Digital Color and Spectral Imaging for Optometry Applications

• Main Authors: Chu, Chun-Hao, 竺君儫
• Other Authors: Tien, Chung-Hao
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/tfue8j

碩士 === 國立交通大學 === 光電工程研究所 === 106 === In this work, we studied the correspondence between the spectra and color infor-mation. Through the principal component analysis (PCA), we found the high dimensional spectra space can be compressed to the three dimensional color space while keeping most information. For the purpose of optometry, where the strong illumination is inappropriate for the iris imaging. We successfully reconstruct the spectral iridal imaging through the color information by mean of the PCA and least square approximation. In additional to the spectral estimation, this thesis also pioneered the possibility of head-ache classification through the color information. Since the iris color was known as an inherited trait via multiple genes. We tried to use machine learning to distinguish the cluster headache patients from the normal subjects. With preliminary headache data-base, 70% accuracy was achieved to classify the cluster patients and normal person.