| 基于独立分量分析的虹膜识别方法 |
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| 引用本文： | 黄雅平,罗四维,陈恩义.基于独立分量分析的虹膜识别方法[J].计算机研究与发展,2003,40(10):1451-1457. |
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| 作者姓名： | 黄雅平 罗四维 陈恩义 |
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| 作者单位： | 1. 北京交通大学计算机科学与技术系,北京,100044
2. 清华大学计算机科学与技术系,北京,100084 |
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| 基金项目： | 高等学校博士学科点专项科研基金 ( 2 0 0 2 0 0 0 40 2 0 ) |
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| 摘 要： | 虹膜识别技术作为一种生物识别手段，具有惟一性、稳定性和安全性等优点，从而成为当前模式识别和机器学习领域的一个研究热点．提出了一种新的虹膜识别方法，该方法利用独立分量分析(ICA)提取虹膜的纹理特征，并采用竞争学习机制进行识别．实验结果证明了该方法的有效性和对环境的适应性，在图像模糊、噪声干扰等不利条件下，仍然能够正确识别．
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| 关 键 词： | 虹膜识别 独立分量分析 竞争学习 |
An Iris Recognition Algorithm Based on Independent Component Analysis |
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| HUANG Ya Ping ,LUO Si Wei ,and CHEN En Yi.An Iris Recognition Algorithm Based on Independent Component Analysis[J].Journal of Computer Research and Development,2003,40(10):1451-1457. |
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| Authors: | HUANG Ya Ping LUO Si Wei and CHEN En Yi |
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| Affiliation: | HUANG Ya Ping 1,LUO Si Wei 1,and CHEN En Yi 2 1 |
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| Abstract: | Iris recognition, as a biometric technology, has great mathematical advantages, such as variability, stability and security, thus becoming a hot topic in pattern recognition and machine learning research area A new Iris recognition algorithm is proposed, which adopts independent component analysis (ICA) to extract Iris texture feature and adopts competitive learning mechanism to recognize Experimental results show that the algorithm is efficient and adaptive to environment, e g it works well even for blurred Iris image and interference of noises |
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| Keywords: | Iris recognition independent component analysis competitive learning |
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