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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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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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%.
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Li-Min Liu |
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Li-Min Liu Cheng-Chi Loo 駱成麒 |
author |
Cheng-Chi Loo 駱成麒 |
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Cheng-Chi Loo 駱成麒 Peg-Free Hand Features Extraction |
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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 |
work_keys_str_mv |
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