CN109819245B - On-line measuring method and device for chroma and brightness data based on AOI platform - Google Patents
On-line measuring method and device for chroma and brightness data based on AOI platform Download PDFInfo
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Abstract
The invention discloses an AOI platform-based online measurement method for chromaticity and brightness data, which comprises the steps of respectively collecting an ImgRGB data set and a regXYZ data set by a camera and a color analyzer to obtain a conversion model, converting the ImgRGB data set into an ImgXYZ numerical value by adopting the conversion model, extracting the regXYZ numerical value at a calibration position from the regXYZ data set, extracting an XYZ numerical value corresponding to the calibration position from the ImgXYZ numerical value, comparing the IMgXYZ numerical value and the ImgXYZ numerical value to obtain a correction coefficient, and correcting all the ImgXYZ numerical values by adopting the correction coefficient to obtain a first chromaticity brightness value ImgXYZ. The invention automatically collects data and then corrects the camera data by using the data of the color analyzer, improves the efficiency, improves the accuracy and stability of the obtained data and reduces the manpower and equipment cost.
Description
Technical Field
The invention relates to the field of automatic optical detection, in particular to an AOI platform-based online measurement method and device for chrominance and luminance data.
Background
With the rapid development of electronic technology, image sensing technology and computer technology, the use of Automatic Optical Inspection (AOI) technology based on Optical image sensing instead of manual visual Inspection of surface defects has gradually become an important means for surface defect detection, because such a method has the advantages of automation, non-contact, high speed, high precision, high stability, and the like. The AOI technology is also called a machine vision inspection technology or an automatic vision inspection technology, and it is widely used in manufacturing industries of flat panel displays, semiconductors, solar energy, etc. because it uses an optical method to acquire a surface state of a finished product and uses image processing to detect defects such as foreign matter or pattern abnormality.
The existing methods for measuring the chromaticity and brightness data of the panel based on the AOI platform mainly comprise the following two methods.
The first method comprises the following steps: the image data of the panel is collected by a CCD (Charge coupled device) camera, and the collected image data is imported into a drawing tool of a computer to obtain relative luminance and chrominance data. The method comprises the following steps: (11) manually opening a pulse signal generator management unit (namely a PG upper management platform), leading a pre-prepared gray scale picture to be detected (such as a picture of a pure black picture, a red picture, a blue picture and a green picture) into the pulse signal generator management unit, and controlling the pulse signal generator (namely the PG signal generator) to light the panel through the pulse signal generator management unit so as to display the gray scale picture to be detected on the panel; (12) manually controlling a color CCD camera and a black-and-white CCD camera to shoot the panel respectively to obtain image data; (13) managing the image data in a mode of manually editing names; (14) repeating the steps (11) to (13) until all the pre-prepared gray scale pictures to be detected are acquired, thereby obtaining all the image data; (15) and the acquired image data is imported into a drawing tool of a computer to obtain relative brightness and chrominance data.
The second method comprises the following steps: the method comprises the following steps of collecting chromaticity and brightness data of a panel by adopting a CA-310/CA-410 color analyzer to obtain reference brightness and chromaticity data, wherein the reference brightness and chromaticity data comprise: (21) manually opening a pulse signal generator management unit (namely a PG upper management platform) manually, leading a pre-prepared gray scale picture to be detected (such as pictures of a pure black picture, a red picture, a blue picture and a green picture) into the pulse signal generator management unit, and sending a marking picture to a panel by the pulse signal generator management unit for displaying, thereby dividing the gray scale picture to be detected into a plurality of areas; (22) manually placing an acquisition probe of a CA-310/CA-410 color analyzer in one of a plurality of divided areas to acquire the chrominance data and the luminance data of the area, and repeating the operations in sequence until the data acquisition of all the areas is finished, thereby acquiring the reference chrominance data and the luminance data of the panel corresponding to the gray scale picture to be detected; (23) manually observing a screen of the equipment to record manual data; (24) and (5) repeating the steps (21) to (23) until all the pre-prepared gray scale pictures to be detected are acquired, thereby obtaining all the reference chrominance data and all the luminance data.
However, in the first online measurement method, since the obtained image data is greatly affected by factors such as the position of the camera, the external environment, the configuration of the camera, and the exposure at the time of acquisition, the obtained image data is often inconsistent, resulting in inaccurate measured luminance/chrominance data. In the second online measurement method, because manual intervention is required in the measurement process, the measurement result cannot be kept stable, and the efficiency is also influenced by the level of manual operators, so that the measurement efficiency is low and the measurement stability is poor.
Disclosure of Invention
The embodiment of the invention provides an AOI platform-based online measurement method and device for chrominance and luminance data, and solves the problems of low measurement efficiency, inaccurate measurement data and poor stability in the prior art.
In one aspect, the embodiment of the invention provides an online measurement method for chrominance and luminance data based on an AOI platform.
Specifically, the online measurement method of chroma and brightness data based on the AOI platform comprises the following steps:
the method comprises the steps that a camera and a color analyzer are used for simultaneously collecting a to-be-tested gray scale picture automatically displayed by a to-be-tested panel, the camera obtains an ImgRGB data set, the color analyzer obtains a regXYZ data set, and the ImgRGB data set and the regXYZ data set are stored in corresponding file directories according to set data storage paths;
obtaining a conversion model corresponding to the panel model according to the ImgRGB data set and the regXYZ data set of the panel model having the same panel to be tested, and storing the conversion model into a file directory corresponding to the panel model according to a set data storage path;
converting the corresponding ImgRGB data set into an ImgXYZ numerical value by adopting a conversion model corresponding to the panel model;
extracting regXYZ values at the calibration positions from a regXYZ data set obtained by a color analyzer according to the panel model;
extracting XYZ values corresponding to the calibration positions from the ImgXYZ values, and comparing the XYZ values corresponding to the calibration positions with regXYZ values to obtain correction coefficients;
and correcting all the ImgXYZ numerical values by adopting the correction coefficient to obtain a first chromaticity brightness value ImgXYZ.
Preferably, after obtaining the first chromaticity luminance value imgixyz, the method further includes the following steps: the first chromaticity luminance value imgixyz is converted into a second chromaticity luminance value Img _ xyz by a chromaticity coordinate conversion formula. Understandably, the first chromaticity luminance value ImgXYZ is converted into a value in chromaticity coordinates, which facilitates more direct and intuitive acquisition of chromaticity luminance values directly in chromaticity coordinates.
Preferably, the correction factor is a ratio between XYZ values corresponding to the nominal position and regXYZ values.
Preferably, the step of simultaneously acquiring the to-be-tested gray scale picture automatically displayed by the to-be-tested panel through a camera and a color analyzer, the camera obtaining an ImgRGB data set, the color analyzer obtaining a regXYZ data set, and the ImgRGB data set and the regXYZ data set being stored in the corresponding file directory according to a set data storage path includes: configuring an RGB combination of the gray-scale pictures to be detected to obtain a plurality of gray-scale pictures to be detected; configuring panel information, camera acquisition information and color analyzer acquisition information of a panel to be tested; generating a corresponding file directory according to the panel information, the camera acquisition information, the color analyzer acquisition information and the data type and setting a data storage path; controlling a camera to collect a to-be-tested gray scale picture automatically displayed by a to-be-tested panel according to camera collection information, and storing an obtained ImgRGB data set into a corresponding file directory according to a set data storage path; and controlling the color analyzer to acquire the to-be-tested gray scale picture automatically displayed by the to-be-tested panel according to the information acquired by the color analyzer, and storing the acquired regXYZ data set into the corresponding file directory according to the set data storage path.
In the foregoing implementation manner of the embodiment of the present invention, firstly, the file directory includes a plurality of levels of sub-file directories, and during data management, the collected image data and chroma and luminance data can be classified and stored hierarchically according to a set order, so that a user can use the data conveniently. The specific categories and the specific layers can be opened and customized according to the requirements of the user, so that the user can store and use the data. Secondly, the user can customize the RGB combination of the gray scale picture to be detected, so that the user can formulate the gray scale picture to be detected according to the requirement. Thirdly, the data is automatically collected and recorded (namely, collected and recorded in real time) in the document in the computer when the data is collected by the camera and the color analyzer, so that the collection efficiency and the accuracy of data recording are greatly improved, the inaccuracy of the data recording caused by human errors in the recording process is avoided, and the data collection and the recording management are more intelligent. Fourthly, only the software of data management needs to be configured and the configuration information can be stored, so that the requirements of customers on data acquisition of different types of panels are met, the customizability of users is increased, the data acquisition efficiency is improved, the cost of manpower and hardware equipment is reduced, the stable reliability of acquired data is improved, and the acquisition is more flexible, efficient and controllable. Fifthly, the invention stores the data collected by the camera and the data collected by the color analyzer into the same file directory according to the set requirements, thereby realizing uniform classification and management, and improving the correction efficiency and the correction accuracy in the process of correcting the former by using the latter.
Preferably, the step of controlling the camera to acquire the to-be-tested gray scale picture automatically displayed by the to-be-tested panel according to the camera acquisition information, and storing the obtained ImgRGB data set into the corresponding file directory according to the set data storage path includes: automatically switching gray-scale pictures to be tested; controlling a camera to respectively collect panels to be tested displaying different gray scale pictures to be tested according to camera collection information to obtain an ImgRGB data set; and storing the acquired ImgRGB data set into a corresponding file directory according to a set data storage path.
In the implementation manner of the embodiment of the invention, the user-defined gray scale pictures to be detected or the standard gray scale pictures to be detected can be automatically acquired without manual participation, so that the acquisition efficiency is improved.
Preferably, the step of controlling the color analyzer to acquire the to-be-tested gray scale picture automatically displayed by the to-be-tested panel according to the information acquired by the color analyzer, and storing the obtained regXYZ data set into the corresponding file directory according to the set data storage path includes: (i) generating a marking map according to the number of the set acquisition point locations and the horizontal and vertical proportion among the acquisition point locations; (ii) displaying the identification chart on a panel to be tested, wherein the identification chart divides the panel to be tested into a plurality of areas; (iii) placing an acquisition probe of a color analyzer in one of the regions; (iv) automatically switching gray-scale pictures to be tested; (v) according to the information collected by the color analyzer, the color analyzer respectively collects regXYZ data of the panel to be tested displaying different gray scale pictures to be tested; (vi) storing the obtained regXYZ data into a corresponding file directory according to a set data storage path; (vii) and (3) placing the acquisition probe of the color analyzer to another area and repeating the steps (iv) - (vi) according to the set sequence until the regXYZ data in all the areas are acquired and stored in the corresponding file directories.
In the implementation manner of the embodiment of the invention, when the color analyzer is used for collecting the chrominance and luminance data, not only can the number of collected point positions and the arrangement (namely, the horizontal and vertical proportion) of the collected point positions be configured, but also the automatic collection of the full gray scale pictures of all the point positions is supported, so that the manual participation is not needed, and the collection efficiency is improved.
Preferably, the panel information includes a panel model, a panel number, a panel size, a resolution of the panel, and a panel position, the data type includes camera data and color analyzer data, the camera acquisition information includes acquisition frequency, acquisition delay, and auto exposure of the camera, and the color analyzer acquisition information includes acquisition frequency and acquisition delay of the color analyzer.
Preferably, the step of obtaining a conversion model corresponding to the panel model according to the ImgRGB data set and the regXYZ data set having the same panel model of the panel to be tested, and storing the conversion model into a file directory corresponding to the panel model according to the set data storage path includes: extracting an RGB data set of a calibration position from an ImgRGB data set with the same panel model; extracting regXYZ data sets of the calibration positions from regXYZ data sets with the same panel model; and carrying out one-to-one correspondence on the RGB data set of the calibration position and the regXYZ data set of the calibration position to obtain a conversion model.
Preferably, the conversion model is established by a BP neural network or a polynomial fitting method.
On the other hand, the embodiment of the invention provides an online measuring system for chroma and brightness data based on an AOI platform.
Specifically, the online measurement system for chroma and brightness data based on the AOI platform comprises:
the camera acquisition module is used for controlling the camera to acquire a to-be-tested gray scale picture automatically displayed by the to-be-tested panel according to the camera acquisition information to obtain an ImgRGB data set;
the color analyzer acquisition module is used for controlling the color analyzer to acquire the to-be-tested gray scale picture automatically displayed by the to-be-tested panel according to the information acquired by the color analyzer so as to obtain a regXYZ data set;
the data management module is used for configuring panel information, camera acquisition information and color analyzer acquisition information of a panel to be tested, generating a corresponding file directory according to the panel information, the camera acquisition information, the color analyzer acquisition information and the data type, setting a data storage path, storing an ImgRGB data set acquired by the camera acquisition module and a regXYZ data set acquired by the color analyzer acquisition module into the corresponding file directory according to the set data storage path, and storing a conversion model sent by the conversion model generation module into the file directory corresponding to the panel model according to the set data storage path;
the conversion model generation module is used for obtaining a conversion model according to the ImgRGB data set and the regXYZ data set of the panel model with the same panel to be tested;
a correction module, configured to convert the corresponding ImgRGB data set into ImgXYZ values using a conversion model corresponding to the panel model, extract XYZ values corresponding to the calibration position from the ImgXYZ values, compare the XYZ values corresponding to the calibration position with the regXYZ values extracted at the calibration position from the regXYZ data set obtained from the color analyzer according to the panel model, obtain a correction coefficient, and correct all the ImgXYZ values using the correction coefficient, to obtain a first chromaticity luminance value ImgXYZ;
and the format conversion module is used for converting the first chromaticity brightness value ImgXYZ into a second chromaticity brightness value Img _ xyLv through a chromaticity coordinate conversion formula.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
(1) the gray scale picture to be detected is automatically switched, so that the acquisition efficiency can be improved;
(2) the method corrects the ImgRGB data acquired by the camera in real time through the XYZ numerical values acquired by the color analyzer, so that an efficient measurement mode shot by the camera can be used during measurement, and the data measured by the camera is corrected by means of correction information, so that the measurement precision is greatly improved to be similar to the level of the color analyzer, the measurement is completely and automatically realized, the stability is greatly improved, the measurement is stable and reliable, and the labor cost is saved;
(3) the invention has strong universality, not only can be suitable for the chromaticity measurement of the display panel, but also has certain adaptability to other chromaticity measurements.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly described below, and it is obvious that the drawings in the description below are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a flowchart of an online measurement method for chrominance and luminance data based on an AOI platform according to an embodiment of the present invention;
fig. 2 is a flowchart of step S10 of an online measurement method for chroma and luma data based on an AOI platform according to an embodiment of the present invention.
Fig. 3 is a flowchart of step S104 of an online measurement method of chroma and luma data based on an AOI platform according to an embodiment of the present invention.
Fig. 4 is a flowchart of a step S105 of an online measurement method of chroma and luma data based on an AOI platform according to an embodiment of the present invention.
Fig. 5 is a schematic diagram of the identification map described in step S105.
Fig. 6 is a flowchart of step S20 of an online measurement method for chroma and luma data based on an AOI platform according to an embodiment of the present invention.
Fig. 7 is a schematic structural diagram of an online measurement system for chroma and luma data based on an AOI platform according to an embodiment of the present invention.
Fig. 8 is a schematic structural diagram of the camera acquisition module of fig. 7.
Fig. 9 is a schematic structural diagram of the color analyzer acquisition module in fig. 7.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be further described in detail below with reference to the drawings in the embodiments of the present invention.
The embodiment of the invention provides an AOI platform-based online measurement method for chrominance and luminance data, and referring to fig. 1, the method comprises the following steps:
step S10, a camera and a color analyzer are used for simultaneously collecting a to-be-tested gray scale picture automatically displayed by a to-be-tested panel, the camera obtains an ImgRGB data set (namely RGB data), the color analyzer obtains a regXYZ data set (namely tristimulus values), and the ImgRGB data set and the regXYZ data set are stored into corresponding file directories according to a set data storage path;
in one implementation of an embodiment of the invention, the cameras include a color CCD camera and a black and white CCD camera, and the color analyzer is a CA-310 color analyzer or a CA-410 color analyzer.
Referring to fig. 2, step S10 specifically includes the steps of:
s101, configuring an RGB combination of gray-scale pictures to be detected to obtain a plurality of gray-scale pictures to be detected;
step S102, configuring panel information, camera acquisition information and color analyzer acquisition information of a panel to be tested;
step S103, generating a corresponding file directory and setting a data storage path according to the panel information, the camera acquisition information, the color analyzer acquisition information and the data type;
step S104, controlling a camera to collect a to-be-tested gray scale picture automatically displayed by a to-be-tested panel according to camera collecting information, and storing an obtained ImgRGB data set into a corresponding file directory according to a set data storage path;
and S105, controlling the color analyzer to acquire the to-be-tested gray scale picture automatically displayed by the to-be-tested panel according to the information acquired by the color analyzer, and storing the acquired regXYZ data set into the corresponding file directory according to the set data storage path.
Further, in step S101, since the RGB combination of the gray-scale picture to be tested can be customized, the user can make the gray-scale picture to be tested as required.
In step S102, the panel information includes a panel model number, a panel size, a resolution of the panel, and a panel position. The data type comprises camera data and color analyzer data, wherein the camera acquisition information comprises acquisition frequency, acquisition time delay and automatic exposure of the camera, and the color analyzer acquisition information comprises acquisition frequency and acquisition time delay of the color analyzer. Understandably, the present invention supports a variety of configurations for collecting information.
In step S103, the file directory includes multiple levels of sub-file directories, and the collected image data and chroma-luminance data can be classified and stored hierarchically in a set order during data management, so that the user can use the data conveniently. The specific categories and the specific layers can be opened and customized according to the requirements of the user, so that the user can store and use the data. For example, the image data may be classified into a panel type, position information, and a panel number in this order, and the luminance/chrominance data may be classified into a panel type and a panel number. In addition, because the data is automatically collected and recorded (namely collected and recorded in real time) in the document in the computer when the data is collected by the camera and the color analyzer, the collection efficiency and the accuracy of data recording are greatly improved, the inaccuracy of the data recording caused by human errors in the recording process is avoided, and the data collection and the recording management are more intelligent. Moreover, only the software of data management needs to be configured and the configuration information can be stored, so that the requirements of customers on data acquisition of different types of panels are met, the customizability of users is increased, the data acquisition efficiency is improved, the cost of manpower and hardware equipment is reduced, the stability and the reliability of acquired data are improved, and the acquisition is more flexible, efficient and controllable. In addition, the invention stores the data collected by the camera and the data collected by the color analyzer into the same file directory according to the set requirements, and realizes unified classification and management, thereby improving the correction efficiency and the correction accuracy in the process of correcting the former by using the latter.
As shown in fig. 3, step S104 specifically includes:
(11) automatically switching gray-scale pictures to be tested;
(12) controlling a camera to respectively collect panels to be tested displaying different gray scale pictures to be tested according to camera collection information to obtain an ImgRGB data set;
(13) and storing the acquired ImgRGB data set into a corresponding file directory according to a set data storage path.
Regarding step S104, as another implementation manner in the embodiment of the present invention, the panel to be tested may further automatically display a specific image of the gray scale to be tested, so as to realize the acquisition of the image of the single designated gray scale. The method specifically comprises the following steps:
(11') automatically switching to a designated gray scale picture to be detected;
(21') controlling the camera to shoot the panel to be tested displaying the appointed gray scale picture to be tested according to the camera acquisition information to obtain image data;
(31') storing the obtained image data in the corresponding file directory according to the set data storage path.
In the step (11'), the implementation manner of this embodiment can communicate with the management unit of the pulse signal generator (i.e., the PG upper management platform), so as to control the signal generated by the pulse signal generator (i.e., the PG signal generator), so that the panel to be tested displays a specific gray-scale picture to be tested, and further, according to the needs of the user, only a specific certain gray-scale picture to be tested is acquired, so that the acquisition manner of this embodiment is more flexible and controllable.
As shown in fig. 4, step S105 specifically includes:
(i) generating a marking map according to the number of the set acquisition point locations and the horizontal and vertical proportion among the acquisition point locations;
(ii) displaying a marker map on a panel to be tested, wherein the marker map divides the panel to be tested into a plurality of areas;
(iii) placing an acquisition probe of a color analyzer in one of the regions;
(iv) automatically switching gray-scale pictures to be tested;
(v) controlling the color analyzer to respectively acquire regXYZ data of a panel to be tested displaying different gray scale pictures to be tested according to the information acquired by the color analyzer;
(vi) storing the obtained regXYZ data into a corresponding file directory according to a set data storage path;
(vii) and (3) placing the acquisition probe of the color analyzer to another area and repeating the steps (iv) - (vi) according to the set sequence until the regXYZ data in all the areas are acquired and stored in the corresponding file directories.
In the above implementation manner, when the color analyzer is used to collect chrominance and luminance data, not only the number of collected points and the arrangement (i.e., the horizontal-vertical ratio) of the collected points can be configured (as shown in fig. 5, there are 9 collection points on the marker map, so as to divide the panel to be measured into 9 regions, it should be noted that, when the camera collects data, the marker map is shot simultaneously, so that the calibration positions mentioned below can be obtained from the marker map), but also the automatic collection of full grayscale pictures of all the points (i.e., all the 9 collection regions) is supported, so that manual participation is not required, and the collection efficiency is improved.
It should be noted that, the automatic switching of the to-be-tested gray scale picture in step (iv) may not only achieve the acquisition of a single specified gray scale picture when the color analyzer acquires, but also achieve the automatic acquisition of all gray scale pictures when the color analyzer acquires, and the steps of the two acquisition modes are the same as those of the two acquisition modes of the camera, and are not repeated here.
Regarding step S105, as another implementation manner in the embodiment of the present invention, the color analyzer may further implement the acquisition of a full grayscale picture of a single point (i.e. a single region). The method specifically comprises the following steps:
(i'), generating a marker graph according to the number of the set acquisition point positions and the horizontal-vertical proportion among the acquisition point positions;
(ii') displaying a marker map on the panel to be tested, wherein the marker map divides the panel to be tested into a plurality of areas;
(iii') placing the acquisition probe of the color analyzer to a designated area;
(iv'), automatically switching the gray-scale picture to be tested;
(v'), according to the information collected by the color analyzer, the color analyzer collects the chroma and brightness data of the panel to be tested which displays different gray scale pictures to be tested;
(vi'), the obtained multiple groups of chroma and brightness data are stored in corresponding file directories according to the set data storage path.
In the implementation manner, when the color analyzer is used to collect the chrominance and luminance data, not only the number of collected point locations and the arrangement (i.e., the horizontal-vertical ratio) of the collected point locations can be configured (as shown in fig. 5, there are 9 collection points on the identification map, so as to divide the panel to be measured into 9 regions), but also the collection of full gray scale images of single point locations (i.e., single regions) is supported, so that the flexibility and controllability of the collection are increased.
It should be noted that, the automatic switching of the to-be-tested gray scale picture in step (iv') not only can realize the acquisition of a single designated gray scale picture during the camera acquisition, but also can realize the automatic acquisition of all gray scale pictures during the camera acquisition, and the steps of the two acquisition modes are the same as those of the two acquisition modes of the camera, and are not repeated here.
Step S20, obtaining a conversion model corresponding to the panel model according to the ImgRGB data set and regXYZ data set of the same panel model of the panel to be tested, and storing the conversion model into a file directory corresponding to the panel model according to a set data storage path;
as shown in fig. 6, step S20 specifically includes:
step S201, extracting an RGB data set of a calibration position from an ImgRGB data set with the same panel model;
step S202, extracting regXYZ data sets of the calibration positions from regXYZ data sets with the same panel models;
step S203, the RGB data set of the calibration position and the regXYZ data set of the calibration position are in one-to-one correspondence to obtain a conversion model Q1.
Specifically, a conversion model Q1 is established by adopting a BP neural network or a polynomial fitting method.
Step S30, converting the corresponding ImgRGB data set into ImgXYZ numerical value by adopting a conversion model corresponding to the panel model;
step S40, extracting regXYZ values at the calibration positions from the regXYZ dataset obtained from the color analyzer, according to the panel model;
step S50, extracting XYZ values corresponding to the calibration positions from the imgixyz values, and comparing the XYZ values corresponding to the calibration positions with the regXYZ values to obtain a correction coefficient;
and step S60, correcting all the ImgXYZ numerical values by adopting the correction coefficients to obtain a first chromaticity brightness value ImgXYZ.
For example, the ratio between the XYZ value and the regXYZ value corresponding to the calibration position in the imgixyz value can be directly calculated, and the obtained ratio is used as the correction coefficient Q2.
In step S70, the first chromaticity luminance value imgixyz is converted into the second chromaticity luminance value Img _ xyz by the chromaticity coordinate conversion formula.
The chromaticity coordinate conversion formula is as follows: x ═ X/(X + Y + Z); Y/(X + Y + Z); and Lv ═ Y.
Understandably, the first chromaticity luminance value ImgXYZ is converted into a value in chromaticity coordinates, which facilitates more direct and intuitive acquisition of chromaticity luminance values directly in chromaticity coordinates.
The embodiment of the invention has the following beneficial effects:
(1) the gray scale pictures to be detected are automatically switched, so that a plurality of self-defined gray scale pictures to be detected or a plurality of standard gray scale pictures to be detected can be automatically acquired without manual participation, and the acquisition efficiency can be improved;
(2) the method corrects the ImgRGB data acquired by the camera in real time through the XYZ numerical values acquired by the color analyzer, so that an efficient measurement mode shot by the camera can be used during measurement, and the data measured by the camera is corrected by means of correction information, so that the measurement precision is greatly improved to be similar to the level of the color analyzer, the stability of the measurement is greatly improved completely and automatically, the measurement is stable and reliable, and the labor cost is saved;
(3) the invention has strong universality, not only can be suitable for the chromaticity measurement of the display panel, but also has certain adaptability to other chromaticity measurements.
Referring to fig. 7-9, an embodiment of the present invention further provides an AOI platform-based online measurement system for chrominance and luminance data, which includes a camera acquisition module 10, a color analyzer acquisition module 20, a data management module 30, a conversion model generation module 40, a rectification module 50, and a format conversion module 60. The camera acquisition module 10 is configured to control the camera to acquire a to-be-tested gray scale picture automatically displayed by the to-be-tested panel according to the camera acquisition information, so as to obtain an ImgRGB data set. The color analyzer acquisition module 20 is configured to control the color analyzer to acquire the to-be-tested gray scale picture automatically displayed by the to-be-tested panel according to the information acquired by the color analyzer, so as to obtain a regXYZ data set. The data management module 30 is configured to configure panel information, camera acquisition information, and color analyzer acquisition information of a panel to be tested, generate a corresponding file directory according to the panel information, the camera acquisition information, the color analyzer acquisition information, and the data type, set a data storage path, store an ImgRGB data set acquired by the camera acquisition module and a regXYZ data set acquired by the color analyzer acquisition module into the corresponding file directory according to the set data storage path, and store a conversion model sent by the conversion model generation module 40 into the file directory corresponding to the panel model according to the set data storage path. The conversion model generation module 40 is configured to obtain a conversion model according to the ImgRGB dataset and the regXYZ dataset of the panel model having the same panel to be tested. The rectification module 50 is configured to convert the corresponding ImgRGB data set into ImgXYZ values using a conversion model corresponding to the panel model, extract XYZ values corresponding to the calibration positions from the ImgXYZ values, compare the XYZ values corresponding to the calibration positions with the regXYZ values extracted at the calibration positions from the regXYZ data set obtained from the color analyzer according to the panel model to obtain rectification coefficients, and rectify all the ImgXYZ values using the rectification coefficients to obtain the first chromaticity luminance value ImgXYZ. The format conversion module 60 is configured to convert the first chromaticity luminance value imgixyz into the second chromaticity luminance value Img _ xyLv by using a chromaticity coordinate conversion formula. Specifically, the camera capturing module 10 includes a PG signal generator 101, a PG upper management unit 102, an AOI image capturing unit 103, a black-and-white CCD camera 104, and a color CCD camera 105. The black-and-white CCD camera 104 and the color CCD camera 105 are used to take a picture of a gray scale to be measured displayed on the panel to be measured. The PG upper management unit 102 is connected to the PG signal generator 101, and is configured to control the PG signal generator 101 to light the panel to be tested. The PG signal generator 101 is connected to the panel to be tested. The AOI image capturing unit 103 is connected to the data management module 30, and controls the black-and-white CCD camera 104 and the color CCD camera 105 to capture images according to the acquisition information sent by the data management module 30. The color analyzer acquisition module 20 comprises a PG signal generator 201, a PG upper management unit 202, a brightness and chromaticity acquisition unit 203, and an acquisition probe 204, which are connected in sequence. The acquisition probe 204 is connected to the luminance and chrominance acquisition unit 203, and is configured to capture a to-be-detected gray-scale picture displayed by a to-be-detected panel. The brightness and chromaticity acquisition unit 203 is connected with the data management module 30, and controls the acquisition probe 204 to shoot according to the acquisition information sent by the data management module 30. The PG upper management unit 202 is connected to the PG signal generator 201, and is configured to control the PG signal generator 201 to light the panel to be tested. The PG signal generator 201 is connected to the panel to be tested.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent replacements, improvements, etc. within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An AOI platform-based online measurement method for chrominance and luminance data comprises the following steps:
the method comprises the steps that a camera and a color analyzer are used for simultaneously collecting a to-be-tested gray scale picture automatically displayed by a to-be-tested panel, the camera obtains an ImgRGB data set, the color analyzer obtains a regXYZ data set, and the ImgRGB data set and the regXYZ data set are stored in corresponding file directories according to set data storage paths;
obtaining a conversion model corresponding to the panel model according to the ImgRGB data set and the regXYZ data set having the same panel model of the panel to be tested, and storing the conversion model into the file directory corresponding to the panel model according to the set data storage path;
converting the imgRGB data set corresponding to the panel model into imgXYZ numerical values by adopting the conversion model corresponding to the panel model;
extracting regXYZ values at a calibration position from a regXYZ dataset obtained by the color analyzer according to the panel model;
extracting XYZ values corresponding to the calibration positions from the ImgXYZ values, and comparing the XYZ values corresponding to the calibration positions with regXYZ values to obtain a correction coefficient;
and correcting all the ImgXYZ numerical values by adopting the correction coefficient to obtain a first chromaticity brightness value ImgXYZ.
2. The AOI platform-based on-line measurement method for chrominance and luminance data according to claim 1, wherein after obtaining the first chrominance luminance value imgixyz, further comprising the steps of:
and converting the first chromaticity luminance value ImgXYZ into a second chromaticity luminance value Img _ xyLv by a chromaticity coordinate conversion formula.
3. The AOI platform-based on-line measurement method for chrominance luminance data according to claim 1 or 2, wherein the correction factor is a ratio between the XYZ values corresponding to the calibration position and the regXYZ values.
4. The AOI platform-based online measurement method for chrominance and luminance data according to claim 1 or 2, wherein a camera and a color analyzer are used to simultaneously acquire a to-be-tested gray scale picture automatically displayed on a to-be-tested panel, the camera obtains an ImgRGB data set, the color analyzer obtains a regXYZ data set, and the step of storing the ImgRGB data set and the regXYZ data set into corresponding file directories according to a set data storage path comprises:
configuring an RGB combination of gray scale pictures to be detected to obtain a plurality of gray scale pictures to be detected;
configuring panel information, camera acquisition information and color analyzer acquisition information of the panel to be tested;
generating a corresponding file directory according to the panel information, the camera acquisition information, the color analyzer acquisition information and the data type and setting a data storage path;
controlling the camera to collect the gray scale picture to be detected automatically displayed by the panel to be detected according to the camera collecting information, and storing the obtained ImgRGB data set into the corresponding file directory according to the set data storage path;
and controlling the color analyzer to acquire the to-be-detected gray scale picture automatically displayed by the to-be-detected panel according to the information acquired by the color analyzer, and storing the acquired regXYZ data set into the corresponding file directory according to the set data storage path.
5. The AOI platform-based online chroma and brightness data measurement method of claim 4, wherein the step of controlling a camera to collect the to-be-tested gray scale picture automatically displayed by the to-be-tested panel according to the camera collection information, and storing the obtained ImgRGB data set into the corresponding file directory according to the set data storage path comprises:
automatically switching the gray scale picture to be detected;
controlling the camera to respectively collect the panels to be tested displaying different gray scale pictures to be tested according to the camera collecting information to obtain the ImgRGB data set;
and storing the obtained ImgRGB data set into the corresponding file directory according to the set data storage path.
6. The AOI platform-based online measurement method for chrominance and luminance data according to claim 4, wherein the step of controlling the color analyzer to acquire the to-be-tested gray scale picture automatically displayed by the to-be-tested panel according to the information acquired by the color analyzer, and storing the obtained regXYZ dataset into the corresponding file directory according to the set data storage path comprises:
(i) generating a marking map according to the number of the set acquisition point locations and the horizontal and vertical proportion among the acquisition point locations;
(ii) displaying the identification chart on the panel to be tested, wherein the identification chart divides the panel to be tested into a plurality of areas;
(iii) placing an acquisition probe of the color analyzer into one of the regions;
(iv) automatically switching the gray scale picture to be detected;
(v) controlling the color analyzer to respectively acquire regXYZ data of the panel to be tested displaying different gray scale pictures to be tested according to the information acquired by the color analyzer;
(vi) the obtained regXYZ data is stored in the corresponding file directory according to the set data storage path;
(vii) (vi) placing the acquisition probe of said colour analyser in another of said regions and repeating steps (iv) - (vi) in the order set until regXYZ data within all said regions is acquired and stored in the corresponding said file directory.
7. The AOI platform-based online measurement method of chroma brightness data of claim 4, wherein the panel information comprises a panel model, a panel number, a panel size, a resolution of the panel, and a panel position, the data types comprise camera data and color analyzer data, the camera acquisition information comprises an acquisition frequency, an acquisition delay, and an automatic exposure of a camera, and the color analyzer acquisition information comprises an acquisition frequency and an acquisition delay of a color analyzer.
8. The AOI platform-based on-line measurement method for chrominance and luminance data according to claim 1 or 2, wherein the step of obtaining a conversion model corresponding to the panel model from the ImgRGB data set and the regXYZ data set having the same panel model of the panel to be tested, and storing the conversion model into the file directory corresponding to the panel model according to the set data storage path comprises:
extracting an RGB data set of a calibration position from the ImgRGB data set with the same panel model;
extracting regXYZ datasets of calibration positions in the regXYZ datasets having the same panel model;
and carrying out one-to-one correspondence on the RGB data set of the calibration position and the regXYZ data set of the calibration position to obtain the conversion model.
9. The AOI platform-based online measurement method for chroma and luma data according to claim 8, wherein the transformation model is established by a BP neural network or a polynomial fitting method.
10. An AOI platform-based online measurement system for chroma and brightness data comprises:
the camera acquisition module is used for controlling the camera to acquire a to-be-tested gray scale picture automatically displayed by the to-be-tested panel according to the camera acquisition information to obtain an ImgRGB data set;
the color analyzer acquisition module is used for controlling a color analyzer to acquire the to-be-detected gray scale picture automatically displayed by the to-be-detected panel according to information acquired by the color analyzer so as to obtain a regXYZ data set;
the data management module is used for configuring panel information, camera acquisition information and color analyzer acquisition information of the panel to be tested, generating a corresponding file directory according to the panel information, the camera acquisition information, the color analyzer acquisition information and the data type, setting a data storage path, storing the ImgRGB data set acquired by the camera acquisition module and the regXYZ data set acquired by the color analyzer acquisition module into the corresponding file directory according to the set data storage path, and storing the conversion model sent by the conversion model generation module into the file directory corresponding to the panel model according to the set data storage path;
the conversion model generation module is used for obtaining a conversion model according to the ImgRGB data set and the regXYZ data set which have the same panel model of the panel to be tested;
and the correcting module is used for converting the imgRGB data set corresponding to the panel model into imgXYZ numerical values by adopting the conversion model corresponding to the panel model, extracting XYZ numerical values corresponding to the calibration positions from the imgXYZ numerical values, comparing the XYZ numerical values corresponding to the calibration positions with regXYZ numerical values at the calibration positions extracted from the regXYZ data set obtained from the color analyzer according to the panel model to obtain correction coefficients, and correcting all the imgXYZ numerical values by adopting the correction coefficients to obtain a first chromaticity brightness value imgXYZ.
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| CN110954305A (en) * | 2019-12-10 | 2020-04-03 | 深圳市摩西尔电子有限公司 | Self-monitoring type light source chromaticity and brightness data acquisition system and control method thereof |
| CN114453280B (en) * | 2022-01-25 | 2024-03-26 | 武汉精立电子技术有限公司 | Display panel defect detection method |
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