A method and system for quality inspection and evaluation of floss flower products based on digitization

Abstract

The present application discloses a method and system for detecting and evaluating the quality of floss flower products based on digitization, belonging to the field of product quality inspection. The present application performs abnormal analysis of the binding position based on the texture image data of the binding position and the position data corresponding to the floss flower after binding, and then performs abnormal analysis of binding damage based on the image data of the floss flower product after binding. The quality analysis of floss flower binding is carried out by comprehensively considering the results of the abnormal analysis of the binding position and the abnormal analysis of binding changes. The present application comprehensively analyzes the texture image and position accuracy of the binding position after binding, accurately and efficiently evaluates the binding quality, and while evaluating the binding quality, takes into account the damage analysis of the product appearance during the binding process, and then comprehensively analyzes the binding quality of the product.

Description

Technical Field

[0001] This application belongs to the field of product quality inspection, and specifically relates to a digital-based method and system for inspecting and evaluating the quality of velvet flower products. Background Art

[0002] Velvet flower products are traditional handicrafts made mainly from silk and feathers through unique manufacturing processes. They are usually used as decorations or gifts and have high artistic and historical values. Velvet flower products have bright and colorful colors and delicate shapes, which can showcase the charm of Chinese traditional culture. They are widely used in fields such as stage costumes, film and television props, folk art, and traditional handicrafts. When inspecting the quality of velvet flower products, a quality inspection and evaluation system for velvet flower products is required. There is no dedicated inspection system for the quality inspection of velvet flower products in the existing technology. Usually, visual analysis is carried out manually, and other inspection systems cannot comprehensively analyze the texture image and position accuracy of the binding position after binding, and at the same time, they cannot analyze the damage to the product appearance during the binding process, resulting in poor evaluation efficiency and accuracy. Most of the existing technologies have the above problems.

[0003] In order to accurately and efficiently evaluate the binding quality, this application designs a digital-based method and system for inspecting and evaluating the quality of velvet flower products. Summary of the Invention

[0004] To solve the deficiencies in the existing technology mentioned in the background art, this application proposes a digital-based method and system for inspecting and evaluating the quality of velvet flower products. This application comprehensively analyzes the texture image and position accuracy of the binding position after binding, accurately and efficiently evaluates the binding quality, and while evaluating the binding quality, takes into account the analysis of the damage to the product appearance during the binding process, and then comprehensively analyzes the binding quality of the product.

[0005] To achieve the above object, this application provides the following technical solutions: In the first aspect, this application provides a digital-based method for inspecting and evaluating the quality of velvet flower products, which includes the following specific steps:

[0006] Step 1: Obtain the image data of the velvet flower product to be inspected, and at the same time obtain the texture image data of the binding position and the position data corresponding to the velvet flower after binding;

[0007] Step 2: Perform abnormal analysis of the binding position based on the texture image data of the binding position and the position data corresponding to the velvet flower after binding;

[0008] Step 3: Perform abnormal analysis of the binding damage based on the image data of the velvet flower product after binding;

[0009] Step 4: Conduct the quality analysis of the velvet flower binding by integrating the analysis results of the abnormal binding position and the abnormal binding change.

[0010] Preferably, the specific content of obtaining the image data of the velvet flower product to be detected, and simultaneously obtaining the texture image data of the binding position and the binding position data is as follows:

[0011] Step 11: Obtain the image data of the velvet flower product to be detected after binding, obtain the image data of the fluff on both sides of the position of the binding thread from the image, and obtain the orientation angle data of the fluff on both sides of the binding thread when the product is placed vertically;

[0012] Step 12: Obtain the texture image data corresponding to the binding position and the binding position data corresponding after binding from the image data of the velvet flower product;

[0013] Step 13: Store the data obtained after acquisition in the storage component.

[0014] Preferably, the abnormal binding position analysis based on the texture image data of the binding position and the position data corresponding to the velvet flower after binding includes the following specific steps:

[0015] Step 21: Obtain the texture image data corresponding to all binding positions and the binding position data corresponding after binding;

[0016] Step 22: Import the binding position data corresponding after binding obtained into the binding position abnormal value calculation formula to calculate the binding position abnormal value. Among them, the binding position abnormal value calculation formula is: , where xi is the distance from the i-th actual binding point position to the corresponding standard binding point, m is the number of binding points, xz is the safety offset distance of the binding point. In this formula, the binding offset distances of all binding points are comprehensively analyzed for the abnormal binding position;

[0017] Step 23: Obtain the texture image data corresponding to the binding position and the texture image data that the binding position needs to form, and import the obtained texture image data corresponding to the binding position and the texture image data that the binding position needs to form into the binding position image abnormal value calculation formula to calculate the binding position image abnormal value. Among them, the binding position image abnormal value calculation formula is: , where a is the contour similarity weight, s() is the area of the image in the parentheses, piz is the contour image of the i-th binding position, piu is the standard contour image of the i-th binding position, is the intersection of the images, is the union of images, Ni is the number of pixel points at the i-th binding position, zij is the pixel value of the j-th pixel point at the i-th binding position, and zijm is the standard pixel value of the j-th pixel point at the i-th binding position. In this formula, the damage and contour anomalies at the binding position during the binding process are comprehensively analyzed through the image contour and pixel anomalies at the binding position;

[0018] Step 24: Obtain the calculated binding position anomaly value and the binding position image anomaly value, and add them after weighting respectively to obtain the binding position anomaly analysis coefficient. In this step, the anomalies at the binding part during the binding process are comprehensively analyzed through the position, contour, and pixel anomalies at the binding part.

[0019] Preferably, the analysis of binding damage anomalies based on the image data of the floss flower product after binding includes the following specific steps:

[0020] Step 31: Obtain the orientation angle data of the fluff on both sides of the binding thread when the product is placed vertically, and at the same time obtain the standard orientation angle of the fluff on both sides when the product is placed vertically;

[0021] Step 32: Import the obtained orientation angle data of the fluff on both sides of the binding thread when the product is placed vertically and the standard orientation angle of the fluff on both sides when the product is placed vertically into the calculation formula of the binding damage anomaly analysis value. Among them, the calculation formula of the binding damage anomaly analysis value is: , where M is the number of fluff on both sides of the binding thread, is the orientation angle of the c-th fluff passed by the binding thread when the product is placed vertically, is the standard orientation angle of the c-th fluff passed by when the product is placed vertically, Lc is the vertical distance from the middle of the c-th fluff to the binding thread, and Lm is the length of the product.

[0022] Preferably, the analysis of the binding quality of the floss flower by integrating the binding position anomaly analysis result and the binding change anomaly analysis result includes the following specific contents: Obtain the calculated binding position anomaly analysis coefficient and the binding damage anomaly analysis value, and substitute the obtained binding position anomaly analysis coefficient and the binding damage anomaly analysis value into the calculation formula of the binding quality analysis value. Among them, the calculation formula of the binding quality analysis value is: , where Zw is the binding position anomaly analysis coefficient, and exp() is the exponential power of the natural constant e;

[0023] Compare the calculated binding quality analysis value with the set binding quality threshold. If the calculated binding quality analysis value is greater than or equal to the set binding quality threshold, it is judged that the binding of the floss flower product is qualified. If the obtained binding quality analysis value is less than the set binding quality threshold, it is judged that the binding of the floss flower product is unqualified.

[0024] In a second aspect, the present application provides a digitalized quality inspection and evaluation system for velvet flower products, which is implemented based on the above-mentioned digitalized quality inspection and evaluation method for velvet flower products. Specifically, it includes a data acquisition module, a position anomaly analysis module, a damage anomaly analysis module, and a binding quality analysis module. Among them, the data acquisition module is used to acquire the image data of the velvet flower products to be inspected, and at the same time acquire the texture image data of the binding position and the position data corresponding to the velvet flower after binding. The position anomaly analysis module performs binding position anomaly analysis based on the texture image data of the binding position and the position data corresponding to the velvet flower after binding. The damage anomaly analysis module performs binding damage anomaly analysis based on the image data of the velvet flower products after binding. The binding quality analysis module is used to comprehensively analyze the binding quality of the velvet flower by combining the binding position anomaly analysis results and the binding change anomaly analysis results. It may also include a control module, which is used to control the operation of the data acquisition module, the position anomaly analysis module, the damage anomaly analysis module, and the binding quality analysis module.

[0025] In a third aspect, the present application provides an electronic device, including: a processor and a memory, where the memory stores a computer program that can be called by the processor;

[0026] The processor executes the above-mentioned digitalized quality inspection and evaluation method for velvet flower products by calling the computer program stored in the memory.

[0027] In a fourth aspect, the present application provides a computer-readable storage medium storing instructions, which when run on a computer, cause the computer to execute the above-mentioned digitalized quality inspection and evaluation method for velvet flower products.

[0028] At the same time, compared with the prior art, the technical effects and advantages of the present application are as follows: 1. The present application performs binding position anomaly analysis based on the texture image data of the binding position and the position data corresponding to the velvet flower after binding, and then performs binding damage anomaly analysis based on the image data of the velvet flower products after binding. By comprehensively analyzing the binding position anomaly analysis results and the binding change anomaly analysis results, the present application comprehensively analyzes the texture image and position accuracy of the binding position after binding, and accurately and efficiently evaluates the binding quality.

[0029] 2. While evaluating the binding quality, it also takes into account the damage analysis of the product appearance during the binding process, and then comprehensively analyzes the binding quality of the product. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings;

[0031] Figure 1 It is a schematic diagram of the overall process of a digital-based quality inspection and evaluation method for velvet flower products in this application;

[0032] Figure 2 It is a schematic diagram of the specific process of step 2 of a digital-based quality inspection and evaluation method for velvet flower products in this application;

[0033] Figure 3 It is a schematic diagram of the specific process of step 4 of a digital-based quality inspection and evaluation method for velvet flower products in this application;

[0034] Figure 4 It is a schematic diagram of the overall framework of a digital-based quality inspection and evaluation system for velvet flower products in this application. Detailed implementation manners

[0035] The following will clearly and completely describe the technical solutions in the embodiments of this application in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only some embodiments of this application, rather than all embodiments. The description of at least one exemplary embodiment is actually only illustrative and in no way limits this application or its application or use.

[0036] In addition, the drawings are only schematic diagrams of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and thus repeated descriptions thereof will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor methods and / or microcontroller methods.

[0037] It should be understood that although the terms "first", "second", etc. may be used here to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit can be called the second unit, and similarly the second unit can be called the first unit. The term "and / or" used here includes any and all combinations of one or more of the listed related items.

[0038] Example 1

[0039] To solve the technical problems raised in the background art, the present application provides a preferred embodiment: As Figures 1 - 3 shown, a method for detecting and evaluating the quality of digital floss flower products includes the following specific steps:

[0040] Step 1: Obtain the image data of the floss flower products to be detected, and at the same time obtain the texture image data of the binding position and the position data corresponding to the floss flower after binding;

[0041] In this embodiment, Step 1 includes the following specific steps: Step 11: Obtain the image data of the floss flower products to be detected after binding, obtain the image data of the fluff on both sides of the binding line from the image, and obtain the orientation angle data of the fluff on both sides of the binding line when the product is placed vertically. The image data of the fluff on both sides of the binding line and the angle data of the fluff on both sides of the binding line can be obtained through general image processing software, which is a conventional means for obtaining image information in the prior art. For example, for the angle data of the fluff on both sides, if this fluff faces left and its orientation is changed under the influence of the binding line;

[0042] Step 12: Obtain the texture image data corresponding to the binding position and the binding position data corresponding after binding from the image data of the floss flower products. The following are the general steps for obtaining the required data: Prepare image data: Collect and prepare the image data of the floss flower products, ensure that the images are clear and unobstructed, and mark the position of the binding line; Image processing: Use image processing techniques, such as filtering, edge detection, and threshold processing, to extract the texture image data of the binding line; Identify the binding line position: Use computer vision techniques, such as template matching, feature matching, and deep learning, to identify the position of the binding line; Obtain the texture image data: According to the identified binding line position, extract the corresponding texture image data from the image data of the floss flower products; Obtain the position data after binding: After obtaining the image data of the floss flower products after binding, use computer vision techniques to identify the position of the binding line and obtain the corresponding binding position data. The data acquisition part is a conventional technical means for image processing in the prior art and is not the main innovative part of the present application, so it will not be described in detail here;

[0043] Step 13: Store the acquired data in the storage component. For the data storage process in the present application, that is, store the collected different types of data in different storage devices for easy classification and retrieval;

[0044] Step 2: Perform abnormal analysis of the binding position based on the texture image data of the binding position and the position data corresponding to the floss flower after binding;

[0045] In this embodiment, step 2 includes the following specific steps: Step 21, obtain the texture image data corresponding to all binding positions and the binding position data corresponding after binding;

[0046] Step 22, import the binding position data corresponding after binding obtained into the binding position outlier calculation formula to calculate the binding position outlier value. Among them, the binding position outlier calculation formula is: , where xi is the distance from the i-th actual binding point position to the corresponding standard binding point, m is the number of binding points, xz is the binding point safety offset distance, and in this formula, the binding offset distances of all binding points are comprehensively analyzed for binding position anomalies;

[0047] Step 23, obtain the texture image data corresponding to the binding position and the texture image data that the binding position needs to form, and import the texture image data corresponding to the obtained binding position and the texture image data that the binding position needs to form into the binding position image outlier calculation formula to calculate the binding position image outlier value. Among them, the binding position image outlier calculation formula is: , where a is the contour similarity weight, s() is the area of the image in the parentheses, piz is the contour image of the i-th binding position, piu is the standard contour image of the i-th binding position, is the intersection of the images, is the union of the images, Ni is the number of pixel points of the i-th binding position, zij is the pixel value of the j-th pixel point of the i-th binding position, zijm is the standard pixel value of the j-th pixel point of the i-th binding position. Here, it should be noted that the standard pixel value and the standard contour image are obtained from the product design image. Before each product is produced, there must be a product design image. In this formula, the damage and contour anomalies of the binding position during the binding process are comprehensively analyzed through the image contour and image pixel anomalies of the binding position;

[0048] Step 24, obtain the calculated binding position outlier value and the binding position image outlier value, and add them after weighting respectively to obtain the binding position anomaly analysis coefficient. In this step, the anomalies of the binding part during the binding process are comprehensively analyzed through the position, contour and pixel anomalies of the binding part;

[0049] Step 3, perform binding damage anomaly analysis based on the image data of the floss flower product after binding;

[0050] In this embodiment, step 3 includes the following specific steps: The binding damage anomaly analysis based on the image data of the floss flower product after binding includes the following specific steps:

[0051] Step 31, obtain the orientation angle data of the fluff on both sides of the binding thread when the product is placed vertically, and at the same time obtain the standard orientation angle of the fluff on both sides when the product is placed vertically;

[0052] Step 32: Import the obtained orientation angle data of the fluff on both sides of the binding thread and the standard orientation angle of the fluff on both sides when the product is placed vertically into the calculation formula for the binding failure anomaly analysis value. The calculation formula for the binding failure anomaly analysis value is as follows: , where M is the number of fluff on both sides of the binding thread, is the orientation angle of the c-th fluff passed by the binding thread when the product is placed vertically, is the standard orientation angle of the c-th fluff passed by when the product is placed vertically, Lc is the vertical distance from the middle of the c-th fluff to the binding thread, and Lm is the length of the product. This formula is used to analyze whether the squeezing effect of the binding thread destroys the positions of the fluff on both sides of the binding thread, resulting in the destruction of the original positions of the fluff on both sides of the binding thread, thereby affecting the product quality. At the same time, in order to perform different weight analyses on the fluff at different distances from the binding thread, because the farther the influence is transmitted, the greater the influence is, the vertical distance from the middle of the fluff to the binding thread is set as the weight of the fluff at different positions;

[0053] Step 4: Conduct a quality analysis of the fluff binding by integrating the binding position anomaly analysis result and the binding change anomaly analysis result;

[0054] In this embodiment, Step 4 includes the following specific steps: Step 41: Obtain the calculated binding position anomaly analysis coefficient and the binding failure anomaly analysis value, and substitute the obtained binding position anomaly analysis coefficient and the binding failure anomaly analysis value into the calculation formula for the binding quality analysis value. The calculation formula for the binding quality analysis value is as follows: , where Zw is the binding position anomaly analysis coefficient, and exp() is the exponential power of the natural constant e;

[0055] Step 42: Compare the calculated binding quality analysis value with the set binding quality threshold. If the calculated binding quality analysis value is greater than or equal to the set binding quality threshold, it is determined that the fluff product binding is qualified; if the obtained binding quality analysis value is less than the set binding quality threshold, it is determined that the fluff product binding is unqualified.

[0056] Secondly, it should be noted that in this embodiment, the acquisition method of relevant setting parameters in this embodiment (such as the binding quality threshold in step 4, the contour similarity weight, the binding position anomaly weight, and the binding position image anomaly weight in step 2, etc.) is obtained through experiments by those skilled in the art. The preferred acquisition method is as follows: Obtain the image data of at least 500 assembled floss flower products to be detected after binding, the texture image data of the binding position, and the position data corresponding to the floss flower after binding. Corresponding to step 2 and step 3, finally substitute them into the binding quality analysis value calculation formula to calculate the binding quality analysis value. At the same time, invite experts to judge the qualification of these floss flower products to be detected, and substitute the qualification judgment result and the binding quality analysis value into the fitting software to obtain the value of the relevant setting parameters that meets the maximum judgment accuracy rate.

[0057] Finally, the advantages of this embodiment are described here. This embodiment performs binding position anomaly analysis based on the texture image data of the binding position and the position data corresponding to the floss flower after binding, and then performs binding damage anomaly analysis based on the image data of the floss flower product after binding. The binding quality of the floss flower is analyzed by comprehensively considering the binding position anomaly analysis result and the binding change anomaly analysis result. This application comprehensively analyzes the texture image and position accuracy of the binding position after binding, accurately and efficiently evaluates the binding quality, and takes into account the damage analysis of the product appearance during the binding process while evaluating the binding quality, thereby comprehensively analyzing the binding quality of the product.

[0058] Embodiment 2

[0059] As Figure 4 shown, this embodiment provides a digital-based floss flower product quality detection and evaluation system, which is implemented based on the above-mentioned digital-based floss flower product quality detection and evaluation method. It specifically includes: a data acquisition module for acquiring the image data of the floss flower product to be detected, and at the same time acquiring the texture image data of the binding position and the position data corresponding to the floss flower after binding; a position anomaly analysis module for performing binding position anomaly analysis based on the texture image data of the binding position and the position data corresponding to the floss flower after binding; a damage anomaly analysis module for performing binding damage anomaly analysis based on the image data of the floss flower product after binding; a binding quality analysis module for comprehensively analyzing the binding quality of the floss flower by combining the binding position anomaly analysis result and the binding change anomaly analysis result; it may also include a control module, and the control module is used to control the operation of the data acquisition module, the position anomaly analysis module, the damage anomaly analysis module, and the binding quality analysis module. At the same time, it should be noted that Figure 4 the arrow direction in represents the data transmission direction.

[0060] Embodiment 3

[0061] This embodiment provides an electronic device, including: a processor and a memory, wherein, a computer program that can be called by the processor is stored in the memory;

[0062] By calling the computer program stored in the memory, the processor executes the above-mentioned method for detecting and evaluating the quality of digital floss flower products.

[0063] This electronic device may have relatively large differences due to different configurations or performances, and can include one or more processors and one or more memories. Among them, at least one computer program is stored in the memory, and this computer program is loaded and executed by the processor to implement the method for detecting and evaluating the quality of digital floss flower products provided by the above method embodiment. This electronic device can also include other components for realizing the functions of the device. For example, this electronic device can also have components such as wired or wireless network interfaces and input / output interfaces for inputting and outputting data. This embodiment will not be elaborated here.

[0064] Embodiment 4

[0065] This embodiment provides a computer-readable storage medium, on which a rewritable computer program is stored;

[0066] When the computer program runs on a computer device, it enables the computer device to execute the above-mentioned method for detecting and evaluating the quality of digital floss flower products.

[0067] For example, the computer-readable storage medium can be a read-only memory, a random access memory, a compact disc read-only memory, magnetic tapes, floppy disks, and optical data storage devices, etc.

[0068] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions according to the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that the computer can access or a data storage device such as a server or a data center that includes one or more collections of available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0069] The term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device.

[0070] In addition, the parts of the above technical solutions provided in the embodiments of the present application that are consistent with the corresponding technical solutions in the prior art in terms of implementation principles are not described in detail to avoid excessive elaboration.

[0071] As described above, the specific embodiments further elaborate on the purpose, technical solutions, and beneficial effects of the present invention. It should be understood that the above description is only the specific embodiments of the present invention and is not used to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A digital-based velvet flower product quality detection and evaluation method, characterized in that: It includes the following specific steps: Acquire the image data of the velvet flower product to be inspected, and simultaneously acquire the texture image data of the binding position and the position data corresponding to the velvet flower after binding; Perform binding position abnormality analysis based on the binding position texture image data and the position data corresponding to the velvet flower after binding; The specific steps include: Acquire all texture image data corresponding to the binding positions and the corresponding binding position data after binding; The obtained binding position data corresponding to the binding is imported into the binding position abnormal value calculation formula to calculate the binding position abnormal value, wherein the binding position abnormal value calculation formula is: , where xi is the distance from the i-th actual binding point to the corresponding standard binding point, m is the number of binding points, and xz is the safe offset distance of the binding point; Acquire texture image data corresponding to the binding position and texture image data required to be formed at the binding position, and import the acquired texture image data corresponding to the binding position and texture image data required to be formed at the binding position into a binding position image abnormality value calculation formula to calculate the binding position image abnormality value; Among them, the calculation formula of the abnormal value of the binding position image is: , where a is the contour similarity weight, s() is the area of ​​the image in brackets, piz is the contour image of the i-th binding position, and piu is the standard contour image of the i-th binding position. is the intersection of the images, is the union of the images, Ni is the number of pixels at the i-th binding position, zij is the pixel value of the j-th pixel at the i-th binding position, and zijm is the standard pixel value of the j-th pixel at the i-th binding position; Obtain the calculated binding position abnormal value and binding position image abnormal value, weight them respectively and then add them to obtain the binding position abnormality analysis coefficient; Binding damage anomaly analysis is performed based on the image data of the bound velvet flower product; the specific steps include: importing the acquired orientation angle data of the velvet on both sides of the binding line when the product is placed vertically and the standard orientation angle of the velvet on both sides when the product is placed vertically into the binding damage anomaly analysis value calculation formula to calculate the binding damage anomaly analysis value, wherein the binding damage anomaly analysis value calculation formula is: , where M is the number of hairs on both sides of the binding line, is the orientation angle of the cth pile through which the binding line passes when the product is placed vertically, is the standard orientation angle of the cth fluff when the product is placed vertically, Lc is the vertical distance from the middle of the cth fluff to the binding line, and Lm is the length of the product; The quality analysis of velvet flower binding is carried out based on the analysis results of abnormal binding position and abnormal binding damage.

2. A digital-based velvet flower product quality detection and evaluation method as claimed in claim 1, characterized in that: The comprehensive binding position abnormality analysis result and the binding damage abnormality analysis result for velvet flower binding quality analysis include the following specific contents: obtaining the calculated binding position abnormality analysis coefficient and the binding damage abnormality analysis value, substituting the obtained binding position abnormality analysis coefficient and the binding damage abnormality analysis value into the binding quality analysis value calculation formula to calculate the binding quality analysis value, wherein the binding quality analysis value calculation formula is: , where Zw is the binding position abnormality analysis coefficient, and exp() is the power of the natural constant e; The calculated binding quality analysis value is compared with the set binding quality threshold. If the calculated binding quality analysis value is greater than or equal to the set binding quality threshold, the velvet flower product is judged to be qualified in binding. If the obtained binding quality analysis value is less than the set binding quality threshold, the velvet flower product is judged to be unqualified in binding.

3. A digital-based velvet flower product quality detection and evaluation method as claimed in claim 2, characterized in that: The specific contents of acquiring the image data of the velvet flower product to be detected and acquiring the binding position texture image data and the binding position data are as follows: Step 11, obtaining image data of the velvet flower product to be inspected after binding, obtaining image data of the velvet on both sides of the binding line from the image, and obtaining orientation angle data of the velvet on both sides of the binding line when the product is placed vertically; Step 12: acquiring texture image data corresponding to the binding position and corresponding binding position data after binding from the image data of the velvet flower product; Step 13: Store the acquired data in the storage component.

4. A digital velvet product quality detection and evaluation system, which is implemented based on the digital velvet product quality detection and evaluation method according to any one of claims 1 to 3, and is characterized in that: It specifically includes a data acquisition module, a position anomaly analysis module, a damage anomaly analysis module and a binding quality analysis module; wherein the data acquisition module is used to acquire the image data of the velvet flower product that needs to be detected, and at the same time acquire the binding position texture image data and the position data corresponding to the velvet flower after binding; the position anomaly analysis module performs a binding position anomaly analysis based on the binding position texture image data and the position data corresponding to the velvet flower after binding; the damage anomaly analysis module performs a binding damage anomaly analysis based on the image data of the velvet flower product after binding; and the binding quality analysis module is used to comprehensively analyze the binding position anomaly analysis results and the binding damage anomaly analysis results to perform velvet flower binding quality analysis.

5. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; It is characterized in that the processor executes the digital-based velvet flower product quality detection and evaluation method as described in any one of claims 1 to 3 by calling the computer program stored in the memory.

6. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer is caused to execute a digital-based velvet flower product quality detection and evaluation method as described in any one of claims 1 to 3.

Images