A method and device for detecting a screen cutting surface and a storage medium

Abstract

The application relates to a screen cutting surface detection method and device and a storage medium, which comprises the following steps: acquiring first image information and corresponding model information of a to-be-detected screen; determining a plurality of detection points of the to-be-detected screen according to the corresponding model information; generating second image information of the to-be-detected screen according to the plurality of detection points of the to-be-detected screen and the first image information; and determining a treatment scheme of the to-be-detected screen by comparing the second image information with preset screen image based on a comparison algorithm. The first image information and the corresponding model information of the to-be-detected screen are acquired to determine the plurality of detection points of the to-be-detected screen, the second image information of the to-be-detected screen is generated from the plurality of detection points and the first image information, and finally the treatment scheme of the to-be-detected screen is determined by comparing the second image information with the preset screen image, so that positioning detection of a plurality of points of different models is realized, different edge conditions or defect problems are coped with, the quality of the screens leaving the factory is better, and the user experience is better.

Description

[Technical Field]

[0001] This application relates to the field of communication technology, and in particular to a method, apparatus and storage medium for detecting screen cut surfaces. [Background Technology]

[0002] With the advancement of science and technology, electronic devices are closely related to our lives. As the display screens that enable interaction between electronic devices and people, they are particularly important. In the production process of screens, the screen cutting process is of paramount importance. Most screens on the market are cut using lasers, and then the cut edges are removed by a pressing mechanism.

[0003] However, after the pressing mechanism removes the cut edges, it can cause burrs or minor defects at the edges of the screen. If screens with minor defects are not identified, they can cause problems such as light leakage and missing pixels. If burrs appear, they can scratch the phone casing during screen installation. If the burr residue enters the circuit board during installation, it can also affect the normal operation of the circuit. [Summary of the Invention]

[0004] In order to better detect burrs or minor defects at the edges of the screen and avoid problems such as light leakage and missing pixels, this invention acquires the first image information and corresponding model information of the screen under test to determine multiple detection points of the screen under test. Then, the second image information of the screen under test is generated from the multiple detection points and the first image information. Finally, the second image information is compared with a preset screen image to determine the treatment plan for the screen under test.

[0005] The present invention proposes the following solution:

[0006] A method for detecting screen cut surfaces, comprising:

[0007] Obtain the first image information and corresponding model information of the screen under test;

[0008] Based on the corresponding model information, determine multiple detection points for the screen to be tested;

[0009] Based on multiple detection sites of the screen under test and the first image information, the second image information of the screen under test is generated.

[0010] The processing plan for the screen to be tested is determined by comparing the second image information with the preset screen image using a comparison algorithm.

[0011] The detection method described above, wherein the step of acquiring the first image information and corresponding model information of the screen under test includes:

[0012] Acquire the first image information of the screen under test;

[0013] The length and width information of the screen under test are determined based on the first image information of the screen under test and the feature information of the operating platform.

[0014] Based on the length and width information of the screen to be tested and the preset screen length and width information, determine the corresponding model information.

[0015] The detection method described above, wherein the step of determining multiple detection points of the screen to be tested based on the corresponding model information includes:

[0016] Based on the corresponding model information, determine the radius and curvature of the bezel arc of the screen to be tested, the position and size of the top slot, and the top slot shall include at least an arc slot, a square slot or a circular hole.

[0017] Based on the radius and curvature of the arc of the screen frame to be tested, determine the first point where the arc of the frame connects to the straight edge;

[0018] The top slot is divided according to its position and size;

[0019] Based on the first point, the border arc, and the segmented top slot, multiple detection points of the screen under test are determined.

[0020] The detection method described above, wherein the step of generating second image information of the screen under test based on multiple detection points and first image information includes:

[0021] A detection curve is generated based on multiple detection sites on the screen under test;

[0022] The camera is controlled to perform a high-precision scan along the detection curve to generate third image information;

[0023] Multiple third image information pieces are stitched together one by one according to the detection curve to generate second image information, wherein the third image information includes rough edges or defects.

[0024] The detection method described above, wherein the step of determining the processing plan for the screen to be tested by comparing the second image information and the preset screen image based on the comparison algorithm includes:

[0025] The location coordinates of the burrs or defects on the screen under test are determined by comparing the second image information with the preset screen image using a comparison algorithm.

[0026] If there are residual burrs on the screen to be tested, control the robotic arm to drive the non-woven fabric for cleaning.

[0027] If the screen under test has defects, the sorter on the control panel will sort it.

[0028] A device for detecting the cut surface of a screen, comprising:

[0029] The first acquisition module is used to acquire the first image information and the corresponding model information of the screen under test.

[0030] The first determining module is used to determine multiple detection sites of the screen to be tested based on the corresponding model information;

[0031] The first generation module is used to generate second image information of the screen under test based on multiple detection sites and first image information of the screen under test.

[0032] The second determining module is used to determine the processing plan for the screen to be tested by comparing the second image information and the preset screen image based on the comparison algorithm.

[0033] The detection device described above, wherein the first acquisition module includes:

[0034] The first acquisition unit is used to acquire the first image information of the screen to be tested.

[0035] The first determining unit is used to determine the length and width information of the screen under test based on the first image information of the screen under test and the feature information of the operating platform.

[0036] The second determining unit is used to determine the corresponding model information based on the length and width information of the screen to be tested and the preset length and width information of the screen;

[0037] The first determining module includes:

[0038] The third determining unit is used to determine the radius and curvature of the border arc of the screen to be tested, the position and size of the top slot hole, and the top slot hole according to the corresponding model information. The top slot hole includes at least an arc slot, a square slot or a circular hole.

[0039] The fourth determining unit is used to determine the first point where the arc of the border connects to the straight edge based on the radius and curvature of the arc of the border of the screen to be tested.

[0040] A segmentation unit is used to segment the top slot according to the position and size of the top slot.

[0041] The fifth determining unit is used to determine multiple detection points of the screen under test based on the first point, the border arc, and the segmented top slot.

[0042] The first generation module includes:

[0043] The first generation unit is used to generate a detection curve based on multiple detection sites on the screen to be tested;

[0044] The second generation unit is used to control the camera to perform high-precision scanning along the detection curve and generate third image information.

[0045] The third generation unit is used to stitch together multiple third image informations one by one according to the detection curve to generate second image information, wherein the third image information includes burrs or defects.

[0046] The second determining module includes:

[0047] The sixth determining unit is used to determine the location coordinates of the burrs or defects of the screen under test by comparing the second image information and the preset screen image based on the comparison algorithm.

[0048] The first processing unit is used to control the robotic arm to clean the non-woven fabric if there are residual burrs on the screen to be tested.

[0049] The second processing unit is used to control the sorter on the operating table to sort the screen if there is a defect.

[0050] A computer-readable storage medium storing a computer program that, when executed by a screen cut surface detection device, implements the screen cut surface detection method as described above.

[0051] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the screen cut surface detection method as described above.

[0052] This invention acquires first image information and corresponding model information of the screen under test to determine multiple detection points of the screen under test. Then, based on the multiple detection points and the first image information, a second image information of the screen under test is generated. Finally, the second image information is compared with a preset screen image to determine the processing plan for the screen under test. This enables multiple-point positioning detection for different models, addressing different edge conditions or defects, resulting in better screen quality and a better user experience. [Attached Image Description]

[0053] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 This is a flowchart of the screen cutting surface detection method according to the first embodiment of the present invention;

[0055] Figure 2 yes Figure 1 Detailed flowchart of step S11;

[0056] Figure 3 yes Figure 1 Detailed flowchart of step S12;

[0057] Figure 4 yes Figure 1 Detailed flowchart of step S13;

[0058] Figure 5 yes Figure 1 Detailed flowchart of step S14;

[0059] Figure 6 This is a structural block diagram of the screen cutting surface detection device according to the second embodiment of the present invention;

[0060] Figure 7 yes Figure 4 A detailed structural block diagram of the first acquisition module;

[0061] Figure 8 yes Figure 4 Detailed structural block diagram of the first determined module;

[0062] Figure 9 yes Figure 4 Detailed structural block diagram of the first generation module;

[0063] Figure 10 yes Figure 4 Detailed structural block diagram of the second determination module;

[0064] Figure 11 This is a structural block diagram of a computer device according to another embodiment of the present invention.

Detailed Implementation Methods

[0065] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Well-known modules, units, and their connections, links, communications, or operations are not shown or described in detail. Furthermore, the described features, architectures, or functions can be combined in any way in one or more embodiments. Those skilled in the art should understand that the various embodiments described below are only for illustrative purposes and not for limiting the scope of protection of the present invention. It is also readily understood that the modules, units, or processing methods in the various embodiments described herein and shown in the accompanying drawings can be combined and designed in various different configurations. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0066] The definitions of various terms or methods used in the following embodiments are, except where logically impossible, generally defined as broad concepts that can be implemented under the premise of the content disclosed in the embodiments. Under this understanding, all specific subordinate limitations of the terms or methods should be considered as part of the invention, and should not be narrowly interpreted or biased simply because the specification does not disclose such a specific limitation. For example, when the present invention refers to a cloud platform, it includes not only virtual network servers but also real physical devices, which not only have data storage capabilities but also data processing, intelligent analysis, and reasoning capabilities. Similarly, provided logically feasible, the order of steps in the method is flexible and varied, and all specific subordinate limitations within the broad concepts of various terms or methods fall within the scope of protection of this invention.

[0067] First embodiment:

[0068] Please refer to Figures 1 to 5 As shown, this embodiment proposes a method for detecting screen cut surfaces, including S11-S14, wherein:

[0069] S11. Obtain the first image information and corresponding model information of the screen to be tested.

[0070] This embodiment acquires images using a CCD camera. The acquired image information includes images of the screen and the operating table. By determining the image information, the screen model information is identified, thereby determining the screen size and the position of the top recess. Different screens have different top openings, requiring corresponding confirmation to ensure better cleaning and avoid misjudgment or failure to identify problems, thus achieving better detection and cleaning results.

[0071] As a preferred option rather than a specific limitation, step S11 includes S111-S113, wherein:

[0072] S111, Obtain the first image information of the screen to be tested.

[0073] In this embodiment, a CCD camera is fixed at a certain height, and the camera is used to take pictures to obtain first image information. The first image information includes an image of the operating table and an image of the screen to be tested. The purpose of obtaining the image of the operating table is to facilitate the measurement of the length and width information of the screen, so as to make the process of obtaining the screen model more accurate and reliable.

[0074] S112. Determine the length and width information of the screen under test based on the first image information of the screen under test and the feature information of the operating platform.

[0075] This embodiment uses first image information and feature information of the operating platform, the feature information of the operating platform including at least length and width information and feature patterns, and then matches the feature information of the operating platform with the first image information to calculate the length and width information of the screen to be tested according to the ratio, so as to make the calculation results more accurate and reliable and the effect better.

[0076] S113. Determine the corresponding model information based on the length and width information of the screen to be tested and the preset screen length and width information.

[0077] In this embodiment, after determining the length and width information of the screen to be tested, it is matched with the preset screen length and width information stored in the cloud platform to determine the corresponding model size. When producing multiple models with the same length and width but different top slots, multiple corresponding model information will be obtained based on the length and width information. Then, the shape and size of the top slot will be extracted from the first image information for matching to more accurately determine the model. The determination process is accurate and reliable, and the effect is better.

[0078] S12. Based on the corresponding model information, determine multiple detection points for the screen to be tested.

[0079] In this embodiment, the length and width of the screen to be tested and the corresponding position of the slot are determined by the corresponding model information. After the determination, the edge of the screen needs to be detected. At this time, multiple detection points need to be determined first. The detection of straight edges is more direct, while the four corners and the top slot positions are the key detection points. During the test, the detection effect is better by detecting multiple determined points.

[0080] As a preferred option rather than a specific limitation, step S12 includes S121-S124, wherein:

[0081] S121. Based on the corresponding model information, determine the radius and curvature of the bezel arc of the screen to be tested, the position and size of the top slot, wherein the top slot includes at least an arc slot, a square slot or a circular hole.

[0082] This embodiment uses the corresponding model information to determine the radius and curvature of the arc at the four corners of the frame, so as to determine the corresponding detection points. In addition, it is also necessary to detect the slots. Different screens have different shapes and positions of the slots. There are arc-shaped grooves located in the middle of the top, square grooves located in the middle of the top, or circular holes located in the middle of the top or at the corners, square grooves located in the middle of the top, or elliptical holes located in the middle of the top or at the corners. By determining the radius and curvature of the arc of the frame, the position and size of the top slots, it is possible to better determine the points to be detected and to perform more accurate detection.

[0083] S122. Determine the first point where the arc of the screen border connects to the straight edge based on the radius and curvature of the arc.

[0084] This embodiment determines the connection points between the arc and the straight edge of the screen frame by measuring the arc radius and curvature of the arc. There are eight such connection points, which are determined by the connection points between the four arcs and the four straight edges at the corners. By determining these connection points, some detection points are determined, and then these points are further divided into multiple second points to make the detection process more accurate and reliable.

[0085] S123. Divide the top slot according to its position and size.

[0086] In this embodiment, the position and size of the top slot are determined. To achieve more precise control, the top slot is divided to make the detection process more accurate and reliable. The points set after division are determined according to a preset interval to make the detection results more accurate and reliable.

[0087] S124. Based on the first point, the border arc, and the segmented top slot, determine multiple detection points of the screen to be tested.

[0088] In this embodiment, based on the first point, the border arc, the segmented top slot, and the segmented straight edge, a specific number of points are assigned to each arc at a preset interval, such as 10 points per arc, and the straight edge is configured accordingly. This determines multiple detection points, and by utilizing the shortcomings of the detection points, the detection position information can be better determined.

[0089] S13. Generate the second image information of the screen under test based on the multiple detection sites and the first image information of the screen under test.

[0090] This embodiment generates a detection curve and a path of detection position by multiple detection points on the screen under test. Then, it controls the camera to scan and take pictures along the curve path to obtain a new image. The new image is magnified image information with high accuracy, which can better determine the scan information.

[0091] As a preferred option rather than a specific limitation, step S13 includes S131-S133, wherein:

[0092] S131. Generate a detection curve based on multiple detection sites on the screen to be tested.

[0093] In this embodiment, multiple detection points are connected. To ensure the accuracy of the connection, the number of detection points cannot be too small. The connection is made by connecting the points. For arcs, information such as curvature needs to be combined to make the connection to ensure that the connection is accurate and reliable.

[0094] S132. Control the camera to perform high-precision scanning along the detection curve to generate third image information.

[0095] In this embodiment, after the detection curve is connected, the system automatically generates a path along the detection curve. At this time, it is necessary to control the camera to perform high-precision scanning along the detection curve to obtain clear third image information, which consists of multiple screen edge information.

[0096] S133. Based on the detection curve, multiple third image information are stitched together one by one to generate second image information, wherein the third image information includes burrs or defects.

[0097] In this embodiment, after performing a high-precision scan along the detection curve, the third image information captured along the curve is stitched together one by one according to the order of shooting to obtain the second image information containing burrs or defects, and the detection results are more accurate and reliable.

[0098] S14. Based on the comparison algorithm, compare the second image information with the preset screen image to determine the processing plan for the screen to be tested.

[0099] This embodiment uses a comparison algorithm to compare the second image information and the preset screen image. By determining the difference between the pixel position of the second image information and the preset screen image, if the pixel position is outside the range of the preset screen image, it is determined to be a burr. If the pixel position is missing within the range of the preset screen image, it is determined to be a defect. Then, based on the difference between the burr or the defect, it is determined whether the screen needs to be cleaned to remove the burr or filtered out, resulting in a better processing effect.

[0100] As a preferred option rather than a specific limitation, step S14 includes S141-S143, wherein:

[0101] S141. Based on the comparison algorithm, compare the second image information and the preset screen image to determine the location coordinates of the burrs or defects of the screen to be tested.

[0102] This embodiment compares the second image information with the preset screen image using a comparison algorithm. The comparison algorithm is performed by comparing pixels. By determining the difference between the pixel positions of the second image information and the preset screen image, if the pixel position exceeds the range of the preset screen image, it is determined to be a rough edge. If the pixel position is missing within the range of the preset screen image, it is determined to be a defect. This method can quickly and efficiently list the error information, resulting in better performance.

[0103] S142. If there are residual burrs on the screen to be tested, control the robotic arm to drive the non-woven fabric for cleaning.

[0104] In this embodiment, when burrs are detected on the screen (i.e., screen debris or other dust adhering to the screen edges), a robotic arm carrying a non-woven fabric is controlled to move. To prevent the non-woven fabric from damaging the screen while cleaning residual burrs, it needs to be controlled to move from the inside of the screen outwards along a predetermined trajectory to wipe away the burrs. This ensures better cleaning results without damaging the screen. Alternatively, as an alternative, burrs can also be cleaned using a plasma cleaner, which removes burrs by burning them off with a flame. However, with plasma cleaning, the distance between the screen and the flame, as well as the burning time, need to be controlled. The distance and time need to be adjusted according to the actual situation to achieve better cleaning results.

[0105] S143. If the screen to be tested has defects, control the sorter on the control panel to sort it.

[0106] In this embodiment, a robotic arm can be installed on the operating table to sort the screens. When a defect is detected in the screen, such as missing screen edges causing missing pixels or light leakage, the equipment automatically identifies it and sorts it into the waste area via a sorter. If there is no sorter, the machine will issue an audible and visual alarm to remind the operator to manually sort out the defective screens. In this way, defective screens to be tested can be separated in a timely manner to avoid secondary screening in the later stage and improve work efficiency.

[0107] This embodiment obtains the first image information and corresponding model information of the screen under test to determine multiple detection points of the screen under test. Then, the second image information of the screen under test is generated from the multiple detection points and the first image information. Finally, the second image information is compared with the preset screen image to determine the treatment plan for the screen under test. This enables multiple-point positioning detection for different models to deal with different burr conditions or defects, resulting in better screen quality and a better user experience.

[0108] Second embodiment:

[0109] Please refer to Figures 6 to 10 As shown, this embodiment proposes a screen cutting surface detection device 100, including a first acquisition module 110, a first determination module 120, a first generation module 130, and a second determination module 140, wherein:

[0110] The first acquisition module 110 is connected to the first determination module 120 and is used to acquire the first image information and the corresponding model information of the screen to be tested.

[0111] As a preferred embodiment rather than a specific limitation, the first acquisition module 110 includes a first acquisition unit 111, a first determination unit 112, and a second determination unit 113, wherein:

[0112] The first acquisition unit 111 is connected to the first determination unit 112 and is used to acquire the first image information of the screen to be tested.

[0113] The first determining unit 112 is connected to the second determining unit 113 and is used to determine the length and width information of the screen under test based on the first image information of the screen under test and the feature information of the operating platform.

[0114] The second determining unit 113 is used to determine the corresponding model information based on the length and width information of the screen to be tested and the preset length and width information of the screen.

[0115] The first determining module 120 is connected to the first generating module 130 and is used to determine multiple detection sites of the screen to be tested based on the corresponding model information.

[0116] As a preferred embodiment rather than a specific limitation, the first determining module 120 includes a third determining unit 121, a fourth determining unit 122, a segmentation unit 123, and a fifth determining unit 124, wherein:

[0117] The third determining unit 121, connected to the fourth determining unit 122, is used to determine the radius and curvature of the border arc of the screen to be tested, the position and size of the top slot hole, based on the corresponding model information. The top slot hole includes at least an arc slot, a square slot or a circular hole.

[0118] The fourth determining unit 122, connected to the segmentation unit 123, is used to determine the first point where the arc of the border connects to the straight edge based on the arc radius and curvature of the border of the screen to be tested.

[0119] The segmentation unit 123 is connected to the fifth determining unit 124 and is used to segment the top slot according to the position and size of the top slot.

[0120] The fifth determining unit 124 is used to determine multiple detection points of the screen under test based on the first point, the border arc and the segmented top slot.

[0121] The first generation module 130 is connected to the second determination module 140 and is used to generate second image information of the screen under test based on multiple detection sites and first image information of the screen under test.

[0122] As a preferred embodiment rather than a specific limitation, the first generation module 130 includes a first generation unit 131, a second generation unit 132, and a third generation unit 133, wherein:

[0123] The first generation unit 131 is connected to the second generation unit 132 and is used to generate a detection curve based on multiple detection sites on the screen to be tested.

[0124] The second generation unit 132 is connected to the third generation unit 133 and is used to control the camera to perform high-precision scanning along the detection curve to generate third image information.

[0125] The third generation unit 133 is used to stitch together multiple third image informations one by one according to the detection curve to generate second image information, wherein the third image information includes rough edges or defects.

[0126] The second determining module 140 is used to determine the processing plan for the screen to be tested by comparing the second image information and the preset screen image based on the comparison algorithm.

[0127] As a preferred embodiment rather than a specific limitation, the second determining module 140 includes a sixth determining unit 141, a first processing unit 142, and a second processing unit 143, wherein:

[0128] The sixth determining unit 141 is connected to the first processing unit 142 and is used to determine the position coordinates of the burrs or defects of the screen under test by comparing the second image information and the preset screen image based on the comparison algorithm.

[0129] The first processing unit 142 is connected to the second processing unit 143 and is used to control the robotic arm to perform a non-woven fabric cleaning operation if there are residual burrs on the screen to be tested.

[0130] The second processing unit 143 is used to control the sorter on the operating table to sort the screen under test if there is a defect.

[0131] This embodiment obtains the first image information and corresponding model information of the screen under test to determine multiple detection points of the screen under test. Then, the second image information of the screen under test is generated from the multiple detection points and the first image information. Finally, the second image information is compared with the preset screen image to determine the treatment plan for the screen under test. This enables multiple-point positioning detection for different models to deal with different burr conditions or defects, resulting in better screen quality and a better user experience.

[0132] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0133] This invention also provides a computer storage medium storing a computer program that, when executed by a processor, implements a screen cutting surface detection method as described in the above embodiments.

[0134] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the screen cutting surface detection methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0135] Alternatively, if the integrated units of the present invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present invention, or the parts that contribute to related technologies, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, terminal, or network device, etc.) to execute all or part of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, RAM, ROM, magnetic disks, or optical disks. Corresponding to the aforementioned computer storage medium, one embodiment also provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements a screen cutting surface detection method as described in the above embodiments.

[0136] This computer device can be a terminal, and its internal structure diagram can be as follows: Figure 11As shown, the computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used to communicate with external terminals via a network connection. When executed by the processor, the computer program implements a method for detecting screen cut surfaces. The display screen can be a liquid crystal display (LCD) or an e-ink display. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0137] This embodiment obtains the first image information and corresponding model information of the screen under test to determine multiple detection points of the screen under test. Then, the second image information of the screen under test is generated from the multiple detection points and the first image information. Finally, the second image information is compared with the preset screen image to determine the treatment plan for the screen under test. This enables multiple-point positioning detection for different models to deal with different burr conditions or defects, resulting in better screen quality and a better user experience.

[0138] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0139] The above embodiments merely illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A method for detecting the cut surface of a screen, characterized in that, include: Acquire the first image information of the screen under test; The length and width information of the screen under test are determined based on the first image information of the screen under test and the feature information of the operating platform. Based on the length and width information of the screen to be tested and the preset screen length and width information, determine the corresponding model information; Based on the corresponding model information, determine multiple detection points for the screen to be tested; Based on multiple detection sites of the screen under test and the first image information, the second image information of the screen under test is generated. Based on the comparison algorithm, the second image information and the preset screen image are compared to determine the processing plan for the screen to be tested. The step of determining multiple detection points of the screen to be tested based on the corresponding model information includes: Based on the corresponding model information, determine the radius and curvature of the bezel arc of the screen to be tested, the position and size of the top slot, and the top slot shall include at least an arc slot, a square slot or a circular hole. Based on the radius and curvature of the arc of the screen frame to be tested, determine the first point where the arc of the frame connects to the straight edge; The top slot is divided according to its position and size; Based on the first point, the border arc, and the segmented top slot, multiple detection points of the screen under test are determined; The step of generating second image information of the screen under test based on multiple detection points and first image information includes: A detection curve is generated based on multiple detection sites on the screen under test; The camera is controlled to perform a high-precision scan along the detection curve to generate third image information; Multiple third image information pieces are stitched together one by one according to the detection curve to generate second image information, wherein the third image information includes rough edges or screen defects.

2. The detection method according to claim 1, characterized in that, The step of determining the processing plan for the screen to be tested by comparing the second image information and the preset screen image based on the comparison algorithm includes: The location coordinates of the rough edges or missing parts of the screen under test are determined by comparing the second image information and the preset screen image using a comparison algorithm. If there are residual burrs on the screen to be tested, control the robotic arm to drive the non-woven fabric for cleaning. If the screen under test has missing parts, the sorter on the control panel will sort it.

3. A device for detecting the cut surface of a screen, characterized in that, include: The first acquisition module is used to acquire the first image information and the corresponding model information of the screen under test. The first determining module is used to determine multiple detection sites of the screen to be tested based on the corresponding model information; The first generation module is used to generate second image information of the screen under test based on multiple detection sites and first image information of the screen under test. The second determining module is used to determine the processing plan for the screen to be tested by comparing the second image information and the preset screen image based on the comparison algorithm. The first determining module includes: The third determining unit is used to determine the radius and curvature of the border arc of the screen to be tested, the position and size of the top slot hole, and the top slot hole according to the corresponding model information. The top slot hole includes at least an arc slot, a square slot or a circular hole. The fourth determining unit is used to determine the first point where the arc of the border connects to the straight edge based on the radius and curvature of the arc of the border of the screen to be tested. A segmentation unit is used to segment the top slot according to the position and size of the top slot. The fifth determining unit is used to determine multiple detection points of the screen under test based on the first point, the border arc, and the segmented top slot. The first generation module includes: The first generation unit is used to generate a detection curve based on multiple detection sites on the screen to be tested; The second generation unit is used to control the camera to perform high-precision scanning along the detection curve and generate third image information. The third generation unit is used to stitch together multiple third image informations one by one according to the detection curve to generate second image information, wherein the third image information includes rough edges or screen defects. The first acquisition module includes: a first acquisition unit, used to acquire first image information of the screen to be tested; a first determination unit, used to determine the length and width information of the screen to be tested based on the first image information of the screen to be tested and the feature information of the operating platform; and a second determination unit, used to determine the corresponding model information based on the length and width information of the screen to be tested and preset screen length and width information.

4. The detection device according to claim 3, characterized in that, The second determining module includes: The sixth determining unit is used to determine the location coordinates of the rough edges or missing parts of the screen under test by comparing the second image information and the preset screen image based on the comparison algorithm. The first processing unit is used to control the robotic arm to clean the non-woven fabric if there are residual burrs on the screen to be tested. The second processing unit is used to control the sorter on the operating table to sort the screen if there is a missing screen.

5. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by the screen cutting surface detection device, implements the screen cutting surface detection method as described in any one of claims 1 or 2.

6. A computer device, characterized in that, The computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the screen cut surface detection method as described in any one of claims 1 or 2.

Images