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机构地区:[1]National Laboratory of Color Science and Engineering,Beijing Institute of Technology [2]School of Light Industry and Chemical Engineering,Dalian Polytechnic University
出 处:《Journal of Beijing Institute of Technology》2013年第1期101-105,共5页北京理工大学学报(英文版)
基 金:Supported by the National Natural Science Foundation of China(61078048)
摘 要:Color appearance model (CAM) can be used to determine the required colors for repro- duction across changes in cross-media. CIECAM02 color appearance model prediction is implemen- ted by artificial neural networks in this paper, which includes forward and reversed prediction. 1333 color samples as training samples and other 1332 color samples as test samples are selected in the Chinese color system. In order to test the prediction accuracy of neural networks after simulation of CIECAM02 color appearance model, the color-difference formula can be used for the evaluation of forward and reversed models. Results have shown that BP neural-network has acceptable accuracy in simulation of CIECAM02 color appearance model for colors of Chinese color system.Color appearance model (CAM) can be used to determine the required colors for repro- duction across changes in cross-media. CIECAM02 color appearance model prediction is implemen- ted by artificial neural networks in this paper, which includes forward and reversed prediction. 1333 color samples as training samples and other 1332 color samples as test samples are selected in the Chinese color system. In order to test the prediction accuracy of neural networks after simulation of CIECAM02 color appearance model, the color-difference formula can be used for the evaluation of forward and reversed models. Results have shown that BP neural-network has acceptable accuracy in simulation of CIECAM02 color appearance model for colors of Chinese color system.
关 键 词:CIECAM02 color appearance model Chinese color system BP neural-network
分 类 号:TS193.13[轻工技术与工程—纺织化学与染整工程]
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