| 主成分分析法在掌纹图像识别中的应用 |
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| 引用本文： | 蔡平胜,闫乐林.主成分分析法在掌纹图像识别中的应用[J].计算机系统应用,2010,19(9):187-190. |
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| 作者姓名： | 蔡平胜 闫乐林 |
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| 作者单位： | 1. 山东教育学院,计算机科学与技术系,山东,济南,250013
2. 山东教育学院,计算机科学与技术系,山东,济南,250013;北京邮电大学,信息与通信工程学院,北京,100876 |
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| 基金项目： | 国家自然科学基金(60743007);山东省教育厅自然科学基金(J07WJ16) |
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| 摘 要： | 掌纹识别技术是生物特征识别领域的又一新兴技术,在网络安全、身份鉴别等方面有广阔的应用前景。将主成分分析法应用于掌纹图像的特征提取,阐释了传统主成分分析与加权主成分分析在处理掌纹图像时的差异,并在不同数据库上对两种方法进行了实验,结果表明传统主成分分析比加权主成分分析有更高的识别率以及加权主成分分析能够削弱光照对识别结果的影响。
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| 关 键 词： | 生物特征识别 掌纹识别 主成分分析 加权主成分分析 |
| 收稿时间： | 2010/3/15 0:00:00 |
| 修稿时间： | 5/1/2010 12:00:00 AM |
Application of Principal Component Analysis to Palmprint Images Recognition |
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| CAI Ping-Sheng and YAN Le-Lin.Application of Principal Component Analysis to Palmprint Images Recognition[J].Computer Systems& Applications,2010,19(9):187-190. |
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| Authors: | CAI Ping-Sheng and YAN Le-Lin |
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| Affiliation: | 1.Department of Computer Science and Technique, Shandong Institute of Eduction, Jinan 250013, China; 2.Information ＆ Telecommunication Engineering School, Beijing University of Posts and Telecommunications, Beijing 100876, China ) |
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| Abstract: | The palmprint recognition is a new biometric technology, which has a good prospect of applications in the areas of network security, identity authentication etc. In this paper, the principal component analysis method is applied to palmprint image feature extraction, and the differences between the traditional principal component analysis(PCA) and the weighted principal component analysis(WPCA) in addressing the palmprint image are explained. According to the experimental results of two methods on two databases, PCA has a higher precision of palmprint recognition than WPCA, and the affection of light condition is weakened by WPCA. |
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| Keywords: | biometric recognition parmprint recognition PCA WPCA |
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