A Study of the Application of CIECAM02 Color Appearance Model in Color Package Printing Industry

碩士 === 世新大學 === 圖文傳播暨數位出版學研究所(含碩專班) === 96 === Often It happens in package printing industry that the same spot colors, printed against different backgrounds (including various relative luminances, background-colors) visually mismatch to each other. Therefore it is needed to have a better solution t...

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Bibliographic Details
Main Authors: Chih-Chun Hsiao, 蕭智鈞
Other Authors: Mei-Chun Lo
Format: Others
Language:zh-TW
Published: 2008
Online Access:http://ndltd.ncl.edu.tw/handle/h93p9t
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Summary:碩士 === 世新大學 === 圖文傳播暨數位出版學研究所(含碩專班) === 96 === Often It happens in package printing industry that the same spot colors, printed against different backgrounds (including various relative luminances, background-colors) visually mismatch to each other. Therefore it is needed to have a better solution than only just colorimetrically using measuring instruments such as spectro-colorimeters or spectrophotometers to decide the acceptability standards or quantization data. In this research, as considered in the application of package printing, the CIECAM02 color appearance model was used to approximate corresponding colors, for different hue angles and lightness, among various relative luminaces of gray backgrounds (i.e. Yb values).. A set of psychophysical experiments, using a paired-comparison method, was conducted to evaluate the performance of CIECAM02 model. An sRGB format of LCD was used as a soft-proof for displaying those simulated images/colors tested. Simultaneously, observers were instructed to respectively adjust three color bars of RGB channels to produce every corresponding color under a test background which would match the color appearance of its corresponding reference color under the reference viewing condition/gray-background considered for each color. The results showed the CIECAM02 model performed well in most of colors except those with high lightness. Therefore, modifications were made by using a regression approach. As results, by combined CIECAM02 with the regression model derived, improvements were made on the predictions of those high-lightness colors.