Methods, apparatus, equipment and storage media for determining the visual quality of pile

Abstract

This application relates to a method, apparatus, device, and storage medium for determining the visual quality of leather suede, and pertains to the field of material quality testing technology. The method includes: acquiring a target length and uniformity information of the leather suede, where the target length is the length of the leather suede and the uniformity information reflects the degree of uniformity of the leather suede. Based on the target length and uniformity information, quality information is determined, which reflects the visual quality of the leather suede. Therefore, by determining the visual quality of leather suede through two dimensions—suede length and suede uniformity—the accuracy of determining the visual quality of leather suede can be improved.

Description

Technical Field

[0001] This application relates to the field of material quality testing technology, specifically to a method, apparatus, equipment, and storage medium for determining the visual quality of velvet fibers. Background Technology

[0002] With the development of society and the economy, vehicles not only need to meet people's basic travel needs, but also their demands for driving and riding comfort. Currently, suede-like leather materials are increasingly widely used in automotive interiors, and the physical properties of leather are directly related to user experience. The visual quality of the leather suede is an important physical property parameter, as it affects the user's visual experience.

[0003] Currently, staff primarily assess the visual quality of leather suede based on subjective perception. However, this may reduce the accuracy of determining the visual quality of leather suede. Summary of the Invention

[0004] This application provides a method, apparatus, device, and storage medium for determining the visual quality of fur, to at least solve the technical problem of reduced accuracy in determining the visual quality of fur in related technologies. The technical solution of this application is as follows:

[0005] According to a first aspect of this application, a method for determining the visual quality of leather suede is provided. The method includes: acquiring a target length of leather suede and uniformity information of the leather suede, wherein the target length is the length of the leather suede, and the uniformity information reflects the degree of uniformity of the leather suede. Based on the target length and uniformity information, quality information is determined, which reflects the visual quality of the leather suede.

[0006] Based on the aforementioned technical means, the server in this application can determine the visual quality of leather suede based on two dimensions: suede length and nap uniformity, rather than through subjective visual evaluation, thereby improving the accuracy of determining the visual quality of leather suede.

[0007] In one possible implementation, the leather suede includes: compressed suede and uncompressed suede. The aforementioned "obtaining the target length of the leather suede" includes: acquiring a first suede image, the first suede image including: a first test area and a second test area, the first test area including compressed suede and the second test area including uncompressed suede. Based on the first suede image, determining a first length and a second length, the first length being the length of the leather suede in the first test area, which is less than a preset length threshold, and the second length being the length of the leather suede in the second test area. Based on the first length and the second length, determining a target length, the target length being the difference between the first length and the second length.

[0008] Based on the above-mentioned technical means, the server in this application can use microscope images to measure the length of the fibers. Since the height of the fibers after pressure is negligible, the fiber length can be calculated by combining the length of the fibers before and after pressure, which can improve the accuracy of the fiber length measurement.

[0009] In one possible implementation, the above-mentioned "obtaining uniform information of leather suede" includes: acquiring a second suede image, the second suede image including a second test region, the magnification of the second suede image being less than the magnification of the first suede image. The second test region is divided into multiple sub-regions, the multiple sub-regions having the same area, and each sub-region having a different density of leather suede. Based on the density of leather suede in each sub-region, a protrusion area is determined for each sub-region, thus determining multiple protrusion areas, where each protrusion area is the area in the sub-region where the density of leather suede is greater than a preset density threshold. From the multiple protrusion areas, a first area and a second area are determined, the first area being the largest among the multiple protrusion areas, and the second area being the smallest among the multiple protrusion areas. Based on the first area and the second area, uniform information is determined, the uniform information being the ratio of the first area to the second area.

[0010] Based on the aforementioned technical means, the server in this application can utilize microscope images to determine the protrusion area of ​​each sub-region, and obtain the uniformity of the leather nap by using the maximum and minimum protrusion areas. Thus, by calculating objective values, the accuracy of the uniformity information of the leather nap can be improved.

[0011] In one possible implementation, the method for determining the visual quality of the fuzz further includes: determining the area of ​​each sub-region. The aforementioned "determining uniformity information based on the first area and the second area" includes: determining a first ratio based on the first area and the area; determining a second ratio based on the second area and the area; and determining uniformity information based on the first ratio and the second ratio, wherein the uniformity information is specifically the ratio of the first ratio to the second ratio.

[0012] Based on the aforementioned technical means, in this application, the server determines the proportion of the protruding area in the sub-region, and obtains the uniformity of the leather nap based on the maximum and minimum proportions of the protruding area.

[0013] In one possible implementation, the aforementioned "determining quality information based on target length and uniformity information" includes: determining a pile length grade based on the target length and a first correspondence, where the first correspondence is the relationship between the target length and the pile length grade, and the pile length grade reflects the degree of influence of the target length on the quality information; determining a uniformity grade based on uniformity information and a second correspondence, where the second correspondence is the relationship between uniformity information and the uniformity grade, and the uniformity grade reflects the degree of influence of the uniformity information on the quality information; and determining the quality information based on the pile length grade and the uniformity grade.

[0014] According to the above technical solution, this application can first determine the length and uniformity of the leather nap separately, and then determine the comprehensive information based on the length and uniformity of the leather nap. By determining the visual quality of the leather nap through two dimensions—nailing length and nap uniformity—the accuracy of determining the visual quality of the leather nap is improved.

[0015] According to a second aspect of this application, an apparatus for determining the visual quality of leather suede is provided. The apparatus includes: an acquisition unit for acquiring a target length of leather suede and uniformity information of the leather suede, wherein the target length is the length of the leather suede, and the uniformity information reflects the degree of uniformity of the leather suede; and a processing unit for determining quality information based on the target length and uniformity information, wherein the quality information reflects the visual quality of the leather suede.

[0016] In one possible implementation, the acquisition unit is specifically used to acquire a first fluff image, which includes a first test area and a second test area. The first test area includes fluff after pressure is applied, and the second test area includes fluff without pressure. The processing unit is specifically used to determine a first length and a second length based on the first fluff image. The first length is the length of the leather fluff in the first test area, and the first length is less than a preset length threshold. The second length is the length of the leather fluff in the second test area. The processing unit is specifically used to determine a target length based on the first length and the second length. The target length is the difference between the first length and the second length.

[0017] In one possible implementation, the acquisition unit is specifically used to acquire a second fuzz image, the second fuzz image including a second test area, and the magnification of the second fuzz image being less than the magnification of the first fuzz image. The processing unit is specifically used to divide the second test area into multiple sub-regions, the multiple sub-regions having the same area, and each sub-region having a different density of leather fuzz. The processing unit is specifically used to determine the protrusion area of ​​each sub-region based on the density of leather fuzz in each sub-region, thereby determining multiple protrusion areas, where each protrusion area is the area in the sub-region where the density of leather fuzz is greater than a preset density threshold. The processing unit is specifically used to determine a first area and a second area from the multiple protrusion areas, where the first area is the largest among the multiple protrusion areas, and the second area is the smallest among the multiple protrusion areas. The processing unit is specifically used to determine uniformity information based on the first area and the second area, where the uniformity information is the ratio of the first area to the second area.

[0018] In one possible implementation, the processing unit is further configured to determine the area of ​​each sub-region. Specifically, the processing unit is configured to determine a first ratio based on a first area and the area of ​​the sub-region. Specifically, the processing unit is configured to determine a second ratio based on a second area and the area of ​​the sub-region. Specifically, the processing unit is configured to determine uniformity information based on the first ratio and the second ratio, wherein the uniformity information is specifically the ratio of the first ratio to the second ratio.

[0019] In one possible implementation, the processing unit is specifically configured to determine a pile length grade based on a target length and a first correspondence, wherein the first correspondence is the relationship between the target length and the pile length grade, and the pile length grade reflects the degree of influence of the target length on the quality information. The processing unit is also specifically configured to determine a uniformity grade based on uniformity information and a second correspondence, wherein the second correspondence is the relationship between uniformity information and the uniformity grade, and the uniformity grade reflects the degree of influence of the uniformity information on the quality information. Finally, the processing unit is specifically configured to determine quality information based on the pile length grade and the uniformity grade.

[0020] According to a third aspect provided in this application, an electronic device is provided, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute instructions to implement the method of the first aspect described above and any possible implementation thereof.

[0021] According to a fourth aspect provided in this application, a computer-readable storage medium is provided that, when the instructions in the computer-readable storage medium are executed by a processor of an electronic device, enables the electronic device to perform the methods described in the first aspect and any possible implementation thereof.

[0022] According to the fifth aspect provided in this application, a computer program product is provided, the computer program product including computer instructions, which, when executed on an electronic device, cause the electronic device to perform the method described in the first aspect and any possible implementation thereof.

[0023] Therefore, the above-mentioned technical features of this application have the following beneficial effects:

[0024] (1) The visual quality of leather suede can be determined by two dimensions: suede length and nap uniformity, rather than by subjective visual assessment, which can improve the accuracy of determining the visual quality of leather suede.

[0025] (2) Microscopic images can be used to measure the length of the fibers. Since the height of the fibers after pressure is negligible, the fiber length can be calculated by the length of the fibers before and after pressure, which can improve the accuracy of the fiber length.

[0026] (3) Microscopic images can be used to determine the protrusion area of ​​each sub-region, and the uniformity of the leather nap can be obtained by using the maximum and minimum protrusion areas. The proportion of protrusion area in each sub-region can also be determined, and the uniformity of the leather nap can be obtained based on the maximum and minimum proportions of protrusion areas. In this way, by calculating objective values, the accuracy of the uniformity information of the leather nap can be improved.

[0027] It should be noted that the technical effects of any of the implementation methods in aspects two through five can be found in the technical effects of the corresponding implementation methods in aspect one, and will not be repeated here.

[0028] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0029] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application, and do not constitute an undue limitation of this application.

[0030] Figure 1 This is a schematic diagram illustrating the structure of a system for determining the visual quality of fluff according to an exemplary embodiment;

[0031] Figure 2 This is a flowchart illustrating a method for determining the visual quality of fluff according to an exemplary embodiment;

[0032] Figure 3 This is a flowchart illustrating another method for determining the visual quality of fluff according to an exemplary embodiment;

[0033] Figure 4 This is a schematic diagram illustrating a leather suede before and after folding, according to an exemplary embodiment;

[0034] Figure 5 This is a schematic diagram illustrating a first fluff image according to an exemplary embodiment;

[0035] Figure 6 This is a top view schematic diagram illustrating a first test area and a second test area according to an exemplary embodiment;

[0036] Figure 7 This is a front view schematic diagram of a first test area and a second test area according to an exemplary embodiment;

[0037] Figure 8 This is a flowchart illustrating yet another method for determining the visual quality of fluff, according to an exemplary embodiment;

[0038] Figure 9 This is a schematic diagram of multiple sub-regions in a second villous image according to an exemplary embodiment;

[0039] Figure 10 This is a schematic diagram illustrating the protrusion area of ​​each of a plurality of sub-regions according to an exemplary embodiment;

[0040] Figure 11 This is a flowchart illustrating yet another method for determining the visual quality of fluff, according to an exemplary embodiment;

[0041] Figure 12 This is a block diagram illustrating a device for determining the visual quality of fluff according to an exemplary embodiment;

[0042] Figure 13 This is a block diagram illustrating an electronic device according to an exemplary embodiment. Detailed Implementation

[0043] To enable those skilled in the art to better understand the technical solutions of this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0044] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0045] Before providing a detailed description of the method for determining the visual quality of fluff in the embodiments of this application, the implementation environment and application scenarios of the embodiments of this application will be introduced first.

[0046] With the development of society and the economy, vehicles not only need to meet people's basic travel needs, but also their demands for driving and riding comfort. Currently, suede-like leather materials are increasingly widely used in automotive interiors, and the physical properties of leather are directly related to user experience. The visual quality of the leather suede is an important physical property parameter, as it affects the user's visual experience.

[0047] Currently, staff primarily assess the visual quality of leather suede based on subjective feelings. However, this may reduce the accuracy of determining the visual quality of leather suede.

[0048] To address the aforementioned problems, this application provides a method for determining the visual quality of leather suede. The method includes: a server acquiring a target length and uniformity information of the leather suede, where the target length is the length of the leather suede and the uniformity information reflects the evenness of the leather suede. Then, the server determines quality information based on the target length and uniformity information, which reflects the visual quality of the leather suede. In this way, the server can determine the visual quality of the leather suede from two dimensions: suede length and suede uniformity, thereby improving the accuracy of determining the visual quality of the leather suede.

[0049] The implementation environment of the embodiments of this application is described below.

[0050] Figure 1 This is a schematic diagram illustrating the structure of a system for determining the visual quality of fluff according to an exemplary embodiment. Figure 1 As shown, the system for determining the visual quality of velvet includes a microscope 101 and a server 102. The microscope 101 is connected to the server 102.

[0051] The microscope 101 can be used to place leather fibers and acquire images of the fibers. The microscope 101 can also be used to send the fibers images to the server 102.

[0052] It should be noted that, in the embodiments of this application, the measurement accuracy of the microscope can be greater than or equal to 1 micrometer.

[0053] Server 102 can communicate with microscope 101. For example, server 102 can acquire images of the velvet structure from microscope 101. Furthermore, server 102 can process the velvet images.

[0054] It should be noted that the server can be a single physical server, or a server cluster consisting of multiple servers. Alternatively, the server cluster can be a distributed cluster. Alternatively, the server can be a cloud server. This application does not limit the specific implementation of the server.

[0055] For ease of understanding, the method for determining the visual quality of the pile provided in this application will be described in detail below with reference to the accompanying drawings. Figure 2 This is a flowchart illustrating a method for determining the visual quality of fluff according to an exemplary embodiment, such as... Figure 2 As shown, the method includes the following steps:

[0056] S201, The server obtains the target length of the leather suede.

[0057] The target length is the length of the leather suede.

[0058] In one possible implementation, the server may receive a first input instruction for inputting the target length of the leather suede. In response to the first input instruction, the server may obtain the target length of the leather suede.

[0059] It should be noted that, in the embodiments of this application, the leather can be imitation suede.

[0060] S202, The server obtains uniformity information of the leather suede.

[0061] Among them, uniformity information is used to reflect the uniformity of the leather nap.

[0062] In one possible implementation, the server can receive a second input instruction for inputting information about the uniformity of the leather nap. In response to the second input instruction, the server can obtain the uniformity of the leather nap.

[0063] S203. The server determines the quality information based on the target length and uniformity information.

[0064] Among them, quality information is used to reflect the visual quality of leather and suede.

[0065] In one possible implementation, the server can determine the pile length grade based on the target length and the first correspondence, whereby the pile length grade is used to reflect the degree of influence of the target length on the quality information.

[0066] In one possible design, the first correspondence is the correspondence between the target length and the pile length grade.

[0067] For example, as shown in Table 1, a first correspondence is illustrated. This first correspondence includes: target length and pile length grade.

[0068] Table 1 First Correspondence Relationship

[0069] Serial Number Target length (micrometers) Length of pile 1 L2-L3 Level 1 2 L1-L2 Level 2 3 Less than L1 or greater than L3 Level 3

[0070] In other words, if the target length is within the range L2-L3, the pile length grade is level 1. If the target length is within the range L1-L2, the pile length grade is level 2. If the target length is less than L1 or greater than L3, the pile length grade is level 3.

[0071] It should be noted that in the embodiments of this application, L1, L2, and L3 are not limited. For example, L1 can be 100, L2 can be 500, and L3 can be 1000. Another example is that L1 can be 200, L2 can be 600, and L3 can be 1000. Yet another example is that L1 can be 100, L2 can be 600, and L3 can be 1100.

[0072] In this embodiment of the application, the server can determine the uniformity level based on the uniformity information and the second correspondence. The uniformity level is used to reflect the degree of influence of the uniformity information on the quality information.

[0073] In one possible design, the second correspondence is the correspondence between uniform information and uniform level.

[0074] For example, as shown in Table 2, a second correspondence is illustrated. This second correspondence includes: uniform information and uniform level.

[0075] Table 2 Second Correspondence

[0076] Serial Number Uniform information Uniform grade 1 B1-B2 Level 1 2 B2-B3 Level 2 3 Greater than B3 Level 3

[0077] In other words, when the uniform information is within the range B1-B2, the uniformity level is 1. When the uniform information is within the range B2-B3, the uniformity level is 2. When the uniform information is greater than B3, the uniformity level is 3.

[0078] It should be noted that in the embodiments of this application, B1, B2, and B3 are not limited. Typically, B1 is 1. For example, B1 can be 1, B2 can be 2, and B3 can be 3. Another example is that B1 can be 1, B2 can be 1.5, and B3 can be 2.5. Yet another example is that B1 can be 1, B2 can be 1.5, and B3 can be 3.

[0079] Then, the server can determine the quality information based on the pile length grade and uniformity grade.

[0080] In one possible design, the quality information can specifically be a quality level.

[0081] For example, as shown in Table 3, Table 3 illustrates the relationship between pile length grade, uniformity grade, and quality information. Table 3 may include: pile length grade, uniformity grade, and quality information.

[0082] Table 3 Relationship between pile length grade, uniformity grade, and quality information

[0083] Serial Number Length of pile Uniform grade Quality Information 1 Level 1 Level 1 Level 1 2 Level 1 or Level 2 Level 2 or Level 1 Level 2 3 Level 2 Level 2 Level 3 4 Level 2 or Level 3 Level 3 or Level 2 Level 4 5 Level 3 Level 3 Level 5

[0084] In other words, when the pile length grade is 1 and the uniformity grade is 1, the quality information is grade 1. When the pile length grade is 1 and the uniformity grade is 2, the quality information is grade 2. When the pile length grade is 2 and the uniformity grade is 1, the quality information is grade 2. When the pile length grade is 2 and the uniformity grade is 2, the quality information is grade 3. In the embodiments of this application, the descriptions of serial numbers 4 and 5 can be referred to the descriptions of serial numbers 1 to 3, and will not be repeated here.

[0085] In this way, the server can determine the pile length grade based on the target length and the first correspondence. The server can also determine the uniformity grade based on the uniformity information and the second correspondence. Then, the server can determine the quality information based on the pile length grade and the uniformity grade. Thus, by comprehensively determining the visual quality of the leather pile based on both pile length and uniformity, the server can improve the accuracy of determining the visual quality of the leather pile.

[0086] Understandably, the server can acquire the target length and uniformity information of the leather suede. The target length refers to the length of the leather suede, and the uniformity information reflects the evenness of the suede. Then, the server can determine quality information based on the target length and uniformity information, which reflects the visual quality of the leather suede. In this way, the server can determine the visual quality of the leather suede from two dimensions: suede length and suede uniformity, thus improving the accuracy of determining the visual quality of the leather suede.

[0087] In some embodiments, to improve the accuracy of the pile length, such as Figure 3 As shown, the leather nap may include: nap after compression and nap without compression. The method for obtaining the target length of the leather nap (S201) may include the following steps:

[0088] S301, The server obtains the first image of the fluff.

[0089] The first villous image includes: a first region to be tested and a second region to be tested.

[0090] In one possible implementation, the microscope can acquire a first villus image and send it to a server. The server can then receive the first villus image from the microscope.

[0091] It should be noted that, in this embodiment, before the microscope acquires the first image of the leather lint, the operator can fold the leather lint in half to ensure that the glass slide covers both the first and second areas to be tested. The operator can adjust the microscope's field of view to the intersection between the first and second areas to be tested and adjust the microscope's magnification to a first preset magnification to ensure that the field of view includes both the first and second areas to be tested. In this embodiment, the first preset magnification can be greater than 10x.

[0092] For example, such as Figure 4 The diagram illustrates a piece of leather suede before and after folding. Solid line area 400 represents the leather suede before folding, and solid line area 405 represents the leather suede after folding. Dashed line area 401 represents the first area to be measured, dashed line area 402 represents the second area to be measured, solid line area 403 represents transparent tape, long dashed line 404 represents the fold line, and thickened dashed line area 406 represents a glass sheet.

[0093] In this embodiment of the application, the server can mark the highest and lowest points of the leather fur in the first fur image to determine the first test area and the second test area.

[0094] The first test area includes the fibers after pressure is applied, and the second test area includes the fibers without pressure.

[0095] It should be noted that, in this embodiment, the method of applying pressure to the leather fibers is not limited. The leather fibers in the first test area and the leather fibers in the second test area are fibers from the same leather. The density of the leather fibers in the first test area and the second test area is greater than a preset density threshold, and individual longer fibers are not considered.

[0096] For example, such as Figure 5 As shown, Figure 5A schematic diagram of a first fuzz image is shown. The first fuzz image includes: a first test area 501 and a second test area 502.

[0097] S302. The server determines a first length and a second length based on the first fluff image.

[0098] Wherein, the first length is the length of the leather suede in the first test area, and the second length is the length of the leather suede in the second test area.

[0099] In one possible design, the first length is less than a preset length threshold.

[0100] It should be noted that the preset length threshold is not limited in this embodiment. For example, the preset length threshold can be 0.5 micrometers. Another example is that the preset length threshold can be 1 micrometer. Yet another example is that the preset length threshold can be 0.1 micrometers.

[0101] In one possible implementation, the server can determine the length of the leather suede in a first test region of the first suede image, and determine the length of the leather suede in a second test region of the first suede image. The server uses the length of the leather suede in the first test region as a first length, and the length of the leather suede in the second test region as a second length.

[0102] S303. The server determines the target length based on the first length and the second length.

[0103] The target length is the difference between the first length and the second length.

[0104] In one possible implementation, the server can obtain the difference between the first length and the second length based on the first length and the second length. The server can then use the first length and the second length as the target length.

[0105] In another possible implementation, the server can annotate the highest point of the leather suede in the first test area within the first suede image, obtaining a first annotation. The server can then annotate the highest point of the leather suede in the second test area within the first suede image, obtaining a second annotation. The server can then determine the height of the first annotation and the height of the second annotation within the first suede image. Based on the heights of the first and second annotations in the first suede image, the server can determine the target length.

[0106] For example, in combination Figure 5The server can draw a horizontal line on the flat surface of the first test area as the first marker (i.e., the bottom edge of the first test area 501), and draw a horizontal line at the highest point of the pile in the second test area as the second marker (i.e., the top edge of the second test area 502). Since the leather pile in the first test area is the pile after pressure, its first length is less than a preset length threshold and can be ignored. Therefore, the first marker can be taken as the lowest point of the leather pile. This improves the accuracy of the pile length.

[0107] Understandably, the server can acquire a first image of the leather fibers, which includes a first test area and a second test area. The first test area includes the fibers after pressure is applied, and the second test area includes the fibers without pressure. Based on the first image, the server can determine a first length and a second length. The first length is the length of the leather fibers in the first test area, which is less than a preset length threshold. The second length is the length of the leather fibers in the second test area. Then, the server can determine a target length based on the first and second lengths, which is the difference between the first and second lengths. In this way, the server can use a microscope to measure the fiber length. Since the height of the fibers after pressure is negligible, the fiber length can be calculated by combining the lengths of the fibers without and after pressure, thus improving the accuracy of the fiber length measurement.

[0108] The method of applying pressure to the leather suede in S301 is described below with reference to a specific embodiment. Before the server acquires the first suede image, the operator can perform sample surface treatment and sample preparation on the leather suede. The sample surface treatment and sample preparation include the following steps: Step 1-Step 4.

[0109] Step 1: Staff can place the leather suede in a constant temperature and humidity environment for a preset time.

[0110] It should be noted that in this embodiment, the ambient temperature range can be [21, 25] degrees Celsius, and the relative humidity can be [40%, 60%]. The preset duration is greater than or equal to 16 hours to ensure that the sample to be tested recovers to the standard state. Before placing the leather suede in a constant temperature and humidity environment, the operator can also gently press the leather suede with their palm and slide it back and forth evenly once to ensure that the leather suede is in a relatively uniform state and to eliminate the influence of factors such as deformation caused by force during transportation.

[0111] Step 2: Staff can select the first test area and the second test area.

[0112] It should be noted that, in the embodiments of this application, the first test area and the second test area can be adjacent areas, so as to facilitate subsequent observation under a microscope.

[0113] Step 3: Staff can stick transparent tape on the first area to be tested and place a weight with a preset load on the transparent tape.

[0114] In this embodiment of the application, the staff can place a weight with a preset load on a transparent tape for a second preset time.

[0115] It should be noted that, in this embodiment, the transparent tape can have an adhesion strength index greater than or equal to 0.47 N / 100 mm, and the test substrate for this adhesion strength index is a stainless steel plate. The preset load range can be [1.8, 2.2] kPa. The second preset time is greater than 5 minutes to ensure that the leather suede in the first test area is fully compressed and flattened under the combined action of the tape and the load.

[0116] For example, such as Figure 6 As shown, this diagram presents a top view of a first and a second test area. The solid line area 600 represents leather suede, the dashed line area 601 represents the first test area, the dashed line area 602 represents the second test area, the solid line area 603 represents transparent tape, and the filled area 604 represents weights. Figure 7 As shown, it illustrates a frontal view of a first test area and a second test area. The solid line area 700 represents leather suede, the bold solid line 701 represents the first test area, the bold dashed line 702 represents the second test area, the solid line area 703 represents transparent tape, and the filled area 704 represents weights.

[0117] Step 4: Staff can remove the preset load weights.

[0118] In this way, the first test area with tape and the second test area adjacent to the first test area without tape can be retained for subsequent microscopic observation and comparison.

[0119] In some embodiments, to improve the accuracy of the uniformity information of the fibers, such as Figure 8 As shown, the method for obtaining uniform information of leather nap (S202) may include the following steps:

[0120] S801, The server obtains the second fluff image.

[0121] The second velvet image includes a second region to be tested, and the magnification of the second velvet image is less than that of the first velvet image.

[0122] In one possible implementation, the microscope can acquire a second villus image. The microscope can send the second villus image to a server. The server can receive the second villus image from the microscope to acquire the second villus image.

[0123] It should be noted that, in this embodiment, the operator can adjust the microscope's field of view to the second area to be tested and adjust the microscope's magnification to a second preset magnification to ensure that the field of view includes a relatively long distance of the second area to be tested. In this embodiment, the second preset magnification can be less than 10x.

[0124] S802. The server divides the second test area into multiple sub-regions.

[0125] Among them, multiple sub-regions have the same area, but the density of leather fur varies in each sub-region.

[0126] In one possible implementation, the server can mark the highest and lowest points of the leather suede in the second suede image to determine a second test region. This second test region includes the area between the highest and lowest points of the leather suede in the second suede image. The server can then divide this second test region into multiple sub-regions.

[0127] For example, such as Figure 9 The diagram illustrates a schematic representation of multiple sub-regions in a second velvet image. The second test region 900 comprises multiple sub-regions. If there are five sub-regions, they are: sub-region 901, sub-region 902, sub-region 903, sub-region 904, and sub-region 905.

[0128] S803. The server determines the protrusion area of ​​each sub-region based on the density of the leather suede in each sub-region, thereby determining multiple protrusion areas.

[0129] The protrusion area is the area in the sub-region where the density of leather fur is greater than a preset density threshold.

[0130] In one possible implementation, for each sub-region, the server can obtain the density of the leather suede in the sub-region. The server can determine the area in the sub-region where the density of the leather suede is greater than a preset density threshold. The server can use the area where the density of the leather suede is greater than the preset density threshold as the protrusion area of ​​the sub-region.

[0131] For example, in combination Figure 9 ,like Figure 10As shown, this diagram illustrates the protrusion area of ​​each of multiple sub-regions. Specifically, the protrusion area of ​​sub-region 901 is the area of ​​closed region 1001, the protrusion area of ​​sub-region 902 is the area of ​​closed region 1002, the protrusion area of ​​sub-region 903 is the area of ​​closed region 1003, the protrusion area of ​​sub-region 904 is the area of ​​closed region 1004, and the protrusion area of ​​sub-region 905 is the area of ​​closed region 1005.

[0132] S804, The server determines the first area and the second area from multiple protrusion areas.

[0133] Among them, the first area is the largest area among the multiple protrusion areas, and the second area is the smallest area among the multiple protrusion areas.

[0134] In one possible implementation, the server can determine the largest area among multiple protrusion areas and the smallest area among multiple protrusion areas. The server can use the largest area among multiple protrusion areas as the first area and the smallest area among multiple protrusion areas as the second area.

[0135] S805, The server determines uniformity information based on the first area and the second area.

[0136] The uniformity information is the ratio of the first area to the second area.

[0137] In one possible implementation, the server can determine the ratio of the first area to the second area based on the first area and the second area. The server can then use this ratio as uniformity information.

[0138] In this embodiment of the application, before the server determines the uniformity information based on the first area and the second area, the server can determine the area of ​​each sub-region.

[0139] In another possible implementation, the server can determine a first ratio based on a first area and a region area. The server can then determine a second ratio based on a second area and a region area. Afterward, the server can determine uniformity information, specifically the ratio of the first ratio to the second ratio, based on the first and second ratios.

[0140] It should be noted that in the embodiments of this application, each of the multiple sub-regions has the same area, so the ratio of the first ratio to the second ratio is equal to the ratio of the first area to the second area.

[0141] In some embodiments, for each sub-region, the server can determine a target ratio based on the region area and the protrusion area to determine multiple target ratios, with one target ratio corresponding to one sub-region. The server can then determine the maximum and minimum ratios from the multiple target ratios. Based on the maximum and minimum ratios, the server can determine uniformity information, specifically the ratio of the maximum to the minimum ratio.

[0142] For example, as shown in Table 4, it illustrates the uniformity information of different leather suede types. Table 4 includes uniformity information of leather suede for three different subjective perceptions: Sample 1, Sample 2, and Sample 3. Each leather suede type includes five sub-regions: Sub-region 1, Sub-region 2, Sub-region 3, Sub-region 4, and Sub-region 5.

[0143] Table 4. Uniformity information of different leather nap.

[0144]

[0145] In other words, for sample 1, which has a good subjective perception, the uniform information is 1.18. For sample 2, which has a medium subjective perception, the uniform information is 2.06. For sample 3, which has a poor subjective perception, the uniform information is 3.36.

[0146] It should be noted that, in the embodiments of this application, the uniformity of the leather nap is generally best when the uniformity information is 1. When the uniformity information is greater than 1, the larger the uniformity information, the worse the uniformity of the leather nap.

[0147] Understandably, the server can acquire a second fuzz image, which includes a second test area. The magnification of the second fuzz image is less than that of the first fuzz image. The server can divide the second test area into multiple sub-regions, each with the same area but a different fuzz density. Based on the fuzz density in each sub-region, the server can determine the protrusion area of ​​each sub-region, thus identifying multiple protrusion areas. Each protrusion area is the area in the sub-region where the fuzz density exceeds a preset density threshold. The server can then determine a first area and a second area from these protrusion areas. The first area is the largest among the protrusion areas, and the second area is the smallest. Subsequently, the server can determine uniformity information based on the first and second areas, which is the ratio of the first area to the second area. In this way, the server can determine the protrusion area of ​​each sub-region and obtain the uniformity of the fuzz through the maximum and minimum protrusion areas. This improves the accuracy of the fuzz uniformity information.

[0148] In some embodiments, to determine the visual quality of a batch of leather suede, a batch includes multiple leather suede pieces. The method for determining the visual quality of the suede may further include: a server acquiring multiple leather suede pieces, wherein the multiple leather suede pieces are leather suede pieces of a target batch. Next, the server acquiring the target length and uniformity information of each leather suede piece among the multiple leather suede pieces. The server determining first average information based on the target length of each leather suede piece among the multiple leather suede pieces, the first average information reflecting the average length of the leather suede pieces in the target batch. The server determining second average information based on the uniformity information of each leather suede piece among the multiple leather suede pieces, the second average information reflecting the average uniformity of the leather suede pieces in the target batch. The server determining comprehensive information based on the first average information and the second average information, the comprehensive information reflecting the average visual quality of the leather suede pieces in the target batch.

[0149] It should be noted that, in this embodiment, since the first average information is used to reflect the average length of multiple leather fibers, and the second average information is used to reflect the average uniformity of multiple leather fibers, the first average information can be equivalent to the target length, the second average information can be equivalent to the uniformity information, and the comprehensive information can be equivalent to the quality information. For the description of "determining comprehensive information based on the first average information and the second average information," please refer to the description of "determining quality information based on the target length and uniformity information" in S203; it will not be repeated here.

[0150] The method for determining the visual quality of the pile in this application will be described below with reference to specific embodiments. For example... Figure 11 As shown, the method for determining the visual quality of fluff may include the following steps:

[0151] S1101. The staff performs restoration treatment on the leather suede to obtain restored leather suede.

[0152] For example, staff can select a suitable testing environment and perform consistent treatment on the leather suede within that environment.

[0153] It should be noted that, in the embodiments of this application, the description of "the staff restores the leather suede to obtain the restored leather suede" can be referred to the description in step one that "the staff can place the leather suede in a constant temperature and humidity environment for a preset time", and will not be repeated here.

[0154] S1102. Staff select the first and second test areas from the restored leather suede.

[0155] S1103. The staff applies pressure to the leather suede in the first test area to obtain the leather suede after pressure.

[0156] For example, staff can attach transparent tape to the first test area, apply a preset load to the first test area, and maintain it for a second preset time.

[0157] It should be noted that, in the embodiments of this application, the description of "the staff applying pressure to the leather fur in the first test area" can be found in step three, which describes "the staff can stick transparent tape to the first test area and place a weight with a preset load on the transparent tape". It will not be repeated here.

[0158] In this embodiment of the application, after applying a preset load to the first area to be tested and maintaining it for a second preset time, the worker can remove the preset load to obtain the leather velvet after the pressure is applied.

[0159] S1104. Staff determine the target length of the leather nap based on the first and second test areas.

[0160] It should be noted that, in this embodiment, the first test area includes the leather suede after pressure is applied, and the second test area includes the leather suede without pressure. Regarding the description of "the worker determining the target length of the leather suede based on the first and second test areas" in this embodiment, please refer to the description of determining the target length in S301-S303, which will not be repeated here.

[0161] S1105. Staff determine the uniformity information of the leather nap based on the second test area.

[0162] It should be noted that, in the embodiments of this application, the description of "the staff determines the uniformity information of the leather fur according to the second test area" can be referred to the description of determining uniformity information in S801-S805, and will not be repeated here.

[0163] S1106. Staff determine quality information based on target length and uniformity information.

[0164] S1107. Staff replaced the leather suede for evaluation.

[0165] It should be noted that, in this embodiment, the leather suede needs to be replaced after evaluation to prevent unevenness caused by repeated pressure application, which could lead to inaccurate evaluation. At least three pieces of leather suede from the same batch need to be evaluated to ensure the accuracy of the visual quality assessment within that batch.

[0166] In this way, the server can determine the visual quality of leather suede from two dimensions: suede length and suede uniformity, which can improve the accuracy of determining the visual quality of leather suede.

[0167] The above primarily describes the solutions provided by the embodiments of this application from a methodological perspective. To achieve the above functions, the apparatus or device for determining the visual quality of the velvet fibers includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0168] This application embodiment can, based on the above method, exemplarily divide the apparatus or device for determining the visual quality of fluff into functional modules. For example, the apparatus or device for determining the visual quality of fluff may include functional modules corresponding to each functional division, or two or more functions may be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. It should be noted that the module division in this application embodiment is illustrative and only represents one logical functional division; in actual implementation, there may be other division methods.

[0169] Figure 12 This is a block diagram illustrating a device for determining the visual quality of fluff according to an exemplary embodiment. (Refer to...) Figure 12 The device for determining the visual quality of the plush is used to perform... Figure 2 , Figure 3 and Figure 8 The method shown. The apparatus for determining the visual quality of the plush material includes: an acquisition unit 1201 and a processing unit 1202.

[0170] The acquisition unit 1201 is used to acquire the target length and uniformity information of the leather suede, where the target length is the length of the leather suede and the uniformity information reflects the evenness of the leather suede. The processing unit 1202 is used to determine quality information based on the target length and uniformity information, whereby the quality information reflects the visual quality of the leather suede.

[0171] In one possible implementation, the acquisition unit 1201 is specifically used to acquire a first lint image, which includes a first test area and a second test area. The first test area includes lint after pressure is applied, and the second test area includes lint without pressure. The processing unit 1202 is specifically used to determine a first length and a second length based on the first lint image. The first length is the length of the leather lint in the first test area, and the first length is less than a preset length threshold. The second length is the length of the leather lint in the second test area. The processing unit 1202 is specifically used to determine a target length based on the first length and the second length. The target length is the difference between the first length and the second length.

[0172] In one possible implementation, the acquisition unit 1201 is specifically used to acquire a second fuzz image, the second fuzz image including a second test area, and the magnification of the second fuzz image being less than the magnification of the first fuzz image. The processing unit 1202 is specifically used to divide the second test area into multiple sub-regions, the multiple sub-regions having the same area, and each sub-region having a different density of leather fuzz. The processing unit 1202 is specifically used to determine the protrusion area of ​​each sub-region based on the density of leather fuzz in each sub-region, thereby determining multiple protrusion areas, where each protrusion area is the area in the sub-region where the density of leather fuzz is greater than a preset density threshold. The processing unit 1202 is specifically used to determine a first area and a second area from the multiple protrusion areas, where the first area is the largest among the multiple protrusion areas, and the second area is the smallest among the multiple protrusion areas. The processing unit 1202 is specifically used to determine uniformity information based on the first area and the second area, where the uniformity information is the ratio of the first area to the second area.

[0173] In one possible implementation, the processing unit 1202 is further configured to determine the area of ​​each sub-region. Specifically, the processing unit 1202 is configured to determine a first ratio based on a first area and the area of ​​the sub-region. Specifically, the processing unit 1202 is configured to determine a second ratio based on a second area and the area of ​​the sub-region. Specifically, the processing unit 1202 is configured to determine uniformity information based on the first ratio and the second ratio, wherein the uniformity information is specifically the ratio of the first ratio to the second ratio.

[0174] In one possible implementation, the processing unit 1202 is specifically used to determine the pile length grade based on the target length and a first correspondence, where the first correspondence is the relationship between the target length and the pile length grade, and the pile length grade reflects the degree of influence of the target length on the quality information. The processing unit 1202 is also specifically used to determine the uniformity grade based on uniformity information and a second correspondence, where the second correspondence is the relationship between uniformity information and the uniformity grade, and the uniformity grade reflects the degree of influence of the uniformity information on the quality information. Finally, the processing unit 1202 is specifically used to determine quality information based on the pile length grade and the uniformity grade.

[0175] Regarding the apparatus in the above embodiments, the specific manner in which each unit performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0176] Figure 13 This is a block diagram illustrating an electronic device according to an exemplary embodiment. Figure 13 As shown, the electronic device 1300 includes, but is not limited to, a processor 1301 and a memory 1302.

[0177] The memory 1302 described above is used to store executable instructions of the processor 1301. It is understood that the processor 1301 is configured to execute instructions to implement the method for determining the visual quality of the velvet in the above embodiment.

[0178] It should be noted that those skilled in the art will understand that Figure 13 The electronic device structure shown does not constitute a limitation on the electronic device; the electronic device may include, but is not limited to, other electronic devices. Figure 13 This may indicate more or fewer components, or combinations of certain components, or different component arrangements.

[0179] Processor 1301 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines. By running or executing software programs and / or modules stored in memory 1302, and by calling data stored in memory 1302, it performs various functions and processes data, thereby providing overall monitoring of the electronic device. Processor 1301 may include one or more processing units. Optionally, processor 1301 may integrate an application processor and a modem processor. The application processor mainly handles the operating system, user interface, and applications, while the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into processor 1301.

[0180] The memory 1302 can be used to store software programs and various data. The memory 1302 may mainly include a program storage area and a data storage area, wherein the program storage area may store the operating system, application programs (such as processing units) required by at least one functional module, etc. In addition, the memory 1302 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0181] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory 1302 including instructions, which can be executed by a processor 1301 of an electronic device 1300 to implement the method for determining the visual quality of fur in the above embodiments.

[0182] In actual implementation, Figure 12 The functions of the acquisition unit 1201 and the processing unit 1202 can both be provided by Figure 13 The processor 1301 calls the computer program stored in the memory 1302 to implement the process. The specific execution process can be found in the description of the method for determining the visual quality of the fluff in the previous embodiment, and will not be repeated here.

[0183] Optionally, the computer-readable storage medium may be a non-transitory computer-readable storage medium, such as a read-only memory (ROM), random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device.

[0184] In an exemplary embodiment, this application also provides a computer program product including one or more instructions, which can be executed by a processor of an electronic device to complete the method for determining the visual quality of fur in the above embodiments.

[0185] It should be noted that when one or more instructions in the computer-readable storage medium or computer program product are executed by the processor of an electronic device, they implement the various processes of the above-described method for determining the visual quality of fur, and can achieve the same technical effect as the above-described method for determining the visual quality of fur. To avoid repetition, they will not be described again here.

[0186] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0187] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another apparatus, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0188] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0189] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0190] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, essentially, or the parts that contribute to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0191] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for determining the visual quality of plush texture, characterized in that, The method includes: A first fluff image is acquired, the first fluff image including: a first test area and a second test area, the first test area including fluff after pressure is applied, and the second test area including fluff without pressure; Based on the first velvet image, a first length and a second length are determined. The first length is the length of the leather velvet in the first test area, and the first length is less than a preset length threshold. The second length is the length of the leather velvet in the second test area. The leather velvet includes: the velvet after pressure and the velvet without pressure. The target length of the leather nap is determined based on the first length and the second length, wherein the target length is the difference between the first length and the second length; A second velvet image is acquired, the second velvet image includes a second region to be tested, and the magnification of the second velvet image is less than the magnification of the first velvet image; The second test area is divided into multiple sub-regions, each with the same area, but with a different density of leather fur in each sub-region. Based on the density of the leather suede in each sub-region, the protrusion area of ​​each sub-region is determined to determine a plurality of protrusion areas, wherein the protrusion area is the area in the sub-region where the density of the leather suede is greater than a preset density threshold; A first area and a second area are determined from the plurality of protrusion areas, wherein the first area is the largest of the plurality of protrusion areas and the second area is the smallest of the plurality of protrusion areas; Based on the first area and the second area, the uniformity information of the leather nap is determined, wherein the uniformity information is the ratio of the first area to the second area; the uniformity information is used to reflect the degree of uniformity of the leather nap. Based on the target length and the uniformity information, quality information is determined, which reflects the visual quality of the leather nap.

2. The method according to claim 1, characterized in that, Before determining the uniformity information based on the first area and the second area, the method further includes: Determine the area of ​​each of the sub-regions; Determining the uniformity information based on the first area and the second area includes: A first ratio is determined based on the first area and the area of ​​the region; A second ratio is determined based on the second area and the area of ​​the region; The uniformity information is determined based on the first ratio and the second ratio, wherein the uniformity information is specifically the ratio of the first ratio to the second ratio.

3. The method according to claim 1, characterized in that, The step of determining the quality information based on the target length and the uniformity information includes: Based on the target length and the first correspondence, the pile length grade is determined, wherein the first correspondence is the correspondence between the target length and the pile length grade, and the pile length grade is used to reflect the degree of influence of the target length on the quality information; Based on the uniformity information and the second correspondence, a uniformity level is determined. The second correspondence is the correspondence between the uniformity information and the uniformity level. The uniformity level is used to reflect the degree of influence of the uniformity information on the quality information. The quality information is determined based on the pile length grade and the uniformity grade.

4. A device for determining the visual quality of plush texture, characterized in that, The device includes: An acquisition unit is used to acquire a first fluff image, the first fluff image including: a first test area and a second test area, the first test area including fluff after pressure is applied, and the second test area including fluff without pressure; Based on the first velvet image, a first length and a second length are determined. The first length is the length of the leather velvet in the first test area, and the first length is less than a preset length threshold. The second length is the length of the leather velvet in the second test area. The leather velvet includes: the velvet after pressure and the velvet without pressure. The target length of the leather nap is determined based on the first length and the second length, wherein the target length is the difference between the first length and the second length; A second velvet image is acquired, the second velvet image includes a second region to be tested, and the magnification of the second velvet image is less than the magnification of the first velvet image; The second test area is divided into multiple sub-regions, each with the same area, but with a different density of leather fur in each sub-region. Based on the density of the leather suede in each sub-region, the protrusion area of ​​each sub-region is determined to determine a plurality of protrusion areas, wherein the protrusion area is the area in the sub-region where the density of the leather suede is greater than a preset density threshold; A first area and a second area are determined from the plurality of protrusion areas, wherein the first area is the largest of the plurality of protrusion areas and the second area is the smallest of the plurality of protrusion areas; Based on the first area and the second area, the uniformity information of the leather nap is determined, wherein the uniformity information is the ratio of the first area to the second area; the uniformity information is used to reflect the degree of uniformity of the leather nap. The processing unit is configured to determine quality information based on the target length and the uniformity information, the quality information being used to reflect the visual quality of the leather nap.

5. An electronic device, characterized in that, include: processor; A memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the method as described in any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, When the computer-executable instructions stored in the computer-readable storage medium are executed by the processor of the electronic device, the electronic device is capable of performing the method as described in any one of claims 1 to 3.

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