Face Recognition Based on Compressed Sensing
碩士 === 國立高雄第一科技大學 === 電腦與通訊工程所 === 98 === In recent years, with progress of science and technology, personal identity and data protection becomes more important. Human face recognition that is one of the biometric identification methods has been widely used in the national safety and the government...
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ndltd-TW-098NKIT56500142016-04-20T04:17:30Z http://ndltd.ncl.edu.tw/handle/32023235954289093809 Face Recognition Based on Compressed Sensing 基於壓縮性感測之人臉辨識 Che-wei Chang 張哲維 碩士 國立高雄第一科技大學 電腦與通訊工程所 98 In recent years, with progress of science and technology, personal identity and data protection becomes more important. Human face recognition that is one of the biometric identification methods has been widely used in the national safety and the government organizations. In this thesis, we use the compressed sensing theory to develop a human face recognition system. First, the face recognition problem is transformed to L1 optimum problem. Then, two methods are applied to solve the L1 optimum problem. One is called the log barrier method which can get the optimal solution but takes longer time; the other is the iterative hard threshold(IHT) method which is an iterative method to get the approximate solution. Next, combined with four different features of face, several recognition results are gotten. The face database used in this thesis is obtained from different lighting conditions. As the results, the recognition rate of the log barrier method is better than the IHT method, but it takes longer recognition time. Chien-Cheng Tseng 曾建誠 2010 學位論文 ; thesis 67 zh-TW |
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碩士 === 國立高雄第一科技大學 === 電腦與通訊工程所 === 98 === In recent years, with progress of science and technology, personal identity and data protection becomes more important. Human face recognition that is one of the biometric identification methods has been widely used in the national safety and the government organizations. In this thesis, we use the compressed sensing theory to develop a human face recognition system. First, the face recognition problem is transformed to L1 optimum problem. Then, two methods are applied to solve the L1 optimum problem. One is called the log barrier method which can get the optimal solution but takes longer time; the other is the iterative hard threshold(IHT) method which is an iterative method to get the approximate solution. Next, combined with four different features of face, several recognition results are gotten. The face database used in this thesis is obtained from different lighting conditions. As the results, the recognition rate of the log barrier method is better than the IHT method, but it takes longer recognition time.
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Chien-Cheng Tseng |
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Chien-Cheng Tseng Che-wei Chang 張哲維 |
author |
Che-wei Chang 張哲維 |
spellingShingle |
Che-wei Chang 張哲維 Face Recognition Based on Compressed Sensing |
author_sort |
Che-wei Chang |
title |
Face Recognition Based on Compressed Sensing |
title_short |
Face Recognition Based on Compressed Sensing |
title_full |
Face Recognition Based on Compressed Sensing |
title_fullStr |
Face Recognition Based on Compressed Sensing |
title_full_unstemmed |
Face Recognition Based on Compressed Sensing |
title_sort |
face recognition based on compressed sensing |
publishDate |
2010 |
url |
http://ndltd.ncl.edu.tw/handle/32023235954289093809 |
work_keys_str_mv |
AT cheweichang facerecognitionbasedoncompressedsensing AT zhāngzhéwéi facerecognitionbasedoncompressedsensing AT cheweichang jīyúyāsuōxìnggǎncèzhīrénliǎnbiànshí AT zhāngzhéwéi jīyúyāsuōxìnggǎncèzhīrénliǎnbiànshí |
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