Zhenmin Zhu, Ruichao Song, Hui Luo, Jun Xu, Shiming Chen
{"title":"基于数字传感器和LED阵列光源的彩色视觉系统色彩校正","authors":"Zhenmin Zhu, Ruichao Song, Hui Luo, Jun Xu, Shiming Chen","doi":"10.1155/2016/7467165","DOIUrl":null,"url":null,"abstract":"Color measurement by the colorized vision system is a superior method to achieve the evaluation of color objectively and continuously. However, the accuracy of color measurement is influenced by the spectral responses of digital sensor and the spectral mismatch of illumination. In this paper, two-color vision system illuminated by digital sensor and LED array, respectively, is presented. The Polynomial-Based Regression method is applied to solve the problem of color calibration in the sRGB and color spaces. By mapping the tristimulus values from RGB to sRGB color space, color difference between the estimated values and the reference values is less than . Additionally, the mapping matrix has proved a better performance in reducing the color difference, and it is introduced subsequently into the colorized vision system proposed for a better color measurement. Necessarily, the printed matter of clothes and the colored ceramic tile are chosen as the application experiment samples of our colorized vision system. As shown in the experimental data, the average color difference of images is less than . It indicates that a better performance of color measurement is obtained via the colorized vision system proposed.","PeriodicalId":43355,"journal":{"name":"Active and Passive Electronic Components","volume":"2016 1","pages":"1-16"},"PeriodicalIF":1.3000,"publicationDate":"2016-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2016/7467165","citationCount":"4","resultStr":"{\"title\":\"Color Calibration for Colorized Vision System with Digital Sensor and LED Array Illuminator\",\"authors\":\"Zhenmin Zhu, Ruichao Song, Hui Luo, Jun Xu, Shiming Chen\",\"doi\":\"10.1155/2016/7467165\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Color measurement by the colorized vision system is a superior method to achieve the evaluation of color objectively and continuously. However, the accuracy of color measurement is influenced by the spectral responses of digital sensor and the spectral mismatch of illumination. In this paper, two-color vision system illuminated by digital sensor and LED array, respectively, is presented. The Polynomial-Based Regression method is applied to solve the problem of color calibration in the sRGB and color spaces. By mapping the tristimulus values from RGB to sRGB color space, color difference between the estimated values and the reference values is less than . Additionally, the mapping matrix has proved a better performance in reducing the color difference, and it is introduced subsequently into the colorized vision system proposed for a better color measurement. Necessarily, the printed matter of clothes and the colored ceramic tile are chosen as the application experiment samples of our colorized vision system. As shown in the experimental data, the average color difference of images is less than . It indicates that a better performance of color measurement is obtained via the colorized vision system proposed.\",\"PeriodicalId\":43355,\"journal\":{\"name\":\"Active and Passive Electronic Components\",\"volume\":\"2016 1\",\"pages\":\"1-16\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2016-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1155/2016/7467165\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Active and Passive Electronic Components\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1155/2016/7467165\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Active and Passive Electronic Components","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2016/7467165","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Color Calibration for Colorized Vision System with Digital Sensor and LED Array Illuminator
Color measurement by the colorized vision system is a superior method to achieve the evaluation of color objectively and continuously. However, the accuracy of color measurement is influenced by the spectral responses of digital sensor and the spectral mismatch of illumination. In this paper, two-color vision system illuminated by digital sensor and LED array, respectively, is presented. The Polynomial-Based Regression method is applied to solve the problem of color calibration in the sRGB and color spaces. By mapping the tristimulus values from RGB to sRGB color space, color difference between the estimated values and the reference values is less than . Additionally, the mapping matrix has proved a better performance in reducing the color difference, and it is introduced subsequently into the colorized vision system proposed for a better color measurement. Necessarily, the printed matter of clothes and the colored ceramic tile are chosen as the application experiment samples of our colorized vision system. As shown in the experimental data, the average color difference of images is less than . It indicates that a better performance of color measurement is obtained via the colorized vision system proposed.
期刊介绍:
Active and Passive Electronic Components is an international journal devoted to the science and technology of all types of electronic components. The journal publishes experimental and theoretical papers on topics such as transistors, hybrid circuits, integrated circuits, MicroElectroMechanical Systems (MEMS), sensors, high frequency devices and circuits, power devices and circuits, non-volatile memory technologies such as ferroelectric and phase transition memories, and nano electronics devices and circuits.