Cutting edge detection method, system and computer readable storage medium

Abstract

An embodiment of the present invention provides a blade edge detection method, system, and computer-readable storage medium, wherein the method includes obtaining a blade edge image of a blade to be detected captured by a high-precision camera; treating pixel points in the blade edge image whose grayscale value is higher than a preset grayscale threshold and located in a specific image area as bright spots; determining the difference between the blade edge image of the blade to be detected and a reference blade edge image based on the bright spots; and determining the blade edge detection result corresponding to the blade based on the difference, wherein the blade edge detection result includes at least one of blade edge contamination and blade edge integrity. By capturing the blade edge image with a high-precision camera and processing the blade edge image through visual processing technology, the blade edge is detected by a machine, thereby solving the problem of low blade edge detection accuracy in the industrial field and improving the blade edge detection accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of digital image processing, and in particular to a cutting edge detection method, system and computer-readable storage medium. Background Art

[0002] During the use of the blade, its cutting edge is prone to notches due to wear. The notches on the cutting edge will affect the sharpness of the blade during use. Therefore, we need to check whether there are notches on the cutting edge when using the blade.

[0003] For straight-line cutting tools in the industrial field, a common method for inspecting cutting edge defects is to obtain an image of the cutting edge and make judgments by observing the image. However, this detection method has low detection accuracy and cannot meet the requirements of the industrial field for cutting edges in high-precision operations.

[0004] The above content is only used to assist in understanding the technical solution of the present invention and does not constitute an admission that the above content is prior art. Summary of the Invention

[0005] The main purpose of the present invention is to provide a cutting edge detection method, aiming to solve the problem of low detection accuracy of the cutting edge.

[0006] To achieve the above-mentioned object, the present invention provides a cutting edge detection method, which comprises:

[0007] Obtaining an image of the cutting edge of the blade to be inspected captured by a high-precision camera;

[0008] Pixels in the blade edge image whose grayscale values ​​are higher than a preset grayscale threshold and located in a specific image area are regarded as bright spots;

[0009] determining the difference between the edge image of the blade to be detected and the reference edge image according to the bright spot;

[0010] An edge detection result corresponding to the blade is determined according to the difference, wherein the edge detection result includes at least one of edge contamination and edge integrity.

[0011] Optionally, the step of treating pixel points in the blade edge image whose grayscale values ​​are higher than a preset grayscale threshold and located in a specific image area as bright spots includes:

[0012] Obtaining the grayscale value of each pixel in the blade edge image;

[0013] Determine the pixel points whose grayscale values ​​are greater than a preset grayscale threshold;

[0014] The pixel points are subjected to shape matching according to a preset shape template, and the pixel points of the specific image area are determined by the shape matching to obtain the bright spot.

[0015] Optionally, the step of determining the difference between the edge image of the blade to be detected and a preset reference edge image according to the bright spot includes:

[0016] determining a proportion of the bright spot in each pixel point in the blade edge image;

[0017] The difference between the edge image of the blade to be detected and a preset reference edge image is determined according to the proportion, wherein the proportion is positively correlated with the difference.

[0018] Optionally, the cutting edge information includes cutting edge contamination, and the step of determining the cutting edge detection result corresponding to the cutting edge according to the difference includes:

[0019] determining a first difference degree according to the size of each bright spot in the edge image, wherein the size of the bright spot is positively correlated with the first difference degree;

[0020] The cutting edge contamination degree is determined according to the first difference.

[0021] Optionally, the cutting edge information includes cutting edge integrity, and the step of determining the cutting edge detection result corresponding to the cutting edge according to the difference includes:

[0022] determining a second difference degree according to the number of bright spots in the blade edge image, wherein the number of bright spots is positively correlated with the second difference degree;

[0023] The cutting edge integrity is determined according to the second difference.

[0024] Optionally, the step of determining the difference between the edge image of the blade to be detected and a reference edge image based on the bright spot further includes:

[0025] Determining a location area of ​​the bright spot in the blade edge image;

[0026] Determining a weight value corresponding to the bright spot according to the weight value associated with the position area;

[0027] The difference is determined according to a weight value corresponding to the bright spot, wherein the weight value is positively correlated with the difference.

[0028] Optionally, after the step of determining the edge detection result corresponding to the blade to be detected according to the difference, the method further includes:

[0029] Obtaining the diameter of each bright spot;

[0030] When the diameter of at least one of the bright spots is greater than a preset threshold, it is determined that the cutting edge of the blade to be detected is damaged, and an alarm prompt message is sent to the user.

[0031] In addition, to achieve the above-mentioned purpose, the present invention also provides a blade edge detection system, which includes: a PC, a light source device, a high-precision camera, a display, a memory, a processor, and a blade edge detection program stored on the memory and runnable on the processor. When the blade edge detection program is executed by the processor, the steps of the blade edge detection method described above are implemented.

[0032] Optionally, the PC includes:

[0033] an illumination module, configured to control the light source device to acquire an edge image of the edge to be detected;

[0034] A camera control module, used for controlling the high-precision camera to photograph the cutting edge to be inspected;

[0035] A support module is used to support the cutting edge detection system.

[0036] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, which stores a cutting edge detection program. When the cutting edge detection program is executed by a processor, it implements the various steps of the cutting edge detection method described in the above embodiment.

[0037] An embodiment of the present invention provides a blade edge detection method, system, and computer-readable storage medium, wherein the method includes obtaining a blade edge image of a blade to be detected captured by a high-precision camera; treating pixel points in the blade edge image whose grayscale value is higher than a preset grayscale threshold and located in a specific image area as bright spots; determining the difference between the blade edge image of the blade to be detected and a reference blade edge image based on the bright spots; and determining the blade edge detection result corresponding to the blade based on the difference, wherein the blade edge detection result includes at least one of blade edge contamination and blade edge integrity. By capturing the blade edge image with a high-precision camera and processing the blade edge image through visual processing technology, the blade edge is detected by a machine, thereby solving the problem of low blade edge detection accuracy in the industrial field and improving the blade edge detection accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 Schematic diagram of the hardware architecture of the cutting edge detection device involved in an embodiment of the present invention;

[0039] Figure 2 Schematic diagram of the process of the first embodiment of the cutting edge detection method of the present invention;

[0040] Figure 3 This is a detailed flowchart of step S20 in the second embodiment of the cutting edge detection method of the present invention;

[0041] Figure 4This is a detailed flow chart of step S30 in the third embodiment of the cutting edge detection method of the present invention;

[0042] Figure 5 This is a schematic diagram of a first detailed flow chart of step S40 in the fourth embodiment of the cutting edge detection method of the present invention;

[0043] Figure 6 This is a second detailed flow chart of step S40 in the fifth embodiment of the cutting edge detection method of the present invention;

[0044] Figure 7 This is another detailed flowchart of step S30 in the sixth embodiment of the cutting edge detection method of the present invention;

[0045] Figure 8 2 is a flow chart of the seventh embodiment of the cutting edge detection method of the present invention.

[0046] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0047] It should be understood that the drawings of the present invention show exemplary embodiments of the present invention, and that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0048] As an implementation solution, the cutting edge detection device can be as follows Figure 1 shown.

[0049] The embodiment of the present invention relates to a cutting edge detection device, which includes a processor 101, such as a CPU, a memory 102, and a communication bus 103. The communication bus 103 is used to achieve connection and communication between these components.

[0050] The memory 102 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. Figure 1 As shown, the memory 102 as a computer-readable storage medium may include a cutting edge detection program; and the processor 101 may be used to call the cutting edge detection program stored in the memory 102 and perform the following operations:

[0051] Obtaining an image of the cutting edge of the blade to be inspected captured by a high-precision camera;

[0052] Pixels in the blade edge image whose grayscale values ​​are higher than a preset grayscale threshold and located in a specific image area are regarded as bright spots;

[0053] determining the difference between the edge image of the blade to be detected and the reference edge image according to the bright spot;

[0054] An edge detection result corresponding to the blade is determined according to the difference, wherein the edge detection result includes at least one of edge contamination and edge integrity.

[0055] In one embodiment, the processor 101 may be configured to call a cutting edge detection program stored in the memory 102 and perform the following operations:

[0056] Obtaining the grayscale value of each pixel in the blade edge image;

[0057] Determine the pixel points whose grayscale values ​​are greater than a preset grayscale threshold;

[0058] The pixel points are subjected to shape matching according to a preset shape template, and the pixel points of the specific image area are determined by the shape matching to obtain the bright spot.

[0059] In one embodiment, the processor 101 may be configured to call a cutting edge detection program stored in the memory 102 and perform the following operations:

[0060] determining a proportion of the bright spot in each pixel point in the blade edge image;

[0061] The difference between the edge image of the blade to be detected and a preset reference edge image is determined according to the proportion, wherein the proportion is positively correlated with the difference.

[0062] In one embodiment, the processor 101 may be configured to call a cutting edge detection program stored in the memory 102 and perform the following operations:

[0063] determining a first difference degree according to the size of each bright spot in the edge image, wherein the size of the bright spot is positively correlated with the first difference degree;

[0064] The cutting edge contamination degree is determined according to the first difference.

[0065] In one embodiment, the processor 101 may be configured to call a cutting edge detection program stored in the memory 102 and perform the following operations:

[0066] determining a second difference degree according to the number of bright spots in the blade edge image, wherein the number of bright spots is positively correlated with the second difference degree;

[0067] The cutting edge integrity is determined according to the second difference.

[0068] In one embodiment, the processor 101 may be configured to call a cutting edge detection program stored in the memory 102 and perform the following operations:

[0069] Determining a location area of ​​the bright spot in the blade edge image;

[0070] Determining a weight value corresponding to the bright spot according to the weight value associated with the position area;

[0071] The difference is determined according to a weight value corresponding to the bright spot, wherein the weight value is positively correlated with the difference.

[0072] In one embodiment, the processor 101 may be configured to call a cutting edge detection program stored in the memory 102 and perform the following operations:

[0073] Obtaining the diameter of each bright spot;

[0074] When the diameter of at least one of the bright spots is greater than a preset threshold, it is determined that the cutting edge of the blade to be detected is damaged, and an alarm prompt message is sent to the user.

[0075] Based on the hardware architecture of the cutting edge detection device based on the digital image processing technology, an embodiment of the cutting edge detection method of the present invention is proposed.

[0076] Reference Figure 2 In a first embodiment, the cutting edge detection method includes the following steps:

[0077] Step S10, obtaining an image of the cutting edge of the blade to be inspected captured by a high-precision camera;

[0078] In this embodiment, a high-precision camera is first used to capture an image of the blade edge to be inspected. With the aid of a lighting device provided in this embodiment, the image captured by the high-precision camera can capture images of the blade edge that are difficult for the naked eye to directly observe. The capture angle of the high-precision camera can be downward, perpendicular to the blade edge, or parallel to the blade edge. It should be emphasized that regardless of the capture angle, the goal is to capture a clear and detailed image of the blade edge to be inspected. This embodiment does not limit the capture angle.

[0079] Step S20, taking pixels in the blade edge image whose grayscale values ​​are higher than a preset grayscale threshold and located in a specific image area as bright spots;

[0080] In this embodiment, after the blade edge image is collected, the pixel points in the blade edge image whose grayscale values ​​are higher than the preset grayscale threshold and are located in a specific image area are determined as bright spots in the blade edge image. The bright spots are white light spots that are relatively scattered near the blade line area of ​​the blade edge image. These bright spots may be caused by blade edge contamination or damage to the blade edge. In this step, the bright spots in the blade edge image are determined without judging the cause of the bright spots.

[0081] Step S30, determining the difference between the edge image of the blade to be detected and the reference edge image according to the bright spot;

[0082] In this embodiment, after determining the bright spots in the blade edge image, the blade edge image is compared with a reference blade edge image. The reference blade edge image is at least one complete and clear blade edge image preset in the database. These reference blade edge images are trained on the equipment through the currently more mature machine recognition algorithm, and a quantitative difference is set as a measure to compare and match the blade edge image of the blade to be detected with the reference blade edge image.

[0083] Step S40 , determining a cutting edge detection result corresponding to the cutting edge to be detected according to the difference, wherein the cutting edge detection result includes at least one of cutting edge contamination and cutting edge integrity.

[0084] In this embodiment, after comparing the blade edge image with the reference blade edge image and obtaining the difference between the two, the blade edge detection result corresponding to the blade to be detected is determined based on the difference. The blade edge detection result includes at least one of the contamination degree and integrity of the blade edge. The contamination degree is a quantitative value that measures the degree of contamination of the blade edge, and the integrity is a quantitative value that measures the degree of integrity of the blade edge. Based on the size of the contamination degree and integrity of the blade edge, the device automatically determines whether the blade to be detected is contaminated or whether the blade edge is severely worn.

[0085] In the technical solution provided in this embodiment, the blade image is collected by a high-precision camera, and the blade image is automatically judged by visual processing technology to solve the problem of low blade detection accuracy in the industrial field, improve the edge detection accuracy, and avoid the risk of being scratched by the blade during manual inspection.

[0086] Reference Figure 3 In the second embodiment, based on the first embodiment, step S20 includes:

[0087] Step S21, obtaining the grayscale value of each pixel in the cutting edge image;

[0088] Step S22, determining the pixel points whose grayscale values ​​are greater than a preset grayscale threshold;

[0089] Step S23 , performing shape matching on the pixel points according to a preset shape template, and determining the pixel points of the specific image area through the shape matching to obtain the bright spot.

[0090] Optionally, this embodiment provides a method for determining bright spots. In this embodiment, after converting the blade edge image into a grayscale image, the grayscale value of each pixel in the blade edge image is extracted, a grayscale threshold is set, and pixels with grayscale values ​​greater than the grayscale threshold are identified as "bright spots." The area of ​​the "bright spots" is then determined, and a blade edge shape template preset in a database is selected as a specific matching area. The shape similarity between the area formed by the "bright spots" and the specific matching area is then determined. "Bright spots" with shape similarities greater than the set threshold are identified as bright spots on the blade edge. The location of the bright spots represents the problem at that location on the blade to be inspected.

[0091] In the technical solution provided in this embodiment, the pixel points whose grayscale values ​​meet the extraction conditions in the edge image are extracted, and the pixel points in a specific area are used as bright spots to determine the location of the problem on the edge of the blade to be inspected.

[0092] Reference Figure 4 In the third embodiment, based on the first embodiment, step S30 includes:

[0093] Step S31, determining the proportion of the bright spot in each pixel in the blade edge image;

[0094] Step S32 : determining the difference between the edge image of the blade to be detected and a preset reference edge image according to the proportion, wherein the proportion is positively correlated with the difference.

[0095] Optionally, this embodiment provides a method for determining the difference between the edge image of the blade to be inspected and a preset reference edge image based on bright spots. In this embodiment, the proportion of pixels in the edge image defined as "bright spots" relative to all pixels in the edge image is determined. Because more bright spots indicate a lower integrity / cleanliness of the blade to be inspected and a greater difference from the complete, clean preset reference edge image, a greater proportion of bright spots relative to all pixels indicates a greater difference between the edge image of the blade to be inspected and the preset reference edge image.

[0096] In the technical solution provided in this embodiment, the difference between the edge image of the blade to be detected and the preset reference edge image is obtained by determining the proportion of pixel points defined as the "bright spots" in the edge image to all pixel points in the edge image.

[0097] Reference Figure 5 In the fourth embodiment, based on the first embodiment, step S40 includes:

[0098] Step S41, determining a first difference degree according to the size of each bright spot in the cutting edge image, wherein the size of the bright spot is positively correlated with the first difference degree;

[0099] Step S42: determining the cutting edge contamination degree according to the first difference.

[0100] Optionally, this embodiment provides a method for determining the edge contamination degree in the edge detection result based on the difference. In this embodiment, whether the bright spot is caused by dirt is determined based on the size of the bright spot. Since the bright spot is essentially composed of pixels, in the edge line image captured by a high-precision camera, the pixels of the edge line image are usually much smaller than the size of a bright spot. The size of each pixel in the edge line image is determined according to the resolution of the display (such as a display with a resolution of 300x300PPI, one square inch contains 90,000 pixels, and 1 pixel is 90,000th of a square inch). Then, the number of pixels contained in each bright spot is determined to determine the size of the bright spot. Then, a positive correlation function is constructed based on the size of the bright spot to obtain the first difference, and the edge contamination degree is determined based on the first difference, wherein the first difference can be positively correlated with the edge contamination degree, or negatively correlated, which is not limited in this embodiment.

[0101] In the technical solution provided in this embodiment, the size of the bright spot is used as the first difference to determine the contamination degree of the blade, that is, whether the bright spot belongs to the dirty type is determined according to the size of the bright spot, and the degree of contamination of the cutting edge of the blade to be detected is determined according to the first difference corresponding to the dirty type bright spot. The traditional manual method of detecting whether the blade edge is contaminated is replaced by a machine, thereby improving detection efficiency.

[0102] Reference Figure 6 In the fifth embodiment, based on the first embodiment, step S40 further includes:

[0103] Step S43, determining a second difference degree according to the number of bright spots in the cutting edge image, wherein the number of bright spots is positively correlated with the second difference degree;

[0104] Step S44: determining the cutting edge integrity according to the second difference.

[0105] Optionally, this embodiment provides a method for determining the edge integrity in the edge detection result based on the degree of difference. In this embodiment, the edge integrity of the bright spots is determined based on the number of bright spots in the edge image. Since different parts of the blade experience different degrees of wear during use, the number of "bright spots" in the image that reflect the degree of wear can be used as a quantitative value reflecting the edge integrity of the blade to be detected. The more bright spots there are, the greater the second degree of difference, and the lower the edge integrity. There are many ways to determine the number of pixels defined as "bright spots" in an image, all of which are conventional technical means in the field and are therefore not further described in this embodiment.

[0106] In the technical solution provided in this embodiment, the number of bright spots is used as the second difference to determine the edge integrity of the blade, and the traditional manual method of detecting whether the blade is complete is replaced by a machine, thereby improving detection efficiency.

[0107] Reference Figure 7 In the sixth embodiment, based on the first embodiment, step S30 further includes:

[0108] Step S33, determining the location area of ​​the bright spot in the blade edge image;

[0109] Step S34, determining a weight value corresponding to the bright spot according to the weight value associated with the position area;

[0110] Step S35 : determining the degree of difference according to the weight value corresponding to the bright spot, wherein the weight value is positively correlated with the degree of difference.

[0111] Optionally, this embodiment provides another method for determining the degree of difference. Because the importance of cutting edges at different locations varies during actual process use, for example, cutting edges at certain locations may cut harder parts during the cutting process, and therefore, cutting edges at these locations have higher requirements for sharpness, meaning they are more important. Therefore, in this embodiment, a larger weight value is assigned to cutting edges in locations with higher importance. When the bright spot is located in a cutting edge location with a higher weight value, the corresponding weight value is also larger. For bright spots with larger weight values, these bright spots are more important in evaluating the blade to be detected during blade detection. Based on the weight values ​​corresponding to the bright spots, a positively correlated function is constructed to determine the degree of difference.

[0112] In the technical solution provided in this embodiment, the difference between the edge image of the blade under inspection and the reference edge image is determined by weighting the bright spots at corresponding locations in the edge image. By assigning weights to bright spots in different regions, the impact of wear and contamination at different edge locations on blade use is refined, improving the accuracy of edge detection.

[0113] Reference Figure 8 In the seventh embodiment, based on the first embodiment, after step S40, the method further includes:

[0114] Step S50, obtaining the diameter of each bright spot;

[0115] Step S60: When the diameter of at least one of the bright spots is greater than a preset threshold, it is determined that the cutting edge of the blade to be detected is damaged, and an alarm prompt message is issued to the user.

[0116] Optionally, in this embodiment, whether the cutting edge of the blade to be detected is damaged is determined based on the diameter of the bright spot. When the diameter of one bright spot among all the bright spots is greater than a preset threshold, it is determined that the cutting edge of the blade to be detected is damaged. At this time, the alarm module of the edge line detection system issues an alarm prompt, so that the user can replace or repair the blade according to the alarm prompt.

[0117] In the technical solution provided in this embodiment, by setting an alarm trigger condition, when the blade to be inspected is detected to be severely damaged, an alarm is issued to the user to prompt the user to replace or repair the blade to avoid quality problems during the use of the blade.

[0118] In addition, the present invention also provides a blade edge detection system, which includes: a PC, a light source device, a high-precision camera, a display, a memory, a processor, and a blade edge detection program stored on the memory and runnable on the processor. When the blade edge detection program is executed by the processor, the steps of the blade edge detection method described above are implemented.

[0119] Optionally, in this embodiment, the PC includes:

[0120] an illumination module, configured to control the light source device to acquire an edge image of the edge to be detected;

[0121] A camera control module, used for controlling the high-precision camera to photograph the cutting edge to be inspected;

[0122] A support module is used to support the cutting edge detection system.

[0123] In addition, the present invention also provides a computer-readable storage medium, which stores a cutting edge detection program. When the cutting edge detection program is executed by a processor, the various steps of the cutting edge detection method described in the above embodiment are implemented.

[0124] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0125] Through the description of the above embodiments, those skilled in the art can clearly understand that the above embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a computer-readable storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0126] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A cutting edge detection method, characterized in that: The steps of the cutting edge detection method include: Obtaining an image of the cutting edge of the blade to be inspected captured by a high-precision camera; Pixels in the blade edge image whose grayscale values ​​are higher than a preset grayscale threshold and located in a specific image area are regarded as bright spots, wherein the bright spots are white light spots in the blade line area of ​​the blade edge image; determining the difference between the edge image of the blade to be detected and the reference edge image according to the bright spot; Determining a cutting edge detection result corresponding to the cutting edge to be detected according to the difference, wherein the cutting edge detection result includes at least one of a cutting edge contamination degree and a cutting edge integrity degree; The step of determining the difference between the edge image of the blade to be detected and the reference edge image according to the bright spot comprises: determining a proportion of the bright spot in each pixel point in the blade edge image; Determining the difference between the edge image of the blade to be detected and the reference edge image according to the proportion, wherein the proportion is positively correlated with the difference; The step of determining the difference between the edge image of the blade to be detected and the reference edge image based on the bright spot further includes: Determining a location area of ​​the bright spot in the blade edge image; Determining a weight value corresponding to the bright spot according to the weight value associated with the position area; The difference is determined according to the weight value corresponding to the bright spot.

2. The cutting edge detection method according to claim 1, wherein: The step of treating the pixel points in the blade edge image whose grayscale values ​​are higher than a preset grayscale threshold and located in a specific image area as bright spots includes: Obtaining the grayscale value of each pixel in the blade edge image; Determine the pixel points whose grayscale values ​​are greater than a preset grayscale threshold; The pixel points are subjected to shape matching according to a preset shape template, and the pixel points of the specific image area are determined by the shape matching to obtain the bright spot.

3. The cutting edge detection method according to claim 1, wherein: The edge detection result includes edge contamination, and the step of determining the edge detection result corresponding to the edge to be detected according to the difference includes: determining a first difference degree according to the size of each bright spot in the edge image, wherein the size of the bright spot is positively correlated with the first difference degree; The cutting edge contamination degree is determined according to the first difference.

4. The cutting edge detection method according to claim 1, wherein: The edge detection result includes edge integrity, and the step of determining the edge detection result corresponding to the edge to be detected according to the difference includes: determining a second difference degree according to the number of bright spots in the blade edge image, wherein the number of bright spots is positively correlated with the second difference degree; The cutting edge integrity is determined according to the second difference.

5. The cutting edge detection method according to claim 1, wherein: After the step of determining the edge detection result corresponding to the blade to be detected according to the difference, the method further includes: Obtaining the diameter of each bright spot; When the diameter of at least one of the bright spots is greater than a preset threshold, it is determined that the cutting edge of the blade to be detected is damaged, and an alarm prompt message is sent to the user.

6. A cutting edge detection system, characterized in that: The blade edge detection system includes: a PC, a light source device, a high-precision camera, a display, a memory, a processor, and a blade edge detection program stored in the memory and runnable on the processor. When the blade edge detection program is executed by the processor, the steps of the blade edge detection method described in any one of claims 1 to 5 are implemented.

7. The cutting edge detection system according to claim 6, wherein: The PC comprises: an illumination module, configured to control the light source device to acquire an edge image of the edge to be detected; A camera control module, used for controlling the high-precision camera to photograph the cutting edge to be inspected; A support module is used to support the cutting edge detection system.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a cutting edge detection program, which, when executed by a processor, implements the steps of the cutting edge detection method according to any one of claims 1 to 5.

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