Analysis of Color Component by Using Multi-Spectral Imaging Technique

• Main Authors: Lin, I-Chen, 林易辰
• Other Authors: Shyu, M. James
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/71084565013420294139

碩士 === 中國文化大學 === 資訊傳播學系 === 101 === The major task in color reproduction is to record the color characteristics and reconstruct the color correctly. However, the problem of metamerism is encountered frequently, which can be solved by multi-spectrum technique. In this study, a grating-type multi-spectral camera was used to capture color signal from 380nm to 730nm in 10 nm interval. Further analysis was performed to calculate the spectral characteristics of the captured artifacts, mainly blue-and-white porcelains and simulated aged objects. Principal component analysis (PCA) and singular value decomposition (SVD) methods were used to analyze the spectral information into linear combination of the numerical color primaries (colorants). The efficiency of these two methods was compared by various experiments to find out which method is more suitable to current configuration. CIE Color difference values were calculated to provide the index for better performance. The results indicated that SVD method performs better than PCA, and SVD method is more stability than the PCA method in reconstructing the color primary with less standard deviation in CIELAB units. Keywords: Multi-Spectral Imaging, Principal Component Analysis, Singular Value Decomposition