Digital Multi-spectral Imaging Technique

碩士 === 國立交通大學 === 光電工程研究所 === 104 === In this study, we focus on improving the multi-spectral imaging system which has been successfully developed. Firstly, in order to improve the stability of the system, we apply a new technique called weighted principal component analysis (wPCA). Implementation...

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Main Authors: Wu, Chih-Ya, 吳至雅
Other Authors: Tien, Chung-Hao
Format: Others
Language:zh-TW
Published: 2016
Online Access:http://ndltd.ncl.edu.tw/handle/98067392828286924143
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spelling ndltd-TW-104NCTU51241372017-09-06T04:22:12Z http://ndltd.ncl.edu.tw/handle/98067392828286924143 Digital Multi-spectral Imaging Technique 數位多頻譜影像技術之研究 Wu, Chih-Ya 吳至雅 碩士 國立交通大學 光電工程研究所 104 In this study, we focus on improving the multi-spectral imaging system which has been successfully developed. Firstly, in order to improve the stability of the system, we apply a new technique called weighted principal component analysis (wPCA). Implementation of this method provides the ability in selection of extracted principal eigenvectors. The result shows the reconstructed spectra based on wPCA are significantly improved in comparison to those obtained from the standard PCA. Then, we propose a new experimental framework to simulate an open environment. We establish a mathematical model by giving a calibration target and controllable ambient light. The experimental result shows that the average colorimetric errors and the RMS errors are decreased by 66.54% and 47.45%. Lastly, we utilize the multi-spectral imaging technique to detect bruises on apples and also build a system that can differentiate between good apples and bad apples. The identification rate is up to 87%. Tien, Chung-Hao Chang, Shu-Wei 田仲豪 張書維 2016 學位論文 ; thesis 42 zh-TW
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 碩士 === 國立交通大學 === 光電工程研究所 === 104 === In this study, we focus on improving the multi-spectral imaging system which has been successfully developed. Firstly, in order to improve the stability of the system, we apply a new technique called weighted principal component analysis (wPCA). Implementation of this method provides the ability in selection of extracted principal eigenvectors. The result shows the reconstructed spectra based on wPCA are significantly improved in comparison to those obtained from the standard PCA. Then, we propose a new experimental framework to simulate an open environment. We establish a mathematical model by giving a calibration target and controllable ambient light. The experimental result shows that the average colorimetric errors and the RMS errors are decreased by 66.54% and 47.45%. Lastly, we utilize the multi-spectral imaging technique to detect bruises on apples and also build a system that can differentiate between good apples and bad apples. The identification rate is up to 87%.
author2 Tien, Chung-Hao
author_facet Tien, Chung-Hao
Wu, Chih-Ya
吳至雅
author Wu, Chih-Ya
吳至雅
spellingShingle Wu, Chih-Ya
吳至雅
Digital Multi-spectral Imaging Technique
author_sort Wu, Chih-Ya
title Digital Multi-spectral Imaging Technique
title_short Digital Multi-spectral Imaging Technique
title_full Digital Multi-spectral Imaging Technique
title_fullStr Digital Multi-spectral Imaging Technique
title_full_unstemmed Digital Multi-spectral Imaging Technique
title_sort digital multi-spectral imaging technique
publishDate 2016
url http://ndltd.ncl.edu.tw/handle/98067392828286924143
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