A method and system for micro-arc multi-layer multi-faceted image acquisition

Abstract

The application is particularly a kind of method and system for micro-arc surface multilayer multi-surface image acquisition, relating to the technical field of medical instrument detection, comprising: an image data acquisition module: collecting image information of orthopedic consumables through a camera; a data analysis module: obtaining a crack value and a hole offset value after analyzing the image information of orthopedic consumables; a comprehensive processing module: obtaining a defect evaluation coefficient after comprehensively processing the crack value and the hole offset value; a defect evaluation module.In the application, multidimensional modeling of the crack value and the hole offset value converts surface defects into quantifiable risk indicators; the crack value comprehensively considers defect length and spatial distribution, and can directly reflect the risk of consumable structural integrity; the hole offset value quantifies the influence of hole position deviation on assembly accuracy, realizes the management of orthopedic consumables, avoids the use of unqualified orthopedic consumables, and thus avoids the medical risks.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical instrument detection, and in particular to a method and system for micro-arc surface multi-layer multi-surface image acquisition. BACKGROUND

[0002] Orthopedic implants, as medical devices that directly contact human tissues, their surface quality is closely related to clinical safety and effectiveness. Orthopedic consumables such as artificial joints, bone plates, and intramedullary nails have complex structures such as micro-arc surfaces, complex hole systems, and multi-layered surfaces.

[0003] However, existing detection techniques mostly only detect defect length or area, lack comprehensive evaluation of defect spatial distribution (such as crack connectivity and opening distance deviation), and are difficult to predict the potential impact of defects on the mechanical properties of consumables. Traditional manual detection is low in efficiency and strong in subjectivity, and is difficult to meet the full-size and full-defect type detection needs of medical-grade products.

[0004] Therefore, a method and system for micro-arc surface multi-layer multi-surface image acquisition are needed, which realizes full-angle coverage of micro-arc surface structures and accurate detection of defects through multi-camera array, intelligent light source regulation, three-dimensional imaging technology, and multi-dimensional quantification algorithm, to meet the urgent needs of orthopedic consumables in high-precision machining, clinical safety, and process traceability. SUMMARY

[0005] The purpose of the present application is to solve the above problems and provide a method and system for micro-arc surface multi-layer multi-surface image acquisition.

[0006] To achieve the above purpose, the present application adopts the following technical solutions:

[0007] A micro-arc surface multi-layer multi-surface image acquisition system, comprising:

[0008] An image data acquisition module acquires image information of orthopedic consumables through a camera;

[0009] A data analysis module analyzes the image information of orthopedic consumables to obtain crack values and opening deviation values;

[0010] A comprehensive processing module processes the crack values and opening deviation values to obtain a defect evaluation coefficient;

[0011] A defect evaluation module determines the defect grade of orthopedic consumables based on the defect evaluation coefficient and performs corresponding processing.

[0012] Preferably, the image data acquisition module specifically comprises:

[0013] A top camera is combined with a side camera, wherein:

[0014] Top camera: detect the flatness of the top surface, coating uniformity;

[0015] Side camera: capture thread profile, edge burr;

[0016] Macro camera: take a second high-definition shot of suspicious areas;

[0017] Programmable LED light source controller is adopted to support multi-channel independent dimming:

[0018] Low-angle ring light is used when detecting reflective surfaces;

[0019] Encoder or laser sensor is used to track the position of consumables in real time, trigger camera exposure, and ensure that there is no trailing in motion imaging;

[0020] The main body of the consumables is automatically positioned through template matching, and the background redundant area is cropped;

[0021] The image is preprocessed, including image denoising, image enhancement, and image correction.

[0022] Preferably, the crack value acquisition process comprises:

[0023] Divide the orthopedic consumable surface into regions in a preset size to obtain each marking region;

[0024] Through Edge detection algorithm, extract the cracks and scratches of the orthopedic consumable surface corresponding to each marking region;

[0025] Respectively obtain the crack and scratch profiles in each marking region, and sequentially connect the first and last ends of each crack profile and scratch profile with a straight line and calculate the length of the straight line to obtain the crack value and the scratch value;

[0026] Respectively arrange each crack value and scratch value in descending order according to the numerical value, and extract the maximum crack value and the maximum scratch value, and divide the maximum crack value and the maximum scratch value by the area of the marking region , to obtain the crack span value and the scratch span value; calculate the sum of the crack span value and the scratch span value to obtain the crack span value;

[0027] Cumulatively obtain the crack span total value of each marking region;

[0028] After marking the crack profiles and scratch profiles in the marking region, they are uniformly marked as crack profiles, the endpoints of the first and last ends of each crack profile are sequentially obtained, and the endpoints of the adjacent two crack profiles are sequentially connected with a straight line until a closed figure formed by the crack profiles is formed, and the figure is the largest figure that can be formed by all the crack profiles, and the area of the figure is calculated and divided by the area of the region to obtain the spread degree.

[0029] Obtain the spread degree of each marking area, and arrange the obtained each spread degree in descending order according to the numerical value, and extract the maximum spread degree, denoted as spread heterogeneity;

[0030] After comprehensive processing of the total value of the crack span and the spread heterogeneity, the crack value of the orthopedic consumable is obtained.

[0031] Preferably, the obtaining process of the hole offset value comprises:

[0032] Taking the standard contour image of the orthopedic consumable as a reference, based on the extracted orthopedic consumable contour image, the extracted orthopedic consumable contour image is matched with the standard contour image of the orthopedic consumable; At this time, the extracted orthopedic consumable contour image and the standard contour image of the orthopedic consumable are coincident in the outer contour;

[0033] The holes in the standard contour image of the orthopedic consumable are marked, and the center points of each hole are obtained and denoted as standard center points;

[0034] Taking the standard center point as the starting point, a straight line connecting the holes in the standard contour image and the corresponding holes in the extracted contour image is drawn, and the length of the straight line is calculated and then the radius of the hole in the standard contour image is subtracted to obtain the distance between the standard contour hole edge and the extracted contour hole edge, denoted as offset length;

[0035] The offset length corresponding to each hole is obtained in turn, and the offset length threshold is preset, the offset length and the offset length threshold are calculated by difference, and the offset length difference is obtained;

[0036] Obtain the contour hole position of the extracted orthopedic consumable corresponding to each offset length difference, and the center position of each hole;

[0037] The center of the hole corresponding to two offset length differences is connected in a straight line in turn to obtain the distribution length value;

[0038] All the distribution length values are arranged in descending order according to the numerical value, and the maximum distribution length value is extracted; the sum of the two offset length differences corresponding to the maximum distribution length value is calculated to obtain the offset length difference sum;

[0039] The maximum distribution length value and the offset length difference sum value are respectively taken as two legs of a right triangle, and the remaining leg is connected to obtain a complete right triangle, and the area of the right triangle is calculated to obtain the hole offset value.

[0040] Preferably, the weight factor of the preset crack value and the hole offset value is calculated by multiplying the crack value and the hole offset value by the weight factor corresponding thereto, and the sum is obtained to obtain the defect evaluation coefficient.

[0041] Preferably, the preset three groups of threshold values have a range of values, and the range of values of each group of threshold values corresponds to a defect level.

[0042] Preferably, when the defect level is a slight defect, the orthopedic consumables are marked and allowed to enter an artificial review process.

[0043] When the defect level is a moderate defect, a warning is triggered, the batch of consumables corresponding to the moderate defect is isolated, and the batch of consumables is re-detected.

[0044] When the defect level is a severe defect, the use is stopped, and the flow of all severe defect orthopedic consumables is locked.

[0045] Preferably, the comprehensive processing module is further used for:

[0046] Establishing a historical data database to store the crack value, the hole offset value and the defect evaluation coefficient of each batch of orthopedic consumables.

[0047] A micro-arc multi-layer multi-surface image acquisition method, comprising:

[0048] Image data acquisition: acquiring image information of orthopedic consumables through a camera;

[0049] Data analysis: obtaining a crack value and a hole offset value by analyzing the image information of the orthopedic consumables;

[0050] Comprehensive processing: obtaining a defect evaluation coefficient by comprehensively processing the crack value and the hole offset value;

[0051] Defect evaluation: determining a defect level of the orthopedic consumables based on the defect evaluation coefficient and performing corresponding processing.

[0052] As described above, due to the adoption of the above technical solutions, the present application has the following advantages:

[0053] 1. The present application converts surface defects into quantifiable risk indicators through multi-dimensional modeling of crack values and hole offset values. The crack value comprehensively considers defect length and spatial distribution, and can directly reflect the risk of consumable structural integrity. The hole offset value quantifies the impact of hole position deviation on assembly accuracy, thereby achieving management of orthopedic consumables and avoiding the use of unqualified orthopedic consumables, which may cause medical risks.

[0054] 2、The application realizes full-angle detection of the small arc surface and multi-layer multi-surface structure of orthopedic consumables through the cooperative design of the multi-camera array and the intelligent light source; the combination of the top camera, the side camera and the macro camera can capture the details of the top surface, the side thread and the local suspicious area of the consumables respectively, and in cooperation with the multi-angle rotating object table, the blind area of the traditional single-view detection is eliminated, which is especially suitable for complex curvature parts such as artificial joint spherical surface and screw chamfer; at the same time, the application of the telecentric lens and the annular polarized light effectively suppresses the imaging distortion caused by the reflection of the metal surface, and in combination with the structured light three-dimensional scanning technology, the two-dimensional image and the three-dimensional point cloud data are synchronously acquired, so that the arc surface contour precision detection can reach the micron level. BRIEF DESCRIPTION OF DRAWINGS

[0055] In the following description of the example embodiments in conjunction with the accompanying drawings, more details, features and advantages of the application are disclosed, in which:

[0056] Figure 1 The flowchart of the application. DETAILED DESCRIPTION

[0057] Several embodiments of the application will be described in more detail below with reference to the accompanying drawings, so that those skilled in the art can implement the application. The application can be embodied in many different forms and purposes and should not be limited to the embodiments described herein. These embodiments are provided to make the application comprehensive and complete, and to fully convey the scope of the application to those skilled in the art. The embodiments do not limit the application.

[0058] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It will be further understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and / or the present specification, and should not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

[0059] Referring to Figure 1 The application provides a technical solution:

[0060] A small arc surface multi-layer multi-surface image acquisition system, comprising:

[0061] Image data acquisition module: acquiring image information of orthopedic consumables through the camera;

[0062] Specifically includes:

[0063] For complex structure consumables (such as hole steel plate, multi-thread screw), top camera combined with side camera is adopted, wherein:

[0064] Top camera (vertical view): detect the flatness of the top surface and the uniformity of the coating;

[0065] Side camera (45° inclined view): capture the thread profile and edge burrs;

[0066] Macro camera (local zoom-in): take a second high-definition shot of suspicious areas (such as suspected cracks);

[0067] Use a programmable LED light source controller to support multi-channel independent dimming (such as adjusting the brightness of the front light, back light, and side light separately):

[0068] When detecting a reflective surface (such as a polished steel plate), use a low-angle ring light to highlight scratches;

[0069] Use an encoder or laser sensor to track the position of the consumables in real time, trigger the camera exposure, and ensure that there is no trailing in the motion imaging;

[0070] And automatically locate the main body of the consumables through template matching, and cut out the background redundant area;

[0071] And pre-process the image, including image denoising, image enhancement, and image correction;

[0072] Image denoising: remove interference signals introduced during image acquisition due to sensor noise, uneven lighting, etc.; including Gaussian noise, salt and pepper noise, and periodic noise;

[0073] Image enhancement: highlight the defect features of orthopedic consumables (such as cracks, scratches, and size deviations), and suppress irrelevant backgrounds; including contrast enhancement, edge enhancement, and color space conversion;

[0074] Image correction: compensate for geometric distortion or uneven lighting during image acquisition to ensure detection accuracy; including geometric correction and lighting uniformity correction;

[0075] The image data acquisition module uses the following optimization scheme for small arc surface structures (such as artificial joint spherical surfaces and screw chamfers):

[0076] Configure a multi-angle rotating stage that supports 5° interval rotation of the consumables within a range of 0~360°, and cooperate with the camera array to realize full-angle coverage of the arc surface;

[0077] Use a telecentric lens combined with a ring polarized light to eliminate imaging distortion caused by arc surface reflection, ensuring clear edge profiles;

[0078] Use structured light three-dimensional scanning technology to simultaneously acquire two-dimensional images and three-dimensional point cloud data of the arc surface, improving the detection accuracy of small arc deviations;

[0079] Data analysis module: analyze the image information of orthopedic consumables to obtain crack value and hole offset value;

[0080] The process of obtaining the crack value includes:

[0081] Divide the surface of the orthopedic consumable into regions according to the preset size to obtain each marking region;

[0082] Divide the surface of the consumable into regular or custom regions (such as grid, functional partition) to facilitate positioning of defect distribution and quantitative analysis;

[0083] Implementation:

[0084] Grid division method: divide the image into rectangular grids according to the preset size, each grid is a marking region, and number it; Application scenario: suitable for consumables with flat surface (such as steel plate), facilitating standardized comparison of defects in each region;

[0085] Functional region division: manually or automatically segment the region of interest according to the structure of the consumable (such as the head, rod, and thread section of a screw). For example: locate the feature points by template matching, and divide the region by polygon clipping;

[0086] Through Edge detection algorithm, extract the cracks and scratches on the surface of the orthopedic consumable corresponding to each marking region;

[0087] Obtain the crack and scratch profiles in each marking region respectively, and sequentially connect the first and last ends of each crack profile and scratch profile with a straight line and calculate the length of the straight line to obtain the crack value and scratch value;

[0088] Sort each crack value and scratch value in descending order according to the numerical value, and extract the maximum crack value and maximum scratch value, respectively; divide the maximum crack value and maximum scratch value by the area of the marking region , to obtain the crack span value and scratch span value; Calculate the sum of the crack span value and the scratch span value to obtain the crack span value;

[0089] Cumulatively obtain the crack span total value of each marking region;

[0090] After marking the crack profiles and scratch profiles in the marking region, they are collectively referred to as crack profiles, the endpoints of the first and last ends of each crack profile are sequentially obtained, and the endpoints of the adjacent two crack profiles are sequentially connected with a straight line until a closed figure is formed by the crack profiles, and the figure is the largest figure that can be formed by all crack profiles. Calculate the area of the figure and divide it by the area of the region to obtain the spread degree;

[0091] Obtain the spread degree of each marking area, and arrange the obtained each spread degree in descending order according to the numerical value, and extract the maximum spread degree, denoted as spread heterogeneity;

[0092] By analyzing the crack span value and spread heterogeneity of each marking area, the area with the most serious defect (such as the area corresponding to the maximum crack span value or the maximum spread heterogeneity) can be located;

[0093] After comprehensive processing of the crack span total value and the spread heterogeneity, the crack value of the orthopedic consumable is obtained;

[0094] The crack span total value and the spread heterogeneity are marked as and respectively, and then substituted into the formula: ; the crack value of the orthopedic consumable is obtained ;

[0095] Among them, is the maximum allowed crack span total value; a1 and a2 are the weight factors of the crack span total value and the spread heterogeneity respectively;

[0096] Cracks (especially cracks) can cause orthopedic consumables (such as steel plates and screws) to break or fail when subjected to stress. The crack value indirectly reflects the structural integrity risk of the consumable by quantifying the length (crack value, scratch value) and spatial distribution (spread) of defects;

[0097] For example: the higher the crack value, the more serious the defect, and the higher the probability of fracture of the consumable due to stress concentration after implantation in the human body;

[0098] In orthopedic surgery, surface defects can cause inflammatory reactions or affect bone tissue growth; defects with high spread (such as large-area scratches or connected cracks) can increase the risk of infection or cause poor implant-bone tissue bonding; the crack value can be used as a quantitative indicator to predict such risks;

[0099] The process of obtaining the hole offset value includes:

[0100] Taking the standard contour image of the orthopedic consumable as a reference, based on the extracted orthopedic consumable contour image, the extracted orthopedic consumable contour image is matched with the standard contour image of the orthopedic consumable; at this time, the outer contour of the extracted orthopedic consumable contour image coincides with that of the standard contour image of the orthopedic consumable;

[0101] By matching the outer contour of the extracted consumable contour with the standard contour, the interference caused by the overall position, rotation or scaling of the consumable is eliminated, ensuring that the subsequent hole offset analysis only focuses on the difference in the hole position itself, rather than the overall attitude deviation of the consumable;

[0102] Mark the holes in the standard contour image of orthopedic consumables, and obtain the center points of each hole and mark them as standard center points;

[0103] Mark the holes in the standard contour and extract the center points (standard center points), and establish a theoretical position reference for each hole. The hole position in the actual contour needs to be compared with the standard center point to quantify the degree of deviation;

[0104] Starting from the standard center point, draw a straight line connecting the holes in the standard contour image and the corresponding extracted contour image holes, calculate the length of the straight line, and then subtract the radius of the hole in the standard contour image to obtain the distance between the standard contour hole edge and the extracted contour hole edge, which is called the deviation length. This deviation length is the longest length that can be obtained between the two contours;

[0105] Starting from the standard center point, connect the edges of the standard hole and the actual hole, calculate the length of the straight line and subtract the standard radius to obtain the distance between the standard contour hole edge and the actual contour hole edge (deviation length).

[0106] This value is essentially the maximum deviation of a single hole in the radial direction (as the straight line passes through the center of the circle, it is the longest distance);

[0107] Obtain the deviation length corresponding to each hole in turn, and preset the deviation length threshold. Calculate the difference between the deviation length and the deviation length threshold to obtain the deviation length difference;

[0108] Obtain the contour hole position of the extracted orthopedic consumables corresponding to each deviation length difference, and the center position corresponding to each hole;

[0109] Connect the hole centers corresponding to two deviation length differences in turn to obtain the distribution length value;

[0110] Arrange all the distribution length values in descending order according to their numerical values, and extract the largest distribution length value. Sum the two deviation length differences corresponding to the largest distribution length value to obtain the deviation length difference sum;

[0111] Take the largest distribution length value and the deviation length difference sum as two legs of a right triangle, and connect the remaining leg to obtain a complete right triangle. Calculate the area of the right triangle to obtain the hole deviation value;

[0112] Comprehensive processing module: obtain the defect evaluation coefficient after comprehensive processing of the crack value and the hole deviation value, including:

[0113] Preset the weight factor of the crack value and the hole deviation value. Multiply the crack value and the hole deviation value by their corresponding weight factors respectively, and then sum them to obtain the defect evaluation coefficient

[0114] The defect evaluation module determines the defect level of the orthopedic consumables based on the defect evaluation coefficient and performs corresponding processing;

[0115] The preset three groups of threshold value ranges correspond to one defect level, the defect evaluation coefficient is matched with the three groups of threshold value ranges to obtain the defect level corresponding to the defect evaluation coefficient, and the defect level includes a slight defect, a moderate defect and a severe defect; and the medical risk of the orthopedic consumables in the medical institutions is evaluated based on the defect level;

[0116] When the defect level is a slight defect, the orthopedic consumables are marked and allowed to enter the artificial re-inspection process;

[0117] When the defect level is a moderate defect, a warning is triggered, the batch of consumables corresponding to the moderate defect is isolated, and the batch of consumables is re-detected;

[0118] When the defect level is a severe defect, the use is stopped, and the flow direction of all the orthopedic consumables with the severe defect is locked;

[0119] The comprehensive processing module is further used for:

[0120] A historical database is established to store the crack value, the hole offset value and the defect evaluation coefficient of each batch of orthopedic consumables.

[0121] A micro-arc surface multilayer multi-surface image acquisition method, comprising:

[0122] Image data acquisition: image information of the orthopedic consumables is acquired by a camera;

[0123] Data analysis: the crack value and the hole offset value are obtained after analyzing the image information of the orthopedic consumables;

[0124] Comprehensive processing: the defect evaluation coefficient is obtained after the crack value and the hole offset value are comprehensively processed;

[0125] Defect evaluation: the defect level of the orthopedic consumables is determined based on the defect evaluation coefficient, and corresponding processing is performed.

[0126] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value, and the influence weight factor and the specific coefficient value in the formula are set by the person skilled in the art according to the actual situation, which can be adjusted and modified later.

[0127] The foregoing description of the embodiments enables one of ordinary skill in the art to make or use the application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein can be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A multi-layer, multi-faceted image acquisition system for micro-arc surfaces, characterized in that, The method comprises the following steps: An image data acquisition module: acquiring image information of the orthopedic consumables through a camera; A data analysis module: obtaining a crack value and a hole offset value after analyzing the image information of the orthopedic consumables; A comprehensive processing module: obtaining a defect evaluation coefficient after comprehensively processing the crack value and the hole offset value; The process of obtaining the crack value comprises the following steps: Dividing the surface of the orthopedic consumables into regions in a preset size to obtain each marking region; By An edge detection algorithm is used to extract the cracks and scratches on the surface of the orthopaedic consumable corresponding to each marking area. Respectively obtaining crack and scratch contours in each marking region, and respectively connecting the first and last ends of each crack and scratch contour with a straight line and calculating the length of the straight line to obtain a crack value and a scratch value; sequentially arrange each crack value and scratch value in descending order according to the numerical value, and extract the maximum crack value and the maximum scratch value therefrom, divide the maximum crack value and the maximum scratch value by the area of the marking region respectively, to obtain a crack span value and a scratch span value; calculate the sum of the crack span value and the scratch span value to obtain a crack span value; Cumulatively obtaining a crack span total value of each marking region; After marking the crack and scratch contours in the marking region, the crack and scratch contours are uniformly marked as crack contours, the endpoints of the first and last ends of each crack contour are obtained in sequence, and the endpoints of two adjacent crack contours are connected with a straight line until a figure enclosed by the crack contours is formed, and the figure is the largest figure that can be formed by all the crack contours, the area of the figure is calculated, and the area is divided by the area of the region to obtain a spread degree; Obtaining the spread degree of each marking region, arranging the obtained spread degrees in descending order according to the numerical value, and extracting the maximum spread degree, which is marked as spread heterogeneity; Comprehensively processing the crack span total value and the spread heterogeneity to obtain the crack value of the orthopedic consumables; The process of obtaining the hole offset value comprises the following steps: Taking the standard contour image of the orthopedic consumables as a reference, matching the extracted orthopedic consumable contour image with the standard contour image of the orthopedic consumables based on the extracted orthopedic consumable contour image; at this time, the outer contours of the extracted orthopedic consumable contour image and the standard contour image of the orthopedic consumables coincide; Marking the holes in the standard contour image of the orthopedic consumables, and obtaining the center points of each hole and marking them as standard center points; Taking the standard center point as a starting point, drawing a straight line connecting the holes in the standard contour image and the holes in the extracted contour image, calculating the length of the straight line, and then subtracting the radius of the hole in the standard contour image to obtain the distance between the standard contour hole edge and the extracted contour hole edge, which is marked as the offset length; Obtaining the offset length corresponding to each hole in sequence, and presetting the offset length threshold, calculating the difference between the offset length and the offset length threshold to obtain the offset length difference; Obtaining the contour hole position of the extracted orthopedic consumables corresponding to each offset length difference, and the center position corresponding to each hole; Connecting the center points of two offset length differences with a straight line to obtain a distribution length value; Arranging all the distribution length values in descending order according to the numerical value, and extracting the maximum distribution length value; summing the two offset length differences corresponding to the maximum distribution length value to obtain the offset length difference sum; Taking the maximum distribution length value and the offset length difference sum as two legs of a right triangle, connecting the remaining leg to obtain a complete right triangle, calculating the area of the right triangle to obtain the hole offset value; A defect evaluation module: determining the defect grade of the orthopedic consumables based on the defect evaluation coefficient and performing corresponding processing.

2. The system according to claim 1, wherein, The image data acquisition module specifically comprises: A top camera combined with a side camera is adopted, wherein: The top camera detects the flatness of the top surface and the uniformity of the coating; The side camera captures the thread profile and edge burrs; The macro camera takes a second high-definition shot of the suspicious area; A programmable LED light source controller is adopted to support multi-channel independent dimming: When detecting a reflective surface, a low-angle ring light is used; An encoder or laser sensor is used to track the position of the consumables in real time, trigger the camera exposure, and ensure that there is no trailing in the moving image; The main body of the consumables is automatically positioned through template matching, and the background redundant area is cropped; The image is preprocessed, including image denoising, image enhancement, and image correction.

3. The system according to claim 1, wherein, The preset crack value and the weight factor of the hole offset value are multiplied by the corresponding weight factor, and the sum of the products is obtained as the defect evaluation coefficient.

4. The system according to claim 3, wherein, The preset three groups of threshold value ranges correspond to a defect level, and the defect evaluation coefficient is matched with the three groups of threshold value ranges to obtain the defect level corresponding to the defect evaluation coefficient, wherein the defect level includes a mild defect, a moderate defect, and a severe defect.

5. The system according to claim 4, wherein, When the defect level is a mild defect, the orthopedic consumable is marked and allowed to enter the manual review process; When the defect level is a moderate defect, a warning is triggered, the batch of consumables corresponding to the moderate defect is isolated, and all the consumables of the batch are re-detected; When the defect level is a severe defect, the use is stopped, and the flow direction of all severe defects of the orthopedic consumable is locked.

6. The system according to claim 1, wherein, The comprehensive processing module is also used to: Establish a historical data database to store the crack value, hole offset value, and defect evaluation coefficient of each batch of orthopedic consumables.

7. A method for micro-arc multi-layer multi-facet image acquisition, according to any one of claims 1-6, wherein the system for micro-arc multi-layer multi-facet image acquisition is characterized in that, It includes: Image data acquisition: image information of the orthopedic consumable is collected through the camera; Data analysis: the crack value and the hole offset value are obtained after analyzing the image information of the orthopedic consumable; Comprehensive processing: the defect evaluation coefficient is obtained after the crack value and the hole offset value are comprehensively processed; Defect evaluation: the defect level of the orthopedic consumable is determined based on the defect evaluation coefficient, and the corresponding processing is performed.

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