Peg-Free Hand Features Extraction

碩士 === 中原大學 === 數學研究所 === 100 ===   Existing palm-recognition machines require using pegs for image acquisition. The main purpose of this study is to acquire high-quality and high-accuracy palm features in a peg-free environment in order to reduce environmental constraints during image acquisition....

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Main Authors: Cheng-Chi Loo, 駱成麒
Other Authors: Li-Min Liu
Format: Others
Language:zh-TW
Published: 2011
Online Access:http://ndltd.ncl.edu.tw/handle/36710958937234658959
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spelling ndltd-TW-100CYCU54790012015-10-13T20:52:04Z http://ndltd.ncl.edu.tw/handle/36710958937234658959 Peg-Free Hand Features Extraction 無錨點手掌特徵擷取 Cheng-Chi Loo 駱成麒 碩士 中原大學 數學研究所 100   Existing palm-recognition machines require using pegs for image acquisition. The main purpose of this study is to acquire high-quality and high-accuracy palm features in a peg-free environment in order to reduce environmental constraints during image acquisition. The experiments use three peg-free pictures acquired from the same individual, and use computer programs to automatically extract features on palm. Extracted features may be different due to muscle scaling and the direction fingers pointing to. The final features are derived by averaging features from those three samples. The final features are compared with the original features and the error ranges are (1) length feature error: 1.52%, (2) area feature error: 1.60%, and (3) perimeter feature error: 1.15%. Li-Min Liu 劉立民 2011 學位論文 ; thesis 26 zh-TW
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description 碩士 === 中原大學 === 數學研究所 === 100 ===   Existing palm-recognition machines require using pegs for image acquisition. The main purpose of this study is to acquire high-quality and high-accuracy palm features in a peg-free environment in order to reduce environmental constraints during image acquisition. The experiments use three peg-free pictures acquired from the same individual, and use computer programs to automatically extract features on palm. Extracted features may be different due to muscle scaling and the direction fingers pointing to. The final features are derived by averaging features from those three samples. The final features are compared with the original features and the error ranges are (1) length feature error: 1.52%, (2) area feature error: 1.60%, and (3) perimeter feature error: 1.15%.
author2 Li-Min Liu
author_facet Li-Min Liu
Cheng-Chi Loo
駱成麒
author Cheng-Chi Loo
駱成麒
spellingShingle Cheng-Chi Loo
駱成麒
Peg-Free Hand Features Extraction
author_sort Cheng-Chi Loo
title Peg-Free Hand Features Extraction
title_short Peg-Free Hand Features Extraction
title_full Peg-Free Hand Features Extraction
title_fullStr Peg-Free Hand Features Extraction
title_full_unstemmed Peg-Free Hand Features Extraction
title_sort peg-free hand features extraction
publishDate 2011
url http://ndltd.ncl.edu.tw/handle/36710958937234658959
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AT luòchéngqí wúmáodiǎnshǒuzhǎngtèzhēngxiéqǔ
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