CN114359176A - Panel detection method and device, electronic equipment and storage medium - Google Patents

Panel detection method and device, electronic equipment and storage medium Download PDF

Info

Publication number
CN114359176A
CN114359176A CN202111547308.4A CN202111547308A CN114359176A CN 114359176 A CN114359176 A CN 114359176A CN 202111547308 A CN202111547308 A CN 202111547308A CN 114359176 A CN114359176 A CN 114359176A
Authority
CN
China
Prior art keywords
area
region
electrode
panel
suspected defect
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202111547308.4A
Other languages
Chinese (zh)
Other versions
CN114359176B (en
Inventor
朱小明
匡梦良
殷亚男
许超
张鑫
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Suzhou Mega Technology Co Ltd
Original Assignee
Suzhou Mega Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Suzhou Mega Technology Co Ltd filed Critical Suzhou Mega Technology Co Ltd
Priority to CN202111547308.4A priority Critical patent/CN114359176B/en
Priority claimed from CN202111547308.4A external-priority patent/CN114359176B/en
Publication of CN114359176A publication Critical patent/CN114359176A/en
Application granted granted Critical
Publication of CN114359176B publication Critical patent/CN114359176B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Landscapes

  • Image Processing (AREA)

Abstract

The embodiment of the invention provides a panel detection method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring an image of a panel to be detected; determining a region of interest in an image of a panel to be detected; identifying a suspected defect area in the region of interest based on a gray difference between pixels in the region of interest; and determining a foreign matter region based on the suspected defect region. The scheme can quickly and accurately determine the foreign matter area in the panel. Thus, the reliability of panel detection is ensured.

Description

Panel detection method and device, electronic equipment and storage medium
Technical Field
The present invention relates to the field of panel detection, and more particularly, to a panel detection method, a panel detection apparatus, an electronic device, and a storage medium.
Background
Chip On Glass (COG for short) is a technology in which a driving circuit Chip is directly bonded On a Glass substrate, and is widely applied to various display products such as liquid crystal display and electroluminescence technologies. In the COG process, a Conductive pin of a driving circuit is aligned to an electrode (bump) on a glass substrate, an Anisotropic Conductive Film (ACF) is used as a bonding dielectric material, and the Conductive pin of the driving circuit is connected and conducted with the electrode on the glass substrate at a high temperature and a high voltage for a certain period of time. Similarly, the flexible circuit board On Glass (FPC On Glass, FOG for short) is a technique in which a flexible circuit board (FPC) is directly bonded to a Glass substrate, and the process is similar to COG. Similarly, Chip On Film (COF) technology is a technology in which a semiconductor chip is first packaged on a flexible substrate, and then the flexible substrate of the packaged product is bonded to a glass substrate, and the manufacturing process is similar to COG.
The panel detection technology can be used for detecting the appearance of the panel, the indentation condition of the conductive particles in the panel and the like. In addition to the problems of appearance and conductive particles, there are some panels that may have foreign matter therein, resulting in an unsatisfactory panel quality. Therefore, a panel inspection method is needed to detect the foreign objects on the panel.
Disclosure of Invention
The present invention has been made in view of the above problems. The invention provides a panel detection method, which comprises the following steps: acquiring an image of a panel to be detected; determining a region of interest in an image of a panel to be detected; identifying a suspected defect area in the region of interest based on a gray difference between pixels in the region of interest; and determining a foreign matter region based on the suspected defect region.
Illustratively, determining the foreign-substance area based on the suspected-defect area includes: determining the area of a suspected defect area; judging whether the suspected defect area meets a preset condition, wherein the preset condition comprises that the area of the suspected defect area meets the area requirement; and determining the suspected defect area meeting the preset condition as a foreign matter area.
Illustratively, prior to determining the area of the suspected defect region, the method further comprises: and performing morphological processing on the identified suspected defect area to process a noise area related to the suspected defect area.
Illustratively, morphologically processing the identified suspected defect regions includes: merging the suspected defect areas with the distance smaller than the merging distance threshold; the method further comprises the following steps: a user interface is provided, wherein the user interface includes a third operable control for setting the merge distance threshold in response to a user operation.
Illustratively, determining the area of the suspected defect region includes: determining the area of each suspected defect region; adding the areas of all the suspected defect areas to obtain the total area of all the suspected defect areas; judging whether the suspected defect area meets the preset condition comprises the following steps: and judging whether the total area of the suspected defect area meets the total area requirement.
Illustratively, the region of interest includes an electrode area, and summing the areas of all suspected defect areas to obtain a total area of all suspected defect areas includes: determining the area of a suspected defect region in each electrode region; the areas of the suspected defect areas in all the electrode areas within the region of interest are added to obtain the total area of the suspected defect areas in all the electrode areas.
Illustratively, the region of interest includes an electrode region, and determining an area of the suspected defect region includes: determining the area of a suspected defect region in each electrode region; judging whether the suspected defect area meets the preset condition comprises the following steps: and judging whether the area of the suspected defect area in each electrode area meets the requirement of a single area.
Illustratively, a user interface is provided, wherein the user interface includes a second operable control for setting an area requirement threshold for a suspected defect area in the region of interest in response to an operation by a user.
Illustratively, determining a region of interest in an image of a panel to be detected comprises: and performing image segmentation on the image of the panel to be detected according to the gray threshold value so as to extract an electrode area in the image of the panel to be detected, wherein the interested area comprises the electrode area.
Illustratively, a user interface is provided, wherein the user interface includes a fourth operable control for setting the grayscale threshold in response to user manipulation.
Illustratively, receiving coordinates of a target area input by a user; cutting out a target area from the image of the panel to be detected according to the coordinates of the target area; the image segmentation of the image of the panel to be detected according to the gray threshold value to extract the electrode area in the image of the panel to be detected comprises the following steps: image segmentation is performed for the target region to determine the electrode region.
Illustratively, determining a region of interest in an image of a panel to be detected comprises: responding to the operation of a user on the image of the panel to be detected, and acquiring boundary coordinates of an electrode area in the image; determining an electrode area from the boundary coordinates, wherein the region of interest comprises the electrode area.
Illustratively, determining the electrode area from the boundary coordinates includes: and in response to the adjustment operation of the user for the boundary coordinates, scaling the boundary of the electrode area.
Illustratively, the method further comprises: a user interface is provided, wherein the user interface includes a fifth operable control for setting a size for scaling the boundary of the electrode area in response to a user operation.
Illustratively, determining a region of interest in an image of a panel to be detected comprises: determining an electrode area in an image of a panel to be detected; an electrode gap region is determined from the electrode regions, wherein the region of interest includes the electrode gap region.
Illustratively, the method further comprises: a user interface is provided, wherein the user interface includes a first operable control for setting a gray scale difference threshold between a suspected defect region and a normal region in the region of interest in response to a user operation.
According to another aspect of the present invention, there is also provided a panel detecting apparatus including: the image acquisition module is used for acquiring an image of the panel to be detected; the ROI determining module is used for determining a region of interest in an image of a panel to be detected; the primary identification module is used for identifying a suspected defect area in the region of interest based on the gray difference among the pixels in the region of interest; and the foreign matter determining module is used for determining a foreign matter area based on the suspected defect area.
According to yet another aspect of the present invention, there is also provided an electronic device comprising a processor and a memory, wherein the memory has stored therein computer program instructions for executing the panel detection method as described above when the computer program instructions are executed by the processor.
According to yet another aspect of the present invention, there is also provided a storage medium having stored thereon program instructions for performing the panel detection method as described above when executed.
According to the technical scheme, the suspected defect area can be determined according to the gray level difference of the pixels in the image of the panel to be detected, and then the foreign matter area can be determined according to the suspected defect area. The scheme can quickly and accurately determine the foreign matter area in the panel. Thus, the reliability of panel detection is ensured.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent by describing in more detail embodiments of the present invention with reference to the attached drawings. The accompanying drawings are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings, like reference numbers generally represent like parts or steps.
FIG. 1 shows a schematic flow diagram of a panel detection method according to one embodiment of the invention;
FIG. 2 shows a partial schematic view of an image of a panel to be inspected according to one embodiment of the invention;
FIG. 3 shows a schematic diagram of a user interface according to one embodiment of the invention;
FIG. 4 shows a schematic flow diagram for determining a region of interest in an image of a panel to be detected according to one embodiment of the present invention;
FIG. 5 shows a schematic flow diagram for determining a region of interest in an image of a panel to be detected according to another embodiment of the present invention;
FIG. 6 shows a schematic flow chart of determining a foreign object region based on a suspected defect region according to one embodiment of the invention;
FIG. 7 shows a schematic flow chart of determining an area of a suspected defect region according to one embodiment of the invention;
FIG. 8 shows a schematic block diagram of a panel detection apparatus according to one embodiment of the present invention; and
FIG. 9 shows a schematic block diagram of an electronic device according to one embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, exemplary embodiments according to the present invention will be described in detail below with reference to the accompanying drawings. It is to be understood that the described embodiments are merely a subset of embodiments of the invention and not all embodiments of the invention, with the understanding that the invention is not limited to the example embodiments described herein. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the invention described herein without inventive step, shall fall within the scope of protection of the invention.
According to one embodiment of the present invention, a panel inspection method is provided. FIG. 1 shows a schematic flow diagram of a panel inspection method 100 according to one embodiment of the invention. The method 100 includes the following steps.
Step S110, an image of the panel to be detected is acquired.
The image of the panel to be detected may be an original image acquired by an image acquisition device such as a camera in the panel detection system, or may be an image obtained after preprocessing the original image. The preprocessing operation may include all operations for more clearly performing panel detection. For example, the preprocessing operation may include a denoising operation such as filtering. The image may contain all or part of the electrodes in the panel to be detected.
Step S120, determining a region of interest in the image of the panel to be detected.
It can be understood that the image of the panel to be detected is acquired to detect the panel to be detected, and the region of interest may be a region on the panel to be detected, which is desired to be detected by any user, for example, an electrode region on the panel to be detected, an electrode gap region between electrodes on the panel to be detected, and the like. In order to reduce the interference in the subsequent steps, the region of interest in the image of the panel to be detected can be extracted after it has been determined. The extraction process may be implemented in response to an input from a user, may also be implemented based on an image segmentation method, and the like, which are not limited herein.
Step S130 identifies a suspected defect region in the region of interest based on the gray-scale difference between pixels in the region of interest.
Fig. 2 shows a partial schematic view of an image of a panel to be inspected according to an embodiment of the invention. Referring to fig. 2, the gray rectangular area is an electrode area including a plurality of electrodes. The black area between every two adjacent electrodes is the electrode gap area. When the region of interest is an electrode region, the gray difference between every two adjacent pixels can be calculated for all pixels within the electrode region, respectively. It can be understood that as the gray scale difference between pixels is larger, the corresponding brightness difference degree presented in fig. 2 is more obvious. Suspected defect regions in the electrode region can be identified based on the difference in gray levels between the pixels. Illustratively, any image segmentation method may be utilized to identify suspected defect regions in the electrode region, such as region-based image segmentation, edge-based image segmentation, and the like. The suspected defect regions identified in this step may include real defect regions and false defect regions (e.g., conductive particles) that were misidentified. Similarly, when the region of interest is an electrode gap region, the gray level difference between each two adjacent pixels can be calculated. A suspected defect region 210 in the inter-electrode gap region may be identified based on the resulting gray differences.
In step S140, a foreign object region is determined based on the suspected defect region.
According to the foregoing step S130, the suspected defect area in the region of interest can be identified and extracted, and as described above, the suspected defect area includes two types of defect areas, i.e., true and false defect areas. For the detection of the suspected defect area, the real defect area can be determined as a foreign area. For example, if a foreign object exists on the panel to be detected, the display of the panel is poor. The image of the panel to be detected can be represented as a bright point, a dark point, a bright line, a dark line or a light spot. Therefore, the foreign object region can be determined by a detection method that detects whether the area of the suspected defect region or the pixel value of the pixel in the suspected defect region, or the like, exceeds a preset threshold. If the foreign matter area is determined to be included in the panel to be detected, the quality of the panel to be detected can be determined to be unqualified. Optionally, this may be alarmed to remind the user to remove the poor quality panel in time.
According to the technical scheme, the suspected defect area can be determined according to the gray level difference of the pixels in the image of the panel to be detected, and then the foreign matter area can be determined according to the suspected defect area. The scheme can quickly and accurately determine the foreign matter area in the panel. Thus, the reliability of panel detection is ensured.
For example, the step S120 of determining the region of interest in the image of the panel to be detected may include performing image segmentation on the image of the panel to be detected according to a gray threshold value to extract the electrode region in the image of the panel to be detected. Wherein the region of interest comprises an electrode region.
It is understood that image segmentation refers to an operation of extracting a region of interest in an image based on some rule. In this embodiment, the image of the panel to be detected may be image-segmented based on a grayscale threshold. For example, the gray values of all pixels on the image of the panel to be detected may be respectively compared with a gray threshold value, and when the gray value of a pixel on the image is greater than or equal to the gray threshold value, the pixel may be determined to belong to the electrode region in the image. Based on this, the division of the electrode region and the electrode gap region in the image of the panel to be detected can be realized, and the electrode region can be extracted accordingly. Alternatively, the extracted electrode region may be directly used as the region of interest. Or, the electrode gap region obtained after the electrode region is extracted may be used as the region of interest. The grayscale threshold may be set in response to a user operation, or may be set according to experience of image segmentation of most panels to be detected before the panel detection apparatus leaves a factory.
Thereby, the region of interest can be determined by means of image segmentation. The method has the advantages of good positioning effect, high segmentation precision and the like, and can reduce the interference in the region of interest obtained by segmentation to a great extent.
Illustratively, the method 100 may include providing a user interface. FIG. 3 shows a schematic diagram of a user interface according to one embodiment of the invention. The user interface includes a fourth operable control 310, shown in FIG. 3 as "Bump minimum grayscale value," for setting a grayscale threshold in response to user manipulation. The fourth operable control 310 may be a text entry box, a tuner or filter box, or the like. For example, when the fourth operable control 310 is a tuner, the user may adjust the grayscale threshold by clicking the up and down arrows after "Bump minimum grayscale value". Specifically, clicking on the up arrow may increase the grayscale threshold, and clicking on the down arrow may decrease the grayscale threshold. It is to be understood that the setting of the gradation threshold value to 80 in this embodiment is merely an example, and is not a limitation of the gradation threshold value. The user can set the gray threshold value reasonably according to actual requirements.
Therefore, the user can set the corresponding gray threshold value through the fourth operable control 310 as required to realize accurate segmentation of the image of the panel to be detected, so that the requirements of different users are met, and the use experience is improved.
Illustratively, the method 100 may further include receiving coordinates of the target area input by the user, and cutting out the target area in the image of the panel to be detected according to the coordinates of the target area.
It can be understood that, since the panel to be detected may have thousands of electrodes, the size of the image of the panel to be detected, which is correspondingly acquired, may be too large, and the interference data therein is too much, which may affect the accuracy of the panel detection result. Therefore, the user can select a target area on the image of the panel to be detected as a targeted area for panel detection. For example, the user may input the coordinates of the selected target area through an input device such as a keyboard. Taking the target area as a rectangle as an example, the coordinates input by the user may be coordinate values of two points, and the coordinate values of the two points are respectively used as position coordinates of an upper left vertex and a lower right vertex or an upper left vertex and an upper right vertex constituting the target area, so as to determine the target area. Alternatively, the user may directly draw the target area at a specific position on the screen using an input device such as a mouse or a touch screen. The coordinates of the start point and the end point of the cursor corresponding to the mouse can be respectively used as the coordinates of different vertexes of the target area. And after the target area is determined, directly cutting the target area from the image of the panel to be detected. In general, the width value for each electrode may be about 30 pixels in size. To ensure reasonableness in the size of the target area and ensure panel detection accuracy, the user may set the target area to 1024 pixels by 1024 pixels. Thus, 20-30 electrodes may be included in the target region.
Based on this, in the above-described image segmentation step, image segmentation may be performed for the target region according to a grayscale threshold value to extract the electrode region in the target region. A person skilled in the art can understand a specific embodiment of performing image segmentation on the target region according to the gray threshold by reading the above description related to performing image segmentation on the image of the panel to be detected according to the gray threshold, and details are not described herein for brevity.
Therefore, the interference except the target area in the image of the panel to be detected can be effectively removed, and the influence on the accuracy of the panel detection result due to the excessive noise in the image is avoided. In addition, the calculation amount is obviously reduced, and the working performance of the system is improved.
Fig. 4 shows a schematic flow chart of the step S120 of determining a region of interest in an image of a panel to be detected according to an embodiment of the present invention. As shown in fig. 4, step S120 may include the following steps. In this embodiment, the region of interest comprises an electrode region.
Step S121, in response to an operation of the user on the image of the panel to be detected, acquiring boundary coordinates of the electrode region in the image.
For example, a user may click on four vertices or a group of diagonal vertices of an electrode in an image of a panel to be detected by using any suitable input device, such as a mouse or a touch screen, to obtain boundary coordinates of the electrode region. By repeatedly performing the above-described operations, the boundary coordinates of the electrode areas of the plurality of electrodes can be obtained. Step S122, determining an electrode area according to the boundary coordinates, wherein the interested area comprises the electrode area.
The boundary coordinates may be obtained in step S121, and for an electrode area, the obtained boundary coordinates are respectively used as coordinates of four vertices or coordinates of a set of diagonal vertices of a rectangular frame, and the electrode area may be selected by using the rectangular frame. It will be appreciated that this rectangular frame is the bounding frame of the electrode area.
The user can thus easily determine the electrode area and use it as the region of interest. The algorithm of the scheme is simple, easy to implement and convenient for user operation.
For example, the step S122 of determining the electrode region according to the boundary coordinates may include scaling the boundary of the electrode region in response to an adjustment operation of the boundary coordinates by a user. For example, the user may perform movement adjustment on the vertex of the originally selected electrode to adjust the boundary coordinates. After the boundary coordinates are changed, the boundary of the corresponding electrode area is changed. Taking one vertex in the electrode, for example the top left vertex, as an example, the user moves it a certain distance to the left and correspondingly the bottom left vertex also moves it the same distance to the left. This allows the boundary of the electrode region to be widened to the left. Conversely, if the upper left vertex and the lower left vertex are moved to the right, the boundary of the electrode area can be retracted to the right. Similarly, the user moves the top left vertex upward a certain distance and correspondingly moves the top right vertex upward the same distance. This makes it possible to spread the boundary of the electrode region outward. Conversely, if the upper left vertex and the upper right vertex are moved downward, the boundary of the electrode region may be retracted downward.
According to the technical scheme, the scaling adjustment of the boundary of the electrode area can be realized. It is understood that an electrode boundary is a location where an electrode is adjacent to its gap. In the image of the panel to be detected, the position usually has a large pixel value change, which significantly affects the subsequent foreign object detection process, and further affects the panel detection result. Therefore, the boundary of the electrode area is adjusted according to the requirement, so that the interference data in the region of interest in the image of the panel to be detected is effectively reduced, the calculation amount is reduced for subsequently determining the foreign matter area, and the accuracy of panel detection is improved.
Illustratively, the method 100 may further include providing a user interface. Referring again to fig. 3, the user interface may include a fifth operable control 320 for setting a size to scale the boundary of the electrode area in response to a user operation. Similarly, the fifth operable control 320 may be a text entry box, a tuner or filter box, or the like. The fifth operable controls 320 are shown in fig. 3 as four controls "TOPX direction", "TOPY direction", "BottomX direction", and "BottomY direction". Where "TOP" and "Bottom" are for the electrode region, "TOP" may represent an upper boundary of the electrode region, and "Bottom" may represent a lower boundary of the electrode region. The "TOPX-direction" may denote an adjustment of the upper boundary for the electrode area in the horizontal direction, i.e. the upper boundary is lengthened or shortened to the left and/or to the right in the horizontal direction. The "TOPY direction" may denote an adjustment in the vertical direction for the upper boundary of the electrode area, i.e. the upper boundary moves up or down in the vertical direction. The functions of the two controls of the "BottomX direction" and the "BottomY direction" can be known in the same way. It will be appreciated that, when the electrode region is adjusted, in order to ensure that the boundary of the electrode region is a regular closed rectangle, after one of the controls is operated, the same operation can be performed on the control associated therewith. Taking the "TOPX direction" control as an example, when the fifth operable control 320 is a dial, the user can perform the scaling size adjustment on the boundary of the electrode area by clicking the up and down arrows behind the "TOPX direction". It is understood that when the value after the "TOPX direction" is a positive number, it may mean that the extension processing is performed on the basis of the length of the upper boundary of the current electrode region. For example, setting the value after the "TOPX direction" to 2, the length of the upper boundary of the electrode region may be extended by 2 pixels to the right or left. Alternatively, the length of the upper boundary of the electrode region may be extended by 1 pixel size to the left and right, respectively. When the value after the "TOPX direction" is negative, the pixel size is correspondingly shortened in a completely opposite way to the above scheme. After the upper boundary of the electrode area is lengthened or shortened, the lower boundary of the electrode area is lengthened or shortened by the same pixel size by using a control in the BottomX direction, and after the adjustment of the upper boundary and the lower boundary of the electrode area is finished, the left boundary and the right boundary of the electrode area are adaptively adjusted to ensure that the boundary of the electrode area is a regular closed rectangle.
The detailed implementation of the operation of the remaining three controls can be understood by those skilled in the art from reading the above description of the "TOPX direction" control, and will not be described herein for brevity.
According to the technical scheme, the user can automatically adjust the boundary of the electrode area only by executing simple operation on the fifth operable control 320, so that different requirements of the user can be met, personalized customization is realized, the user does not need to execute complicated operation, and the use experience is improved.
Fig. 5 shows a schematic flow chart of the step S120 of determining a region of interest in an image of a panel to be detected according to another embodiment of the present invention. As shown in fig. 5, step S120 may include the following steps. In this embodiment, the region of interest comprises an electrode gap region.
Step S123, determining an electrode area in the image of the panel to be detected.
For example, the electrode area in the image of the panel to be detected may be determined in response to an operation by the user. Wherein the electrode area comprises at least one electrode. In one embodiment, a user may perform a drag operation on an image of a panel to be detected along a boundary of at least one electrode in the image using an external input device such as a mouse or a touch screen. First, a mouse is used to click on a vertex of the electrode, such as the top left vertex, and a dragging operation is performed from the vertex until a vertex of a diagonal of the vertex, such as the bottom right vertex. The boundary of at least one electrode can thereby be determined, on the basis of which the electrode area in the image of the panel to be detected can be determined. Alternatively, the electrode region may be extracted by using a threshold-based image segmentation method or the like to determine the electrode region in the image of the panel to be detected.
And step S124, determining an electrode gap area according to the electrode area, wherein the region of interest comprises the electrode gap area.
The electrode area in the image of the panel to be detected can be determined based on step S123. As previously mentioned, the electrode area comprises at least one electrode, and an electrode gap exists between each adjacent electrode, all of the electrode gaps constituting the electrode gap area. And then using the determined electrode gap area as an interested area for subsequent foreign matter area detection.
According to the technical scheme, the electrode area in the image of the panel to be detected is determined, and the electrode gap area can be determined based on the electrode area. It will be appreciated that the above solution is easier to implement and less error than a solution in which the electrode gap region is determined directly, by determining the electrode region indirectly.
Illustratively, the user interface provided by the method 100 may include a first operable control. The first operable control shown in fig. 3 comprises an operable control "gray value difference". The first operable control is used for setting a threshold value of gray level difference between the suspected defect area and the normal area in the region of interest for the aforementioned step S130 in response to the user' S operation. When the gray difference between the pixels in the region of interest exceeds the gray difference threshold, the relevant pixels may be identified as part of the pixels in the suspected defect area, whereas all the pixels may belong to part of the pixels in the normal area. As mentioned above, the region of interest may be an electrode region in the image of the panel to be detected, or may be an electrode gap region in the image of the panel to be detected.
When the slider after the operable control in fig. 3 is "enabled for detection" slides to the right end, it may be indicated that the region of interest is an electrode region in the image of the panel to be detected, and then the "gray value difference" control 331 is used to set a gray value difference threshold between the suspected defect region and the normal region in the electrode region, for example, to 60. The user can adjust the value of the gray scale difference threshold by clicking the up and down arrows behind the "gray scale difference" control 331. Specifically, clicking on the up arrow may increase the gray difference threshold, and clicking on the down arrow may decrease the gray difference threshold.
When the slider of the operable control in fig. 3 after "enabling gap defect detection" slides to the right end, it may be indicated that the region of interest is an electrode gap region in an image of the panel to be detected, and then foreign matter region detection is performed on the electrode gap region. Similarly, a gray scale difference threshold between the suspected defect region and the normal region in the electrode gap region can be set using the "gray scale value difference" control 332, for example, to 120. The numerical adjustment operation for the gray level difference threshold is not described herein again. It is understood that the foreign matter region detection for the electrode region and the electrode gap region is performed separately in most cases. In other words, "enable detection" and "enable gap defect detection" in fig. 3 may not be turned on at the same time.
Therefore, a user can reasonably set the gray difference threshold between the suspected defect area and the normal area in the area of interest by using the first operable control according to actual conditions, the possibility of falsely detecting the normal area as the suspected defect area is reduced, and further excessive calculation data are prevented from being introduced for subsequent calculation. Moreover, the implementation method is convenient for user operation and improves user experience.
Fig. 6 shows a schematic flowchart of the step S140 of determining a foreign object area based on the suspected-defect area according to an embodiment of the present invention. As shown in fig. 6, step S140 may include the following steps.
Step S141 determines the area of the suspected defect region.
For example, after the suspected defect area is identified according to the step S130, the number of all pixel points in the suspected defect area may be counted. It will be appreciated that the number of pixel points may reflect the area of the suspected defect region. Illustratively, the number of the pixel points may be directly used as the area of the suspected defect region. Alternatively, the size of one pixel point can be calculated according to the resolution of the image of the panel to be detected. And multiplying the number of all pixel points by the size of one pixel point to calculate the area of the suspected defect area.
Step S142, determining whether the suspected defect area meets a preset condition, where the preset condition includes that the area of the suspected defect area meets an area requirement.
After the area of the suspected defect area is determined through the calculation, whether the area of the suspected defect area meets the area requirement or not can be judged. The area requirement may include an area requirement threshold. When the area of the suspected defect area is greater than or equal to the first area requirement threshold and less than or equal to the second area requirement threshold, the suspected defect area may be considered to satisfy a preset condition. Otherwise, it is not satisfied.
In step S143, the suspected defect area satisfying the preset condition is determined to be a foreign object area.
For example, the area requirement threshold may be used to indicate a minimum or maximum area of the foreign object region. Therefore, when the area of the suspected defect region satisfies a predetermined condition, the suspected defect region is determined as a foreign region.
According to the technical scheme, whether the suspected defect area is a foreign matter area can be determined by judging whether the area of the suspected defect area meets the preset condition. It can be understood that the parameter of the area can reflect the difference between the foreign matter area and the normal area more directly and accurately, and the reliability is higher. In the image, especially in the electrode area, the conductive particles also have a gray level difference with the surrounding area, and the area occupied by the conductive particles is usually not too large. The suspected defect area is screened by utilizing the area requirement, so that the interference of conductive particles and the like is eliminated, and the accuracy of the foreign matter detection of the panel is effectively improved.
Fig. 7 shows a schematic flowchart of the step S141 of determining the area of the suspected-defect region according to one embodiment of the present invention. As shown in fig. 7, step S141 may include the following steps.
In step S141a, the area of each suspected defect region is determined. Optionally, for each suspected defect area in the region of interest, the number of pixel points therein is counted respectively.
In step S141b, the areas of all the suspected defect areas are added to obtain the total area of all the suspected defect areas.
The total area of all the suspected-defect regions in the region of interest can be obtained by adding the areas of each of the suspected-defect regions calculated by the above step S141 a. It is to be understood that the above-described addition is performed in units of suspected defect areas.
For example, the step S142 of determining whether the suspected-defect region satisfies the predetermined condition may include determining whether the total area of the suspected-defect region satisfies the total area requirement.
The total area requirement may include a total area requirement upper threshold and a total area requirement lower threshold. The total area requirement upper threshold may represent a maximum value of a total area of all suspected defect regions in the region of interest, and the total area requirement lower threshold may represent a minimum value of a total area of all suspected defect regions in the region of interest. It will be appreciated that the total area within the region of interest satisfies the total area requirement when the total area is between the upper threshold and the lower threshold of the total area requirement. Otherwise, the requirements are not met.
It is understood that certain noise data may be introduced during actual panel detection based on image imaging noise, etc. In the scheme, the condition for determining the suspected defect area as the foreign area is further limited, the accuracy of the determination result of the foreign area is ensured, and the robustness of noise processing is improved.
Illustratively, the region of interest includes an electrode region. The step S141b of adding the areas of all the suspected-defect regions to obtain the total area of all the suspected-defect regions may include: first, the area of the suspected defect region in each electrode region is determined. As described above, the area of each suspected defect region can be calculated by step S141 a. And each electrode region may include one or more suspected defect regions. For each electrode region, the areas of all the suspected defect regions are added to determine the area of the suspected defect region in each electrode region. Next, the areas of the suspected defect areas in all the electrode areas within the region of interest are added to obtain the total area of the suspected defect areas in all the electrode areas. It is understood that the area of the suspected defect area in all the electrode areas is added in units of electrode areas. The total area of the suspected defect regions in all electrode regions can thus be obtained.
Thus, the area of the suspected defect region can be calculated for each electrode region, and if the suspected defect region does not exist in the electrode region, the areas are not added. Therefore, before the addition operation is performed, the electrode area in which the suspected defect area does not exist can be eliminated, thereby reducing the data amount of the subsequent processing.
Illustratively, the region of interest includes an electrode region. The step S141 of determining the area of the suspected-defect region includes determining the area of the suspected-defect region in each electrode region. The determination method is as described above and will not be described herein again. Step S142 of determining whether the suspected defect region satisfies the preset condition includes determining whether the area of the suspected defect region in each electrode region satisfies the requirement of a single area.
Illustratively, the single area requirement may include a single electrode area upper limit and a single electrode area lower limit. Wherein the upper limit of the area of the single electrode represents the maximum value of the total area of all the suspected defect areas in the electrode, and the lower limit of the area of the single electrode represents the minimum value of the total area of all the suspected defect areas in the electrode. It will be appreciated that the total area of all suspected defect regions within each electrode region satisfies the individual electrode area requirement when the total area is between the upper and lower individual electrode area limits. Otherwise, the requirements are not met.
It will be appreciated that each electrode has its own electrical conduction. And foreign matter in the electrode will affect its electrical conduction. In the above scheme, the condition that the suspected defect area is determined as the different area is further limited to include the area of the suspected defect area in the single electrode area, so that the qualified electric conduction quality of each electrode in the panel to be detected is ensured, and the quality of the panel to be detected is further ensured.
Illustratively, a second operable control 350, shown in fig. 3 as "single root area lower limit", "single root area upper limit", "multiple root area lower limit", "defect area lower limit", and "defect area upper limit", may also be included in the user interface provided by the method 100 for setting an area requirement threshold for a suspected defect region in the region of interest in response to a user operation. It will be appreciated that the "single root area lower limit", "single root area upper limit", "multi-root area lower limit", and "multi-root area lower limit" in the second operable control 350 are valid when the region of interest is an electrode region. The "lower defect area limit" and the "upper defect area limit" in the second operable control 350 are valid when the region of interest is an electrode gap region. The function of the second operable control 350 can be understood by those skilled in the art from reading the above description of determining the area of the suspected defect region, and is not described herein again for brevity. The user can adjust the numerical value of the area requirement threshold value by clicking the up-down arrows after the 'single area lower limit', 'single area upper limit', 'multi-root area lower limit', 'defect area lower limit' and 'defect area upper limit'. Specifically, clicking on the up arrow may increase the area requirement threshold, and clicking on the down arrow may decrease the area requirement threshold.
Therefore, the user can conveniently and quickly perform custom setting on the area requirement threshold according to actual requirements, the requirements of different users are met, and the use experience is improved.
Through the technical scheme, the position of the foreign matter area can be determined on the image of the panel to be detected. The image in which the foreign object region is detected can be extracted for the convenience of subsequent operations such as processing the foreign object region. For example, the user may turn on or off the function of saving the foreign object area image by sliding the slider after the operable control "save thumbnail" shown in fig. 3.
Preferably, before determining the area of the suspected-defect region in step S141, morphological processing may be further included on the identified suspected-defect region to process a noise region related to the suspected-defect region.
For example, morphologically processing the identified suspected defect regions may include performing dilation and erosion operations on the suspected defect regions, respectively. The above-described dilation operation may be understood as enlarging the suspected defect area 210 of fig. 2, for example. Specifically, each pixel in the suspected-defect area 210 may be scanned by a structural element, and an or operation is performed with each pixel in the structural element and the pixel covered by the structural element, where the pixel is 0 if both the pixels are 0, and otherwise the pixel is 1. Conversely, the etching operation may scan each pixel in the suspected-to-be-defective region 210 with a structural element, and each pixel in the structural element with the pixel covered by the structural element, wherein the pixel is 1 if both are 1, and 0 otherwise. Typically, these two operations are performed sequentially, so that the noise region associated with the suspected defect region can be processed.
Therefore, the noise area connected with the suspected defect area can be effectively removed, part of pixel points in the area of interest in contact with the suspected defect area can be merged into the suspected defect area, small holes in the suspected defect area are filled, and the suspected defect area with a smoother boundary and higher accuracy is obtained. And furthermore, an accurate data base is provided for the foreign matter detection of the subsequent panel.
Illustratively, morphologically processing the identified suspected defect regions may include merging for suspected defect regions having a distance less than a merge distance threshold. As previously mentioned, the method 100 may also include providing a user interface. Referring again to FIG. 3, the user interface may include a third operable control 340, shown in FIG. 3 as a "merge threshold," for setting a merge distance threshold in response to user manipulation. Wherein the merged distance threshold is used to limit the distance between adjacent boundaries of different suspected defect areas. And merging the two suspected-defect areas when the distance between the adjacent boundaries of the two suspected-defect areas is smaller than a merging distance threshold. Otherwise, no processing is performed. For example, the combination treatment may be performed by the above-described expansion and etching operations. The user can adjust the numerical value of the merging distance threshold by clicking the arrow after the merging threshold. Specifically, clicking on the up arrow may increase the merge distance threshold, and clicking on the down arrow may decrease the merge distance threshold.
Therefore, under the condition that interference data influencing the detection result of the foreign matter area is not increased, the merged suspected defect area contains more effective information about the detection of the foreign matter area, and the accuracy of the detection result of the panel is improved.
According to another aspect of the invention, a panel detection device is also provided. FIG. 8 shows a schematic block diagram of a panel detection apparatus 800 according to one embodiment of the present invention. As shown in fig. 8, the apparatus 800 includes an image acquisition module 810, an ROI determination module 820, a primary identification module 830, and a foreign object determination module 840.
The image obtaining module 810 is used for obtaining an image of a panel to be detected.
The ROI determination module 820 is used to determine a region of interest in an image of a panel to be detected.
The primary identification module 830 is configured to identify a suspected defect area in the region of interest based on a gray difference between pixels in the region of interest.
The foreign object determination module 840 is configured to determine a foreign object region based on the suspected defect region.
According to another aspect of the invention, an electronic device is also provided. FIG. 9 shows a schematic block diagram of an electronic device 900 according to one embodiment of the invention. As shown in fig. 9, the electronic device 900 includes a processor 910 and a memory 920. The memory 920 stores computer program instructions, and the computer program instructions are executed by the processor 910 to perform the panel detecting method 100.
According to still another aspect of the present invention, there is also provided a storage medium. Stored on the storage medium are program instructions that, when executed, are operable to perform the panel detection method 100 described above. The storage medium may include, for example, a storage component of a tablet computer, a hard disk of a personal computer, Read Only Memory (ROM), Erasable Programmable Read Only Memory (EPROM), portable compact disk read only memory (CD-ROM), USB memory, or any combination of the above storage media. The computer-readable storage medium may be any combination of one or more computer-readable storage media.
A person skilled in the art can understand specific implementation schemes of the panel detection apparatus, the electronic device, and the storage medium by reading the above description related to the panel detection method, and details are not described herein for brevity.
Although the illustrative embodiments have been described herein with reference to the accompanying drawings, it is to be understood that the foregoing illustrative embodiments are merely exemplary and are not intended to limit the scope of the invention thereto. Various changes and modifications may be effected therein by one of ordinary skill in the pertinent art without departing from the scope or spirit of the present invention. All such changes and modifications are intended to be included within the scope of the present invention as set forth in the appended claims.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the units is only one logical functional division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another device, or some features may be omitted, or not executed.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the invention and aiding in the understanding of one or more of the various inventive aspects. However, the method of the present invention should not be construed to reflect the intent: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
It will be understood by those skilled in the art that all of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where such features are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functions of some of the blocks in a panel detection apparatus according to embodiments of the present invention. The present invention may also be embodied as apparatus programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
The above description is only for the specific embodiment of the present invention or the description thereof, and the protection scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and the changes or substitutions should be covered within the protection scope of the present invention. The protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (15)

1. A panel inspection method, comprising:
acquiring an image of a panel to be detected;
determining a region of interest in the image of the panel to be detected;
identifying a suspected defect area in the region of interest based on a gray difference between pixels in the region of interest; and
determining a foreign object area based on the suspected defect area.
2. The method of claim 1, wherein the determining a foreign object area based on the suspected defect area comprises:
determining the area of the suspected defect area;
judging whether the suspected defect area meets a preset condition, wherein the preset condition comprises that the area of the suspected defect area meets an area requirement; and
and determining the suspected defect area meeting the preset condition as a foreign matter area.
3. The method of claim 2, wherein prior to said determining the area of the suspected defect region, the method further comprises:
and performing morphological processing on the identified suspected defect area to process a noise area related to the suspected defect area.
4. The method of claim 3, wherein,
the morphologically processing the identified suspected defect regions comprises:
merging the suspected defect areas with the distance smaller than the merging distance threshold;
the method further comprises the following steps:
providing a user interface, wherein the user interface includes a third operable control for setting the merge distance threshold in response to a user action.
5. The method of claim 2, wherein,
the determining the area of the suspected defect region comprises:
determining the area of each suspected defect region;
adding the areas of all the suspected defect areas to obtain the total area of all the suspected defect areas; the judging whether the suspected defect area meets a preset condition comprises the following steps:
and judging whether the total area of the suspected defect area meets the total area requirement.
6. The method of claim 5, wherein the region of interest comprises an electrode region,
the summing the areas of all the suspected defect regions to obtain a total area of all the suspected defect regions comprises:
determining the area of a suspected defect region in each electrode region;
adding the areas of the suspected defect areas in all electrode areas within the region of interest to obtain a total area of the suspected defect areas in all electrode areas.
7. The method of claim 2, wherein the region of interest comprises an electrode region,
the determining the area of the suspected defect region comprises:
determining the area of a suspected defect region in each electrode region;
the judging whether the suspected defect area meets a preset condition comprises the following steps:
and judging whether the area of the suspected defect area in each electrode area meets the requirement of a single area.
8. The method of claim 1, wherein the determining a region of interest in the image of the panel to be detected comprises:
and carrying out image segmentation on the image of the panel to be detected according to a gray threshold value so as to extract an electrode area in the image of the panel to be detected, wherein the interested area comprises the electrode area.
9. The method of claim 8, wherein the method further comprises:
receiving coordinates of a target area input by a user;
cutting out a target area in the image of the panel to be detected according to the coordinates of the target area;
the image segmentation of the image of the panel to be detected according to the gray threshold value to extract the electrode area in the image of the panel to be detected comprises:
performing image segmentation on the target region to determine the electrode region.
10. The method of claim 1, wherein the determining a region of interest in the image of the panel to be detected comprises:
responding to the operation of a user on the image of the panel to be detected, and acquiring boundary coordinates of an electrode area in the image;
determining the electrode area from the boundary coordinates, wherein the region of interest includes the electrode area.
11. The method of claim 10, wherein said determining the electrode area from boundary coordinates comprises:
and in response to the adjustment operation of the user for the boundary coordinates, scaling the boundary of the electrode area.
12. The method of claim 1, wherein the determining a region of interest in the image of the panel to be detected comprises:
determining an electrode area in an image of the panel to be detected;
determining an electrode gap region from the electrode regions, wherein the region of interest includes the electrode gap region.
13. A panel testing apparatus, comprising:
the image acquisition module is used for acquiring an image of the panel to be detected;
the ROI determining module is used for determining a region of interest in the image of the panel to be detected;
the primary identification module is used for identifying a suspected defect area in the region of interest based on the gray difference among the pixels in the region of interest;
and the foreign matter determining module is used for determining a foreign matter area based on the suspected defect area.
14. An electronic device comprising a processor and a memory, wherein the memory has stored therein computer program instructions for execution by the processor to perform the panel detection method of any of claims 1 to 12.
15. A storage medium having stored thereon program instructions for performing, when executed, the panel detection method of any one of claims 1 to 12.
CN202111547308.4A 2021-12-16 Panel detection method and device, electronic equipment and storage medium Active CN114359176B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111547308.4A CN114359176B (en) 2021-12-16 Panel detection method and device, electronic equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111547308.4A CN114359176B (en) 2021-12-16 Panel detection method and device, electronic equipment and storage medium

Publications (2)

Publication Number Publication Date
CN114359176A true CN114359176A (en) 2022-04-15
CN114359176B CN114359176B (en) 2024-07-09

Family

ID=

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115841445A (en) * 2022-04-18 2023-03-24 宁德时代新能源科技股份有限公司 Method, device and system for detecting cathode pole piece of composite material belt

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2020133046A1 (en) * 2018-12-27 2020-07-02 深圳配天智能技术研究院有限公司 Defect detection method and device
CN112348773A (en) * 2020-09-28 2021-02-09 歌尔股份有限公司 Screen defect detection method and device and electronic equipment
CN112837303A (en) * 2021-02-09 2021-05-25 广东拓斯达科技股份有限公司 Defect detection method, device, equipment and medium for mold monitoring
CN113538430A (en) * 2021-09-16 2021-10-22 深圳新视智科技术有限公司 Pole piece defect detection method, device, equipment and medium based on difference

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2020133046A1 (en) * 2018-12-27 2020-07-02 深圳配天智能技术研究院有限公司 Defect detection method and device
CN112348773A (en) * 2020-09-28 2021-02-09 歌尔股份有限公司 Screen defect detection method and device and electronic equipment
CN112837303A (en) * 2021-02-09 2021-05-25 广东拓斯达科技股份有限公司 Defect detection method, device, equipment and medium for mold monitoring
CN113538430A (en) * 2021-09-16 2021-10-22 深圳新视智科技术有限公司 Pole piece defect detection method, device, equipment and medium based on difference

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115841445A (en) * 2022-04-18 2023-03-24 宁德时代新能源科技股份有限公司 Method, device and system for detecting cathode pole piece of composite material belt
CN115841445B (en) * 2022-04-18 2024-05-17 宁德时代新能源科技股份有限公司 Method, device and system for detecting cathode pole piece of composite material belt

Similar Documents

Publication Publication Date Title
CN113688807B (en) Self-adaptive defect detection method, device, recognition system and storage medium
CN111340752A (en) Screen detection method and device, electronic equipment and computer readable storage medium
JP4657869B2 (en) Defect detection apparatus, image sensor device, image sensor module, image processing apparatus, digital image quality tester, defect detection method, defect detection program, and computer-readable recording medium
CN108629775B (en) Thermal state high-speed wire rod surface image processing method
CN115908269B (en) Visual defect detection method, visual defect detection device, storage medium and computer equipment
CN112577969B (en) Defect detection method and defect detection system based on machine vision
KR101032446B1 (en) Apparatus and method for detecting a vertex on the screen of a mobile terminal
CN114897847A (en) Image processing method and device, computer readable storage medium and electronic device
CN112734774A (en) High-precision fundus blood vessel extraction method, device, medium, equipment and system
CN111861979A (en) Positioning method, positioning equipment and computer readable storage medium
US20220215521A1 (en) Transmission image-based non-destructive inspecting method, method of providing non-destructive inspection function, and device therefor
EP3904865A1 (en) Image processing device, image processing method, and image processing program
CN112734773B (en) Sub-pixel-level fundus blood vessel segmentation method, device, medium and equipment
JP2011008482A (en) Defect detection method, defect detection device and defect detection program
WO2023109446A1 (en) Conductive particle identification method and apparatus, electronic device, and storage medium
CN114359176B (en) Panel detection method and device, electronic equipment and storage medium
CN114359176A (en) Panel detection method and device, electronic equipment and storage medium
CN114359179A (en) Panel detection method, system, electronic device and storage medium
CN114359177A (en) Image display method and device for panel to be detected, electronic equipment and storage medium
KR101521620B1 (en) method of segmentation of die image for semiconductor device examination
CN114359178A (en) Panel detection method and device, electronic equipment and storage medium
WO2024095721A1 (en) Image processing device and image processing method
KR102616867B1 (en) Method for non-destructive inspection
JP2006135700A (en) Image inspection device, image inspection method, control program and readable storage medium
CN111080664B (en) Data processing method and device, computer storage medium and computer

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant