Surface color difference control system of plastic product

Abstract

The invention discloses a surface color difference control system of a plastic product, relates to the technical field of plastic products, and solves the problems of excessive data processing and low efficiency of an existing color difference analysis mode. Lab values of pixel points in each feature region are converted into three-dimensional coordinates by constructing a three-dimensional coordinate system, and the surface color difference control system of the plastic product is obtained. Calculating a mean value coordinate as a characteristic coordinate, comparing the characteristic coordinate with a standard coordinate of a standard region, and accurately quantifying a color difference value (CY) between the characteristic region and the standard region; according to the quantitative analysis method, whether the color difference reaches the standard or not can be accurately judged, and a clear quantitative basis is provided for subsequent parameter adjustment; and comparing the feature coordinates of the region with the features to be confirmed with standard coordinates, calculating coordinate difference values (CLq, Caq and Cbq), and accurately identifying change features needing to be adjusted according to a preset threshold value (Y3).

Description

Technical Field

[0001] The present invention relates to the technical field of plastic products, and particularly to a surface color difference control system for plastic products. Background Art

[0002] In the plastic product manufacturing industry, the consistency and accuracy of the surface color of products are crucial for product quality and market competitiveness. Due to various factors involved in the production process, such as fluctuations in raw material properties, changes in processing parameters, and differences in equipment performance, color difference problems are extremely likely to occur on the surface of plastic products. Traditional color difference detection methods mainly rely on manual visual inspection, which is not only inefficient but also affected by the subjective factors of inspectors, making it difficult to ensure the accuracy and consistency of detection. With the development of machine vision technology, its application in the field of industrial inspection has become increasingly widespread.

[0003] Although early machine vision detection systems were able to collect images of the surface of plastic products, there were many deficiencies in the image processing and color difference analysis links. In terms of image processing, most systems used simple grayscale methods, which could not accurately reflect color information, resulting in low accuracy in subsequent contour recognition and color difference analysis. For example, directly taking the average value of RGB values for grayscaling ignored the sensitivity differences of the human eye to different colors, causing important information to be lost during the grayscale conversion of the image.

[0004] In the color difference analysis link, early systems usually only performed simple color comparison on the overall image, unable to conduct detailed analysis on different color regions, and easily missed local color difference problems. Moreover, these systems lacked an effective parameter adjustment mechanism. Even if color difference problems were detected, it was difficult to accurately give corresponding adjustment solutions, resulting in color difference problems in the production process being difficult to be solved in a timely manner.

[0005] In addition, existing color difference detection systems also have deficiencies in data management and analysis, unable to make full use of historical data to guide parameter adjustment in the production process, making the optimization of the production process lack data support. Summary of the Invention

[0006] Aiming at the deficiencies of the prior art, the present invention provides a surface color difference control system for plastic products, which solves the problems of excessive data processing and low efficiency in existing color difference analysis methods.

[0007] To achieve the above objectives, the present invention is realized through the following technical solutions: A surface color difference control system for plastic products, comprising: The image feature processing end acquires the surface image of the processed plastic product, assigns different weights to different RGB values associated with different points, determines the gray value associated with each point, converts the surface image into a gray image, and then calibrates several contour regions in the gray image in sequence based on the gradient features existing in the gray image. The specific method is as follows: Based on the different gray values HD associated with different pixel points in the gray image i , use the Sobel algorithm to determine the vertical gradient T associated with the corresponding pixel point i and the vertical gradient D i ; Then use: To determine the comprehensive gradient ZH associated with the corresponding pixel point i , and mark the pixel points that satisfy: ZH i ≥Y1 as gradient pixel points, otherwise, no marking is performed. Y1 is a preset value; Based on several gradient pixel points confirmed in the gray image, determine the gradient contour, record the regions included in different gradient contours as different contour regions, and transmit the gray image with the contour region calibration completed to the partition verification and checking end; The partition verification and checking end compares and verifies the gray image with the contour region calibration completed with the pre-stored template image, identifies the Lab values associated with the same points in different images, and based on the overall difference of the Lab values in the same region, identifies whether the surface image of this plastic product meets the color difference standard. The specific method is as follows: Based on the contour regions calibrated in the gray image, perform region calibration in the original surface image, record the calibrated regions associated with the contour regions as feature regions, and different contour regions correspond to different feature regions; Align the center points of the surface image and the template image. After completing the center point alignment, determine the standard regions associated with the feature regions in the template image, and sequentially determine and perform color difference verification on the standard regions associated with each feature region: Determine the Lab values associated with each different pixel point in the feature region, and construct a three-dimensional coordinate system. The data associated with the x-axis is brightness data, the data associated with the y-axis is red-green value data, and the data associated with the z-axis is yellow-blue value data. Based on the different Lab values associated with different pixel points in the feature region, determine the three-dimensional coordinates (L k , a k , b k ) associated with the corresponding pixel points in the three-dimensional coordinate system, where k represents different pixel points associated with this feature region, and assume k = 1, 2,..., n, and n is the total number of pixel points in the feature region; Use: Confirm the mean coordinates (JL, Ja, Jb) associated with the three-dimensional coordinates corresponding to all pixel points within this feature region, and record them as the feature coordinates of this feature region; Then, adopt the same processing method for determining the feature coordinates within the feature region to confirm the standard coordinates of the standard region associated with this feature region, and calibrate the standard coordinates as (BL, Ba, Bb); Based on the feature coordinates and the standard coordinates, confirm the color difference difference value between the feature region and the standard region: Adopt Confirm the color difference difference value CY, and evaluate whether the color difference difference value CY satisfies: CY ≥ Y2, where Y2 is a preset value. If it is satisfied, calibrate this feature region as a feature to be confirmed region, and execute subsequent re-analysis processing by the change feature confirmation end to determine the specific parameters that need to be controlled and adjusted. If it is not satisfied, no calibration is required.

[0008] Preferably, it further includes: A standard image database, which pre-stores standard template images internally, and the template images are formulated and stored in advance by relevant personnel according to the standards.

[0009] Preferably, it further includes: A change feature confirmation end, which extracts and confirms the feature coordinates and the standard coordinates associated with the feature to be confirmed region, and then confirms the change features based on the coordinate differences between the feature coordinates and the standard coordinates. The specific method is as follows: Record the feature coordinates associated with the corresponding feature to be confirmed region as (JL q , Ja q , Jb q ), where q represents different feature to be confirmed regions, and record the standard coordinates associated with this feature to be confirmed region as (BL q , Ba q , Bb q ); Adopt: CL q = (BL q - JL q ), Ca q = (Ba q - Ja q ), and Cb q = (Bb q - Jb q ) to confirm the change differences CL q , Ca q , and Cb q associated with the corresponding coordinate parameters. If there is a change difference with |change difference| ≥ Y3, calibrate the corresponding change difference as a change feature; otherwise, no calibration is performed, where Y3 is a preset value; Transfer a number of varying features determined by this feature to-be-confirmed area to the correction parameter output end; The correction parameter output end confirms and outputs the correction parameter based on a number of varying features determined by the corresponding feature to-be-confirmed area, in combination with historical data. The specific method is as follows: Confirm the item to which the varying feature belongs: If the varying feature is CL q , confirm whether CL q is a positive value. If it is a positive value, confirm the heating temperature associated with an increase of one unit in the L value from the historical data, and use: CL q × heating temperature = increased temperature to confirm the increased temperature that needs to be corrected. If it is a negative value, confirm the heating temperature associated with a decrease of one unit in the L value from the historical data, and use the same processing method to confirm the decreased temperature that needs to be corrected; If the varying feature is Ca q , confirm whether Ca q is a positive value. If it is a positive value, confirm the proportion of red pigment associated with an increase of one unit in the a value from the historical data, and use: Ca q × proportion of red pigment = increased red ratio to confirm the increased red ratio that needs to be corrected. If it is a negative value, confirm the proportion of green pigment associated with a decrease of one unit in the a value from the historical data, and use: Ca q × proportion of green pigment = increased green ratio to confirm the increased green ratio that needs to be corrected; If the varying feature is Cb q , confirm whether Cb q is a positive value. If it is a positive value, confirm the proportion of yellow pigment associated with an increase of one unit in the b value from the historical data, and use: Ca q × proportion of yellow pigment = increased yellow ratio to confirm the increased yellow ratio that needs to be corrected. If it is a negative value, confirm the proportion of blue pigment associated with a decrease of one unit in the a value from the historical data, and use: Ca q × proportion of blue pigment = increased blue ratio to confirm the increased blue ratio that needs to be corrected.

[0010] The present invention provides a surface color difference control system for plastic products. Compared with the prior art, it has the following beneficial effects: By constructing a three-dimensional coordinate system, the present invention converts the Lab values of pixel points in each feature area into three-dimensional coordinates, calculates the mean coordinate as the feature coordinate, and compares it with the standard coordinate of the standard area, accurately quantifying the color difference difference value (CY) between the feature area and the standard area; this quantitative analysis method can not only accurately judge whether the color difference meets the standard, but also provides a clear quantitative basis for subsequent parameter adjustment; By comparing the characteristic coordinates of the area where the characteristics need to be confirmed with the standard coordinates, the coordinate difference values (CLq, Caq, Cbq) are calculated, and the changing characteristics that need to be adjusted are accurately identified according to the preset threshold (Y3). This method can clearly determine the specific changes in color in terms of brightness, red-green value, yellow-blue value, etc., and points out the direction for subsequent parameter adjustment. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 is a schematic diagram of the principle framework of the present invention; Figure 2 is a schematic diagram for confirming the area where the characteristics of the present invention need to be confirmed. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0012] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0013] The First Embodiment Please refer to Figure 1 , this application provides a surface color difference control system for plastic products, including an image feature processing end, a standard image database, a partition verification and check end, a changing feature confirmation end, and a correction parameter output end. Among them, both the image feature processing end and the standard image database are electrically connected to the input nodes of the partition verification and check end, and the partition verification and check end is electrically connected to the input nodes of the changing feature confirmation end, and the changing feature confirmation end is electrically connected to the input nodes of the correction parameter output end; Among them, the image feature processing end acquires the surface image of the plastic product that has completed the processing by using a machine vision device, assigns different weights to the different RGB values associated with different points in the surface image, confirms the gray value associated with the point, converts the surface image into a gray image, and based on the gradient features existing in the gray image, calibrates several contour areas existing in the gray image in sequence. Specifically, during the image acquisition process, the RGB values can be directly confirmed, which are the R value, the G value, and the B value respectively. When the corresponding image is grayscale processed, different weights need to be assigned to different values to lock the gray value associated with the corresponding point, and then the surface image is adjusted for grayscale conversion according to the different gray values associated with different points to lock the gray image associated with the corresponding surface image. The range of its gray value is 0-255. By confirming the gray features inside the converted gray image and based on the Sobel algorithm to confirm the gradient features associated with different pixel points, the contour areas associated with the gray image are confirmed and calibrated in sequence; Among them, the specific method for converting the surface image into a grayscale image is as follows: Based on the surface image of the plastic product obtained by the machine vision device (when obtaining the image, the plastic product needs to be placed at a fixed position, and the machine vision device obtains the image of the surface of the plastic product to be inspected. The fixed positions of the machine vision device and the plastic product are set in advance by relevant personnel), the RGB values associated with different pixel points in the surface image are confirmed in sequence, and the following formula is used: HD i = 0.299R + 0.587G + 0.114B to confirm the grayscale value HD associated with the corresponding pixel point i , where i represents different pixel points; According to the different grayscale values associated with different pixel points, the surface image is grayscale processed to confirm the grayscale image associated with the surface image (Grayscale processing of the obtained image is relatively common in the prior art, so it will not be elaborated here); The specific method for calibrating different contour regions in the grayscale image is as follows: Based on the different grayscale values associated with different pixel points in the grayscale image HD i , the Sobel algorithm is used to confirm the vertical gradient T associated with the corresponding pixel point i and the vertical gradient D i . Specifically, when the Sobel algorithm is used to confirm gradient data, it generally based on the corresponding pixel point and multiple groups of pixel points associated therewith. According to the different pixel values associated with different pixel points, different weights are assigned to different pixel values, and then the weighted parameters are summed up to confirm the corresponding vertical gradient and vertical gradient. Since the method for confirming gradient features is relatively common in the prior art, it will not be elaborated here; Then the following formula is used: to confirm the comprehensive gradient ZH associated with the corresponding pixel point i , and the pixel points that satisfy: ZH i ≥ Y1 are calibrated as gradient pixel points, otherwise, no calibration is performed. Y1 is a preset value; Based on several gradient pixel points confirmed in the grayscale image, the gradient contour is confirmed, and the regions included in different gradient contours are denoted as different contour regions (when the color difference of the corresponding region is relatively obvious, the surrounding contour belongs to the confirmed gradient contour. Based on the specific pixel values associated with the pixel points, it can be quickly and effectively confirmed. Based on the corresponding gradient features, different contour regions can be confirmed from the grayscale image, and different contour regions correspond to different color regions), and the grayscale image with the contour region calibration completed is transmitted to the partition verification and comparison end.

[0014] Its standard image database pre-stores standard template images, which are formulated and stored in advance by relevant personnel according to the standards for facilitating subsequent color difference verification and comparison.

[0015] Its partition verification and checking end compares and verifies the grayscale image with the contour area calibrated with the pre-stored template image, identifies the Lab values associated with the same points in different images, and identifies whether the surface image of this plastic product meets the color difference standard. Specifically, the grayscale image has the same size as the pre-stored template image. Unless there is an error in the size inspection of the corresponding plastic product, it is necessary to ensure that the size of the corresponding plastic product is correct before performing the color difference inspection, and the arrangement of the corresponding grayscale image and the template image is in the same state, that is, it facilitates the specific image comparison process in the later stage; The specific method for performing the comparison and verification is as follows: Based on the contour area calibrated in the grayscale image, perform area calibration in the original surface image, and record the area calibrated and associated with the contour area as the feature area. Different contour areas correspond to different feature areas; Combined with Figure 2 , make the center points of the surface image and the template image coincide. There is a preset center point in the template image. When the surface image is acquired, the position of the center point has been marked or the internal center point of the surface image can also be confirmed according to the overall image edge of the surface image. Combine the image edge with the two-dimensional coordinate system to determine the internal center point of the surface image. After the center points coincide, confirm the standard area associated with the feature area in the template image, and sequentially confirm the standard area associated with each feature area and perform color difference verification: Confirm the Lab values associated with each different pixel point in the feature area (the L value is the brightness data of the corresponding point, the a value is the red-green value of the corresponding point, positive indicates red, negative indicates green, the b value is the yellow-blue value of the corresponding point, positive indicates yellow, negative indicates blue), and construct a three-dimensional coordinate system. The data associated with the x-axis is the brightness data, the data associated with the y-axis is the red-green value data, and the data associated with the z-axis is the yellow-blue value data. Based on the different Lab values associated with different pixel points in the feature area, confirm the three-dimensional coordinates (L k , a k , b k ) associated with the corresponding pixel points in the three-dimensional coordinate system, where k represents the different pixel points associated with this feature area, and it is assumed that k = 1, 2,..., n, and n is the total number of pixel points in the feature area; Adopt: Confirm the mean coordinates (JL, Ja, Jb) associated with the three-dimensional coordinates of all pixel points in this feature area, and record them as the feature coordinates of this feature area; Then, adopt the processing method of determining the same characteristic coordinates within the characteristic area to confirm the standard coordinates of the standard area associated with this characteristic area, and mark the standard coordinates as (BL, Ba, Bb); Based on the characteristic coordinates and the standard coordinates, confirm the color difference value between the characteristic area and the standard area: Adopt Confirm the color difference value CY, and evaluate whether the color difference value CY meets the condition: CY≥Y2, where Y2 is a preset value, and its specific value is determined by the operator according to experience. If it is satisfied, it means that the color difference of this characteristic area is relatively obvious. Mark this characteristic area as the characteristic area to be confirmed, and execute the subsequent change characteristic confirmation end for re-analysis to determine the specific parameters that need to be controlled and adjusted. If it is not satisfied, no marking is required; Specifically, based on the multiple points associated with the corresponding partition in the corresponding image, confirm the three-dimensional coordinate points based on the Lab values related to each point. Then, from the three-dimensional coordinates of the confirmed several spatial coordinate points, lock the mean coordinate, and confirm the characteristic points (i.e., characteristic coordinates) associated with the corresponding area in the three-dimensional coordinate system through the mean coordinate. Subsequently, confirm the standard area with a comparison relationship based on this characteristic area, and synchronously confirm the numerical points associated with the standard area. According to the actual comparison and verification of the two groups of numerical points, confirm the difference distance between the two point coordinates. If the difference distance is large, it means that the color characteristics of this characteristic area are quite different from those of the standard area. Therefore, it is necessary to specifically confirm the characteristic values to identify whether the corresponding color difference length or value exceeds the standard. By using this color difference verification method, the quick verification effect for the same characteristic color area can be achieved quickly and effectively, and the verification result can be output in a timely manner and specifically displayed.

[0016] Among them, the change characteristic confirmation end extracts and confirms the characteristic coordinates and the standard coordinates associated with the characteristic area to be confirmed. Then, based on the coordinate difference between the characteristic coordinates and the standard coordinates, confirm the change characteristics and transmit the confirmed change characteristics to the correction parameter output end. The specific method for confirmation is as follows: Record the characteristic coordinates associated with the corresponding characteristic area to be confirmed as (JL q 、Ja q 、Jb q ), where q represents different characteristic areas to be confirmed. Record the standard coordinates associated with this characteristic area to be confirmed as (BL q 、Ba q 、Bb q ); Adopt: CL q =(BL q -JL q ), Ca q =(Ba q -Jaq ), and Cb q = (Bb q - Jb q ) to confirm the change difference CL associated with the corresponding coordinate parameters q , Ca q , and Cb q . If there exists a change difference with |change difference| ≥ Y3, the corresponding change difference is marked as a change feature; otherwise, no marking is performed. Here, Y3 is a preset value, and its specific value is determined by the operator according to experience. Generally, Y3 takes five change units (i.e., five scales on the corresponding coordinate); Transmit the several change features determined by this area to be confirmed for features to the correction parameter output end. Specifically, the change feature is the relevant parameter that needs to be adjusted subsequently. When the corresponding change feature is negative, the parameter needs to be down - adjusted for subsequent processing in the same area. When the corresponding change feature is positive, the parameter needs to be up - adjusted for subsequent processing in the same area.

[0017] The correction parameter output end, based on the several change features determined by the corresponding area to be confirmed for features, combines historical data to confirm and output the correction parameter. The specific method for confirming the correction parameter is as follows: Confirm the item to which the change feature belongs: If the change feature is CL q , confirm whether CL q is positive. If it is positive, confirm the heating temperature associated with the L value increased by one unit from the historical data, and use: CL q × heating temperature = increased temperature to confirm the increased temperature that needs to be corrected. If it is negative, confirm the heating temperature associated with the L value decreased by one unit from the historical data, and use the same processing method to confirm the decreased temperature that needs to be corrected; If the change feature is Ca q , confirm whether Ca q is positive. If it is positive, confirm the proportion of red pigment associated with the a value increased by one unit from the historical data, and use: Ca q × proportion of red pigment = increased red ratio to confirm the increased red ratio that needs to be corrected. If it is negative, confirm the proportion of green pigment associated with the a value decreased by one unit from the historical data, and use: Ca q × proportion of green pigment = increased green ratio to confirm the increased green ratio that needs to be corrected; If the change feature is Cb q , confirm whether Cb q is positive. If it is positive, confirm the proportion of yellow pigment associated with the b value increased by one unit from the historical data, and use: Ca q× Yellow pigment ratio = Yellow enhancement ratio. Confirm the yellow enhancement ratio that needs to be corrected. If it is negative, confirm the blue pigment ratio associated with a one-unit decrease in the a value from historical data, and use: Ca q × Blue pigment ratio = Blue enhancement ratio. Confirm the blue enhancement ratio that needs to be corrected; Output the confirmed correction parameters for external relevant personnel to review, and promptly control and adjust the associated parameters.

[0018] Some of the data in the above formulas are used for numerical calculations after removing their dimensions, and the content not described in detail in this specification belongs to the prior art well-known to those skilled in the art.

[0019] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A surface color difference control system for plastic products, characterized in that, Including: An image feature processing terminal acquires the surface image of the processed plastic product, assigns different weights to different RGB values associated with different points, confirms the gray value associated with each point, converts the surface image into a gray image, and then calibrates several contour regions existing in the gray image in sequence based on the gradient features existing in the gray image; A partition verification and check terminal compares and verifies the gray image with the calibrated contour regions with a pre-stored template image, identifies the Lab values associated with the same points in different images, and identifies whether the surface image of this plastic product meets the color difference standard based on the overall difference in Lab values in the same region.

2. The surface color difference control system for a plastic product according to claim 1, characterized in that For the image feature processing terminal, the specific method of converting the surface image into a gray image is: Based on the surface image of the plastic product obtained by the machine vision device, the RGB values associated with different pixel points in the surface image are confirmed in sequence, and the following formula is used: HD i = 0.299R + 0.587G + 0.114B to confirm the grayscale value HD i , where i represents different pixel points; According to the different gray values associated with different pixel points, the surface image is grayed out to confirm the gray image associated with the surface image.

3. The surface color difference control system for a plastic product according to claim 1, characterized in that, For the image feature processing terminal, the specific method of calibrating different contour regions in the gray image is: Based on the different grayscale values HD associated with different pixel points in the grayscale image i , the Sobel algorithm is used to confirm the vertical gradient T i and the vertical gradient D i ; Then adopt: Confirm the comprehensive gradient ZH associated with the corresponding pixel i , and the pixels that satisfy: ZH i ≥Y1 are calibrated as gradient pixels, otherwise, no calibration is performed, where Y1 is a preset value; Based on several gradient pixel points confirmed in the gray image, the gradient contours are confirmed, and the regions included in different gradient contours are recorded as different contour regions, and the gray image with the calibrated contour regions is transmitted into the partition verification and check terminal.

4. The surface color difference control system for a plastic product according to claim 1, characterized in that, It also includes: A standard image database pre-stores standard template images, and the template images are prepared and stored in advance by relevant personnel according to the standards.

5. The surface color difference control system for a plastic product according to claim 1, wherein, For the partition verification and check terminal, the specific method of identifying whether the surface image of this plastic product meets the color difference standard is: Based on the contour regions calibrated in the gray image, region calibration is performed in the original surface image, and the regions associated with the calibrated contour regions are recorded as feature regions, and different contour regions correspond to different feature regions; The surface image and the template image are centered and overlapped. After the center points are overlapped, the standard regions associated with the feature regions in the template image are confirmed, and the standard regions associated with each feature region are confirmed in sequence and color difference verification is performed: Confirm the Lab values associated with each different pixel point in the feature region, and construct a three-dimensional coordinate system. The data associated with the x-axis is brightness data, the data associated with the y-axis is red-green value data, and the data associated with the z-axis is yellow-blue value data. Based on the different Lab values associated with different pixel points in the feature region, confirm the three-dimensional coordinates (L k , a k , b k ) associated with the corresponding pixel points in the three-dimensional coordinate system, where k represents the different pixel points associated within this feature region, and it is assumed that k = 1, 2, ……, n, and n is the total number of pixel points in the feature region; Adopt: Confirm the mean coordinates (JL, Ja, Jb) associated with the three-dimensional coordinates corresponding to all pixel points within this feature region, and record them as the feature coordinates of this feature region; Then, by adopting the processing method of determining the same feature coordinates in the feature region, the standard coordinates of the standard region associated with this feature region are confirmed, and the standard coordinates are calibrated as (BL, Ba, Bb); Based on the feature coordinates and the standard coordinates, confirm the color difference value between the feature area and the standard area: Use Confirm the color difference value CY, and evaluate whether the color difference value CY meets the requirement: CY≥Y2, where Y2 is a preset value. If it meets the requirement, label this feature area as the feature to be confirmed area, and execute the subsequent variable feature confirmation end for further analysis to determine the specific parameters that need to be controlled and adjusted.

6. The surface color difference control system for a plastic product according to claim 5, characterized in that, If CY does not satisfy CY≥Y2, no calibration is required.

7. The surface color difference control system of a plastic product according to claim 1, characterized in that, It also includes: A change feature confirmation terminal extracts and confirms the feature coordinates and standard coordinates associated with the feature region to be confirmed, then confirms the change features based on the coordinate differences between the feature coordinates and the standard coordinates, and transmits the confirmed change features into the correction parameter output terminal; A correction parameter output terminal confirms and outputs the correction parameters based on several change features determined for the corresponding feature region to be confirmed in combination with historical data.

8. The surface color difference control system for a plastic product according to claim 7, wherein, For the change feature confirmation terminal, the specific method of confirming the change features is: Denote the feature coordinates associated with the corresponding feature to be confirmed area as (JL q 、Ja q 、Jb q ), where q represents different features to be confirmed areas. Denote the standard coordinates associated with this feature to be confirmed area as (BL q 、Ba q 、Bb q ); Adoption: CL q = (BL q - JL q ), Ca q = (Ba q - Ja q ), and Cb q = (Bb q - Jb q ), confirm the change differences CL q , Ca q , and Cb q associated with the corresponding coordinate parameters. If there exists a change difference with |change difference| ≥ Y3, then label the corresponding change difference as a change feature; otherwise, do not perform any labeling, where Y3 is a preset value; Transmit several change features determined for this feature region to be confirmed into the correction parameter output terminal.

9. A surface color difference control system for a plastic product according to claim 8, characterized in that, For the correction parameter output terminal, the specific method of confirming the correction parameters is: Identify the item to which the change feature belongs: If the change feature is CL q , confirm CL q whether it is a positive value. If it is a positive value, confirm the heating temperature associated with the L value increasing by one unit from the historical data, and use: CL q × heating temperature = increased temperature. Confirm the increased temperature that needs to be corrected. If it is a negative value, confirm the heating temperature associated with the L value decreasing by one unit from the historical data, and use the same method to confirm the decreased temperature that needs to be corrected; If the change feature is Ca q , confirm whether Ca q is a positive value. If it is a positive value, confirm the proportion of red pigment associated with a one-unit increase in the a value from historical data, and use: Ca q × proportion of red pigment = red enhancement ratio, and confirm the red enhancement ratio that needs to be corrected. If it is a negative value, confirm the proportion of green pigment associated with a one-unit decrease in the a value from historical data, and use: Ca q × proportion of green pigment = green enhancement ratio, and confirm the green enhancement ratio that needs to be corrected; If the change feature is Cb q , confirm Cb q whether it is positive. If it is positive, confirm the proportion of yellow pigment associated with a one-unit increase in the b value from historical data, and use: Ca q × the proportion of yellow pigment = the yellow increase ratio, and confirm the yellow increase ratio that needs to be corrected. If it is negative, confirm the proportion of blue pigment associated with a one-unit decrease in the a value from historical data, and use: Ca q × the proportion of blue pigment = the blue increase ratio, and confirm the blue increase ratio that needs to be corrected.

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