CN115035091B - Equipment screen maintenance feature detection method and device - Google Patents
Equipment screen maintenance feature detection method and deviceInfo
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- CN115035091B CN115035091B CN202210761336.4A CN202210761336A CN115035091B CN 115035091 B CN115035091 B CN 115035091B CN 202210761336 A CN202210761336 A CN 202210761336A CN 115035091 B CN115035091 B CN 115035091B
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
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- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30121—CRT, LCD or plasma display
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
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Abstract
本发明涉及一种设备屏幕维修特征检测方法及装置，在获取到待测智能设备的闪光灯图像后，提取闪光灯图像的曝光点区域，并根据曝光点区域的梯度方向分布和梯度方向，判断待测智能设备的设备屏幕是否存在维修特征。基于此，通过闪光灯图像的环境设定，降低闪光灯图像的照明环境干扰。同时，通过针对闪光灯图像的图像优化方式，便于准确快速地确定待测智能设备的屏幕区域是否存在维修特征。
The present invention relates to a method and apparatus for detecting device screen repair features. After acquiring a flash image of a smart device under test, the method extracts the exposure point region of the flash image and, based on the gradient distribution and direction of the exposure point region, determines whether the device screen under test has repair features. Based on this, the flash image's ambient lighting environment is set to reduce interference. Furthermore, image optimization methods for the flash image facilitate accurate and rapid determination of the presence of repair features in the screen area of the smart device under test.
Description
Technical Field
The invention relates to the technical field of electronic products, in particular to a method and a device for detecting equipment screen maintenance characteristics.
Background
With the development of electronic product technology, various intelligent devices are layered endlessly, such as smart phones, notebook computers, tablet computers and the like. At present, along with the high-speed development of economy and technology, the popularization and updating speed of intelligent equipment are also faster and faster. Taking a smart phone as an example, the advent of the 5G era has accelerated the generation of smart phones. In the process of iteration of the intelligent equipment, effective recovery is one of effective utilization means of the residual value of the intelligent equipment, so that chemical pollution to the environment and waste can be reduced.
In the recovery process of the mobile phone, the overall loss degree of the equipment screen has a great influence on the recovery valuation of the intelligent equipment. Where equipment screen wear is severe, maintenance of the equipment screen is often required. However, the repaired device screen has a large impact on the recycling valuation of the smart device, and thus it is necessary to detect whether the device screen of the smart device has a repair feature during recycling to determine the repair status. However, the conventional method is to collect the image of the screen of the device by using the recycling device, but the illumination state of the collecting process can bring a lot of interference to the image, which affects the accuracy of maintenance feature detection.
In summary, it can be seen that the conventional detection method for the screen maintenance feature of the device has the above disadvantages.
Disclosure of Invention
Based on this, it is necessary to provide a method and a device for detecting the maintenance characteristics of the equipment screen aiming at the defects existing in the conventional detection method of the maintenance characteristics of the equipment screen.
A method for detecting equipment screen maintenance features comprises the following steps:
Acquiring a flash lamp image of the intelligent device to be detected, wherein the flash lamp image is a shooting image of the intelligent device to be detected when the intelligent device to be detected is irradiated by a flash lamp;
extracting an exposure point area of the flash lamp image, wherein the exposure point area comprises exposure points of the intelligent device to be detected irradiated by the flash lamp;
And judging whether the equipment screen of the intelligent equipment to be tested has maintenance characteristics or not according to the gradient direction distribution and the gradient direction of the exposure point area.
According to the equipment screen maintenance feature detection method, after the flash lamp image of the intelligent equipment to be detected is obtained, the exposure point area of the flash lamp image is extracted, and whether maintenance features exist on the equipment screen of the intelligent equipment to be detected is judged according to the gradient direction distribution and the gradient direction of the exposure point area. Based on this, by setting the environment of the flash image, the illumination environment disturbance of the flash image is reduced. Meanwhile, by means of image optimization aiming at the flash lamp image, whether maintenance features exist in a screen area of the intelligent device to be detected or not can be accurately and rapidly determined.
In one embodiment, the process of extracting the exposure point area of the flash image includes the steps of:
Carrying out gray level conversion on the flash lamp image to generate a corresponding gray level image;
carrying out binarization processing on the gray level image to obtain a binarized image;
Extracting the edge of the binarized image through an edge detection algorithm;
And screening out the exposure point area of the edge by a circle detection algorithm.
In one embodiment, before the process of binarizing the gray-scale image to obtain the binarized image, the method further comprises the steps of:
white noise interference of the gray scale image is removed.
In one embodiment, the process of judging whether the device screen of the intelligent device to be tested has maintenance features according to the gradient direction distribution and the gradient direction of the exposure point area includes the steps of:
calculating the gradient of the exposure point area;
Calculating the gradient direction and the gradient amplitude of each pixel point in the exposure point area by utilizing the gradient;
calculating gradient direction distribution of the exposure point area according to the gradient direction and the amplitude;
and sequencing the gradient direction distribution in an inverted order according to the gradient direction, and judging whether the equipment screen of the intelligent equipment to be tested has maintenance characteristics according to the angle of the gradient direction after sequencing in the inverted order.
In one embodiment, the process of sorting gradient direction distribution in a reverse order according to gradient direction, and judging whether a device screen of the intelligent device to be tested has maintenance features according to an angle of the gradient direction after sorting in the reverse order includes the steps of:
And judging whether the equipment screen of the intelligent equipment to be tested has maintenance characteristics or not according to the first n angles distributed in the front gradient direction after the reverse sequence sequencing, wherein n is a positive integer.
In one embodiment, n is 3.
In one embodiment, the process of judging whether the device screen of the intelligent device to be tested has maintenance features according to the first n angles distributed in the front gradient direction after the reverse sequence ordering includes the steps of:
And when the first n angles are target angles, judging that the equipment screen of the intelligent equipment to be tested has maintenance features, otherwise, judging that the intelligent equipment to be tested does not have maintenance features.
An equipment screen repair feature detection apparatus comprising:
The system comprises an image acquisition module, a display module and a display module, wherein the image acquisition module is used for acquiring a flash lamp image of the intelligent equipment to be detected, wherein the flash lamp image is a shooting image when the intelligent equipment to be detected is irradiated by a flash lamp;
The area extraction module is used for extracting an exposure point area of the flash lamp image, wherein the exposure point area comprises exposure points of the intelligent equipment to be detected, which are irradiated by the flash lamp;
And the feature detection module is used for judging whether the equipment screen of the intelligent equipment to be detected has maintenance features according to the gradient direction distribution and the gradient direction of the exposure point area.
According to the device for detecting the maintenance characteristics of the equipment screen, after the flash lamp image of the intelligent equipment to be detected is obtained, the exposure point area of the flash lamp image is extracted, and whether the maintenance characteristics exist on the equipment screen of the intelligent equipment to be detected is judged according to the gradient direction distribution and the gradient direction of the exposure point area. Based on this, by setting the environment of the flash image, the illumination environment disturbance of the flash image is reduced. Meanwhile, by means of image optimization aiming at the flash lamp image, whether maintenance features exist in a screen area of the intelligent device to be detected or not can be accurately and rapidly determined.
A computer storage medium having stored thereon computer instructions which, when executed by a processor, implement the apparatus screen repair feature detection method of any of the above embodiments.
According to the computer storage medium, after the flash lamp image of the intelligent device to be detected is obtained, the exposure point area of the flash lamp image is extracted, and whether the maintenance feature exists on the device screen of the intelligent device to be detected is judged according to the gradient direction distribution and the gradient direction of the exposure point area. Based on this, by setting the environment of the flash image, the illumination environment disturbance of the flash image is reduced. Meanwhile, by means of image optimization aiming at the flash lamp image, whether maintenance features exist in a screen area of the intelligent device to be detected or not can be accurately and rapidly determined.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the device screen repair feature detection method of any of the above embodiments when the program is executed by the processor.
According to the computer equipment, after the flash lamp image of the intelligent equipment to be detected is obtained, the exposure point area of the flash lamp image is extracted, and whether the maintenance feature exists on the equipment screen of the intelligent equipment to be detected is judged according to the gradient direction distribution and the gradient direction of the exposure point area. Based on this, by setting the environment of the flash image, the illumination environment disturbance of the flash image is reduced. Meanwhile, by means of image optimization aiming at the flash lamp image, whether maintenance features exist in a screen area of the intelligent device to be detected or not can be accurately and rapidly determined.
Drawings
FIG. 1 is a flow chart of a method for detecting equipment screen maintenance features according to an embodiment;
FIG. 2 is a flow chart of another embodiment of a method for device screen maintenance feature detection;
FIG. 3 is a flowchart of a method for device screen maintenance feature detection according to yet another embodiment;
FIG. 4 is a block diagram of an apparatus screen maintenance feature detection device according to an embodiment;
fig. 5 is a schematic diagram of an internal structure of a computer according to an embodiment.
Detailed Description
For a better understanding of the objects, technical solutions and technical effects of the present invention, the present invention will be further explained below with reference to the drawings and examples. Meanwhile, it is stated that the embodiments described below are only for explaining the present invention and are not intended to limit the present invention.
Fig. 1 is a structural diagram of an acquisition device, as shown in fig. 1, wherein the acquisition device comprises a left light source 1, a right light source 11, a left acrylic light transmitting sheet 2, a right acrylic light transmitting sheet 10, a power line socket 3, a power switch 4, a touch screen 5, a flash lamp 6, a one-to-three data line 7, a camera 8, a front metal light guide strip 9 and a rear metal light guide strip 13, which are used for enhancing the brightness of the front side and the rear side, and an intelligent device placing plate 12 to be tested is generally green.
As shown in fig. 1, the smart device under test is placed in the placement board 12, and image capturing is performed by the camera 8 to capture the smart device under test. Unlike the long-time stable illumination photographed in the conventional recycling process, the flash 6 provides instantaneous strong flash illumination at the camera 8, and the flash image is collected in cooperation with the camera 8.
Based on this, fig. 2 is a flowchart of an apparatus screen maintenance feature detection method according to an embodiment, as shown in fig. 2, the apparatus screen maintenance feature detection method according to an embodiment includes steps S100 to S102:
s100, acquiring a flash lamp image of the intelligent device to be detected, wherein the flash lamp image is a shooting image of the intelligent device to be detected when the intelligent device to be detected is irradiated by a flash lamp;
s101, extracting an exposure point area of a flash lamp image, wherein the exposure point area comprises exposure points of the intelligent device to be tested, which are irradiated by the flash lamp;
s102, judging whether a device screen of the intelligent device to be tested has maintenance features or not according to gradient direction distribution and gradient direction of the exposure point area.
The execution subject of step S100 acquires a flash image, and performs the next image processing.
In step S101, the exposure point area of the flash lamp image is extracted, the irrelevant image information is removed, the subsequent image processing calculation amount is reduced, and the accuracy of detecting the maintenance feature is improved. And if the equipment screen has the maintenance feature, the equipment screen representing the corresponding intelligent equipment to be detected is maintained.
In one embodiment, the exposure point area of the flash image may be extracted by a pre-established image cropping approach.
In one example, fig. 3 is a flowchart of an apparatus screen maintenance feature detection method according to another embodiment, as shown in fig. 3, a process of extracting an exposure point area of a flash image in step S101 includes steps S200 to S204:
s200, performing gray level conversion on the flash lamp image to generate a corresponding gray level image;
s201, removing white noise interference of a gray level image;
s202, binarizing the gray level image to obtain a binarized image;
s203, extracting the edge of the binarized image through an edge detection algorithm;
s204, screening out the exposure point area of the edge through a circle detection algorithm.
Step S201 is an optional step.
The flash lamp image I is subjected to gray level conversion to generate a corresponding gray level image G1, and the following formula is shown:
G1(j,i)=0.1140*Ib(j,i)+0.5870*Ig(j,i)+0.2989*Ir(j,i)
The white noise interference of the gray image G1 is removed, and the white noise interference can be performed by a gaussian blur process, as follows:
Wherein G2 represents the gray-scale image G1 after the gaussian blur processing.
Where j=1, 2..h, i=1, 2..w, j and i denote coordinate values in the horizontal direction and the vertical direction with respect to the origin of the upper left corner in the gradation image G1, respectively, H and W denote the height and the width of X, W denote the length of the rectangular window, set to 3, a denote the amplitude of the corresponding rectangular window, set to 16. The rectangular window represents the template corresponding to the gaussian filter:
in one embodiment, the edge detection algorithm may be a Canny edge detection operator. Binarizing the gray level image (G1 or G2) to obtain a binarized image B, and extracting an edge E of the binarized image B by a Canny edge detection operator, wherein the formula is as follows:
as a preferred implementation mode, the threshold value of the Canny edge detection operator is respectively set to be 30 and 60 so as to improve the detection accuracy of intelligent devices to be detected, such as intelligent mobile phones.
In one embodiment, the circle detection algorithm may be a hough circle detection method. And screening out an exposure point region X in the edge E by a Hough circle detection method.
In one embodiment, as shown in fig. 3, in step S102, a process of determining whether a device screen of the intelligent device to be tested has a maintenance feature according to gradient direction distribution and gradient direction of an exposure point region includes steps S300 to S303:
S300, calculating gradients of the exposure point areas;
s301, calculating gradient directions and amplitudes of all pixel points in an exposure point area by using gradients;
s302, calculating gradient direction distribution of an exposure point area according to the gradient direction and the amplitude;
S303, carrying out reverse order sorting on the gradient direction distribution according to the gradient direction, and judging whether a device screen of the intelligent device to be tested has maintenance features according to the angle of the gradient direction after the reverse order sorting.
Wherein, the gradient G of the exposure spot area is calculated as follows:
G=|Gx|+|Gy|
calculating the gradient direction theta and the amplitude M of each pixel point in the exposure point area X by using the gradient G, wherein the gradient direction theta and the amplitude M are as follows:
using the gradient direction θ and the amplitude M, the gradient direction distribution H of the exposure spot area X is calculated as follows:
H(θ)=∑M(j,i),θ∈[0,360]
In one embodiment, the process of sorting gradient direction distribution in a reverse order according to gradient direction, and judging whether a device screen of the intelligent device to be tested has maintenance features according to an angle of the gradient direction after sorting in the reverse order includes the steps of:
And judging whether the equipment screen of the intelligent equipment to be tested has maintenance characteristics or not according to the first n angles distributed in the front gradient direction after the reverse sequence sequencing, wherein n is a positive integer.
In one embodiment, n is 3.
In one embodiment, the process of judging whether the device screen of the intelligent device to be tested has maintenance features according to the first n angles distributed in the front gradient direction after the reverse sequence ordering includes the steps of:
And when the first n angles are target angles, judging that the equipment screen of the intelligent equipment to be tested has maintenance features, otherwise, judging that the intelligent equipment to be tested does not have maintenance features.
In one embodiment, the target angle is 60 ° or 120 °.
According to the equipment screen maintenance feature detection method of any embodiment, after the flash lamp image of the intelligent equipment to be detected is obtained, the exposure point area of the flash lamp image is extracted, and whether maintenance features exist on the equipment screen of the intelligent equipment to be detected is judged according to gradient direction distribution and gradient direction of the exposure point area. Based on this, by setting the environment of the flash image, the illumination environment disturbance of the flash image is reduced. Meanwhile, by means of image optimization aiming at the flash lamp image, whether maintenance features exist in a screen area of the intelligent device to be detected or not can be accurately and rapidly determined.
The embodiment of the invention also provides a device screen maintenance feature detection device.
Fig. 4 is a block diagram of an apparatus screen maintenance feature detection device according to an embodiment, and as shown in fig. 4, the apparatus screen maintenance feature detection device according to an embodiment includes:
The image acquisition module 100 is used for acquiring a flash lamp image of the intelligent device to be detected, wherein the flash lamp image is a shooting image of the intelligent device to be detected when the intelligent device to be detected is irradiated by a flash lamp;
the area extraction module 101 is used for extracting an exposure point area of the flash lamp image, wherein the exposure point area comprises exposure points of the intelligent device to be detected, which are irradiated by the flash lamp;
The feature detection module 102 is configured to determine whether a maintenance feature exists on a device screen of the intelligent device to be detected according to the gradient direction distribution and the gradient direction of the exposure point area.
According to the device for detecting the maintenance characteristics of the equipment screen, after the flash lamp image of the intelligent equipment to be detected is obtained, the exposure point area of the flash lamp image is extracted, and whether the maintenance characteristics exist on the equipment screen of the intelligent equipment to be detected is judged according to the gradient direction distribution and the gradient direction of the exposure point area. Based on this, by setting the environment of the flash image, the illumination environment disturbance of the flash image is reduced. Meanwhile, by means of image optimization aiming at the flash lamp image, whether maintenance features exist in a screen area of the intelligent device to be detected or not can be accurately and rapidly determined.
The embodiment of the invention also provides a computer storage medium, on which computer instructions are stored, which when executed by a processor, implement the method for detecting the equipment screen maintenance characteristics according to any of the above embodiments.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can 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), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SYNCHLINK) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
Or the above-described integrated units of the invention may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solution of the embodiments of the present invention may be essentially or part contributing to the related art, and the computer software product may be stored in a storage medium, and include several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device) to execute all or part of the methods of the embodiments of the present invention. The storage medium includes various media capable of storing program codes such as a removable storage device, a RAM, a ROM, a magnetic disk or an optical disk.
Corresponding to the above computer storage medium, in one embodiment, there is also provided a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the method for detecting a screen maintenance feature of a device according to any one of the above embodiments when the processor executes the program.
The computer device may be a terminal, and its internal structure may be as shown in fig. 5. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by a processor implements a device screen maintenance feature detection method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, the input device of the computer equipment can be a touch layer covered on the display screen, can be keys, a track ball or a touch pad arranged on the shell of the computer equipment, can also be an external keyboard, a touch pad or a mouse, and the like
According to the computer equipment, after the flash lamp image of the intelligent equipment to be detected is obtained, the exposure point area of the flash lamp image is extracted, and whether the maintenance feature exists on the equipment screen of the intelligent equipment to be detected is judged according to the gradient direction distribution and the gradient direction of the exposure point area. Based on this, by setting the environment of the flash image, the illumination environment disturbance of the flash image is reduced. Meanwhile, by means of image optimization aiming at the flash lamp image, whether maintenance features exist in a screen area of the intelligent device to be detected or not can be accurately and rapidly determined.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the invention, which are described in detail and are not to be construed as limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (9)
1. The equipment screen maintenance feature detection method is characterized by comprising the following steps:
acquiring a flash lamp image of the intelligent device to be detected, wherein the flash lamp image is a shooting image when the intelligent device to be detected is irradiated by a flash lamp;
Extracting an exposure point area of the flash lamp image, wherein the exposure point area comprises exposure points of the intelligent equipment to be tested, which are irradiated by the flash lamp;
Judging whether a maintenance feature exists on the equipment screen of the intelligent equipment to be detected according to the gradient direction distribution and the gradient direction of the exposure point area;
The process for judging whether the equipment screen of the intelligent equipment to be detected has maintenance characteristics according to the gradient direction distribution and the gradient direction of the exposure point area comprises the following steps:
Calculating the gradient of the exposure point area;
calculating the gradient direction and the gradient amplitude of each pixel point in the exposure point area by utilizing the gradient;
Calculating gradient direction distribution of the exposure point area according to the gradient direction and the amplitude;
and carrying out reverse order sorting on the gradient direction distribution according to the gradient direction, and judging whether a device screen of the intelligent device to be tested has maintenance characteristics according to the angle of the gradient direction after the reverse order sorting.
2. The apparatus screen maintenance feature detection method according to claim 1, wherein the process of extracting the exposure point area of the flash image includes the steps of:
performing gray level conversion on the flash lamp image to generate a corresponding gray level image;
Performing binarization processing on the gray level image to obtain a binarized image;
extracting the edge of the binarized image through an edge detection algorithm;
and screening out the exposure point area of the edge through a circle detection algorithm.
3. The apparatus screen maintenance feature detection method according to claim 2, further comprising, before the process of binarizing the grayscale image to obtain a binarized image, the steps of:
and removing white noise interference of the gray level image.
4. The method for detecting the maintenance feature of the equipment screen according to claim 1, wherein the process of sorting the gradient direction distribution in an inverted order according to the gradient direction, and judging whether the maintenance feature exists on the equipment screen of the intelligent equipment to be detected according to the angle of the gradient direction after the inverted order comprises the steps of:
And judging whether maintenance features exist on the equipment screen of the intelligent equipment to be tested according to the first n angles distributed in the gradient direction after the reverse sequence sequencing, wherein n is a positive integer.
5. The equipment on-screen maintenance feature detection method of claim 4, wherein n is 3.
6. The method for detecting the maintenance characteristics of the equipment screen according to claim 4, wherein the process of judging whether the maintenance characteristics exist on the equipment screen of the intelligent equipment to be detected according to the first n angles of the gradient direction distribution after the reverse order sorting comprises the steps of:
and when the first n angles are target angles, judging that the equipment screen of the intelligent equipment to be tested has maintenance features, otherwise, judging that the intelligent equipment to be tested does not have maintenance features.
7. An apparatus screen repair feature detection device, comprising:
The system comprises an image acquisition module, a display module and a display module, wherein the image acquisition module is used for acquiring a flash lamp image of the intelligent equipment to be detected, wherein the flash lamp image is a shooting image when the intelligent equipment to be detected is irradiated by a flash lamp;
The area extraction module is used for extracting an exposure point area of the flash lamp image, wherein the exposure point area comprises exposure points of the intelligent equipment to be detected, which are irradiated by the flash lamp;
the feature detection module is used for judging whether maintenance features exist on the equipment screen of the intelligent equipment to be detected according to the gradient direction distribution and the gradient direction of the exposure point area;
Judging whether the equipment screen of the intelligent equipment to be detected has maintenance characteristics or not according to the gradient direction distribution and the gradient direction of the exposure point area, wherein the process comprises the following steps:
Calculating the gradient of the exposure point area;
calculating the gradient direction and the gradient amplitude of each pixel point in the exposure point area by utilizing the gradient;
Calculating gradient direction distribution of the exposure point area according to the gradient direction and the amplitude;
and carrying out reverse order sorting on the gradient direction distribution according to the gradient direction, and judging whether a device screen of the intelligent device to be tested has maintenance characteristics according to the angle of the gradient direction after the reverse order sorting.
8. A computer storage medium having stored thereon computer instructions which when executed by a processor implement the apparatus screen maintenance feature detection method of any of claims 1 to 6.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the device screen maintenance feature detection method of any one of claims 1 to 6 when the program is executed by the processor.
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