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Proceedings Paper

Classification of emerald based on multispectral image and PCA
Author(s): Weiping Yang; Dazun Zhao; Qingmei Huang; Pengyuan Ren; Jie Feng; Xiaoyan Zhang
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Paper Abstract

Traditionally, the grade discrimination and classifying of bowlders (emeralds) are implemented by using methods based on people's experiences. In our previous works, a method based on NCS(Natural Color System) color system and sRGB color space conversion is employed for a coarse grade classification of emeralds. However, it is well known that the color match of two colors is not a true "match" unless their spectra are the same. Because metameric colors can not be differentiated by a three channel(RGB) camera, a multispectral camera(MSC) is used as image capturing device in this paper. It consists of a trichromatic digital camera and a set of wide-band filters. The spectra are obtained by measuring a series of natural bowlders(emeralds) samples. Principal component analysis(PCA) method is employed to get some spectral eigenvectors. During the fine classification, the color difference and RMS of spectrum difference between estimated and original spectra are used as criterion. It has been shown that 6 eigenvectors are enough to reconstruct reflection spectra of the testing samples.

Paper Details

Date Published: 8 February 2005
PDF: 9 pages
Proc. SPIE 5637, Electronic Imaging and Multimedia Technology IV, (8 February 2005); doi: 10.1117/12.571602
Show Author Affiliations
Weiping Yang, Beijing Institute of Technology (China)
Yunnan Normal Univ. (China)
Dazun Zhao, Beijing Institute of Technology (China)
Qingmei Huang, Beijing Institute of Technology (China)
Pengyuan Ren, Beijing Institute of Technology (China)
Jie Feng, Yunnan Normal Univ. (China)
Xiaoyan Zhang, Yunnan Normal Univ. (China)


Published in SPIE Proceedings Vol. 5637:
Electronic Imaging and Multimedia Technology IV
Chung-Sheng Li; Minerva M. Yeung, Editor(s)

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