the at least one communication bus 403 is arranged to enable a connected communication between the memory 401 and the at least one processor 402 etc. Although not shown, the computer device 4 may further include a power source (such as a battery) for powering the various components, and preferably the power source may be logically connected to the at least one processor 402 via a power management device, such that functions of managing charging, discharging, and power consumption are performed by the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The computer device 4 may further include various sensors, bluetooth modules, wi-Fi modules, etc., which will not be described in detail herein.
The integrated units implemented in the form of software functional modules described above may be stored in a computer readable storage medium. The software functional modules described above are stored in a storage medium and include instructions for causing a computer device (which may be a personal computer, a computer device, or a network device, etc.) or processor (processor) to perform portions of the methods described in the various embodiments of the application.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be other manners of division when actually implemented.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
Claims (9)
1. A method for detecting surface defects of a copper foil, the method comprising:
adjusting the real-time acquisition speeds of the first group of linear array CCD cameras and the second group of linear array CCD cameras according to the real-time movement speed of the copper foil to be tested and the preset reference acquisition speed;
acquiring an upper surface image of the copper foil to be tested acquired by the first group of linear array CCD cameras at the real-time acquisition speed, and acquiring a lower surface image acquired by the second group of linear array CCD cameras at the real-time acquisition speed;
acquiring corresponding characteristic point pairs in the upper surface image and the lower surface image;
identifying potential defect areas in the upper surface image and the lower surface image according to the corresponding characteristic point pairs;
performing surface defect detection on the potential defect area to obtain a hidden defect detection result;
Performing surface defect detection on the upper surface image to obtain an upper surface defect detection result, and performing surface defect detection on the lower surface image to obtain a lower surface defect detection result;
Generating a copper foil surface defect detection result according to the hidden defect detection result, the upper surface defect detection result and the lower surface defect detection result;
The identifying potential defect areas in the upper surface image and the lower surface image according to the corresponding feature point pairs comprises:
Calculating displacement vectors between the corresponding feature point pairs;
Judging whether displacement exists between the upper surface image and the lower surface image according to the displacement vector;
when it is determined that there is displacement, the areas of the upper surface image and the lower surface image corresponding to the displacement vectors are identified as potential defect areas.
2. The method for detecting surface defects of copper foil according to claim 1, wherein adjusting the real-time acquisition speeds of the first set of line CCD cameras and the second set of line CCD cameras according to the real-time movement speed of the copper foil to be detected and the preset reference acquisition speed comprises:
calculating to obtain a moving speed ratio according to the real-time moving speed of the copper foil to be tested and a preset reference moving speed;
determining a quality grade according to the model parameters of the copper foil to be tested;
acquiring the microscopic texture change rate of the copper foil to be tested;
And adjusting the real-time acquisition speeds of the first group of linear array CCD cameras and the second group of linear array CCD cameras according to the moving speed ratio, the quality grade, the microscopic texture change rate and the preset reference acquisition speed.
3. The method of claim 2, wherein the acquiring the corresponding pairs of feature points in the upper surface image and the lower surface image comprises:
detecting feature points of the upper surface image to obtain first key feature points;
detecting the feature points of the lower surface image to obtain second key feature points;
And performing feature matching on the first key feature points and the second key feature points to obtain corresponding feature point pairs.
4. The method of claim 1, wherein performing surface defect detection on the upper surface image to obtain an upper surface defect detection result, and performing surface defect detection on the lower surface image to obtain a lower surface defect detection result comprises:
performing differential processing on the upper surface image and a reference upper surface image to obtain a first differential image;
Performing surface defect detection based on the upper surface image to obtain a first upper surface defect detection result;
Performing surface defect detection based on the first differential image to obtain a second upper surface defect detection result;
correcting the first upper surface defect detection result according to the second upper surface defect detection result to obtain the upper surface defect detection result;
performing differential processing on the lower surface image and the reference lower surface image to obtain a second differential image;
Performing surface defect detection based on the lower surface image to obtain a first lower surface defect detection result;
performing surface defect detection based on the second differential image to obtain a second lower surface defect detection result;
And correcting the first lower surface defect detection result according to the second lower surface defect detection result to obtain the lower surface defect detection result.
5. The method for detecting surface defects of copper foil according to claim 1, further comprising:
Determining a defect position according to the detection result of the surface defect of the copper foil;
and sending the defect position to a labeling machine, so that the labeling machine labels the region, corresponding to the defect position, on the copper foil to be tested.
6. The method for detecting surface defects of copper foil according to claim 1, wherein the first group of linear array CCD cameras are used for acquiring the upper surface of the copper foil to be detected under the condition that an upper surface detection light source and a high-brightness backlight source provide illumination environments, and the second group of linear array CCD cameras are used for acquiring the lower surface of the copper foil to be detected under the condition that a lower surface detection light source provides illumination environments, so that the lower surface image is acquired.
7. A copper foil surface defect detection device, characterized in that the device comprises:
The camera adjusting module is used for adjusting the real-time acquisition speeds of the first group of linear array CCD cameras and the second group of linear array CCD cameras according to the real-time movement speed of the copper foil to be detected and the preset reference acquisition speed;
The image acquisition module is used for acquiring an upper surface image of the copper foil to be tested acquired by the first group of linear array CCD cameras at the real-time acquisition speed and acquiring a lower surface image acquired by the second group of linear array CCD cameras at the real-time acquisition speed;
the feature acquisition module is used for acquiring corresponding feature point pairs in the upper surface image and the lower surface image;
The region identification module is used for identifying potential defect regions in the upper surface image and the lower surface image according to the corresponding characteristic point pairs;
The first detection module is used for carrying out surface defect detection on the potential defect area to obtain a hidden defect detection result;
The second detection module is used for carrying out surface defect detection on the upper surface image to obtain an upper surface defect detection result, and carrying out surface defect detection on the lower surface image to obtain a lower surface defect detection result;
The result generation module is used for generating a copper foil surface defect detection result according to the hidden defect detection result, the upper surface defect detection result and the lower surface defect detection result;
The identifying potential defect areas in the upper surface image and the lower surface image according to the corresponding feature point pairs comprises:
Calculating displacement vectors between the corresponding feature point pairs;
Judging whether displacement exists between the upper surface image and the lower surface image according to the displacement vector;
when it is determined that there is displacement, the areas of the upper surface image and the lower surface image corresponding to the displacement vectors are identified as potential defect areas.
8. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the copper foil surface defect detection method according to any one of claims 1 to 6 when the computer program is executed.
9. A computer-readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the steps of the copper foil surface defect detection method according to any one of claims 1 to 6.
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