Contactless Hand Recognition Based on Distribution Estimation

2007 Biometrics Symposium Pub Date : 2007-09-01 DOI:10.1109/BCC.2007.4430547

J. Doublet, O. Lepetit, M. Revenu

引用次数: 24

Abstract

More and more research have been developed very recently for automatic hand recognition. This paper proposes a new method for contactless hand authentication in complex images with low cost devices. Our system uses skin color and hand shape information for hand detection process. Next, the palm is extracted and characterized by a bank of Gabor filters. Finally, the palm features are compared with a distribution estimation given an optimal discrimination. The experimental results present an error rate lower than 1.7% with a population of 49 people.

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基于分布估计的非接触式手部识别

近年来，对自动识别技术的研究越来越多。本文提出了一种基于低成本设备的复杂图像非接触式手部认证新方法。我们的系统使用皮肤颜色和手部形状信息进行手部检测。接下来，棕榈提取和特征的银行Gabor过滤器。最后，将手掌特征与给定最优判别的分布估计进行比较。实验结果表明，在49人的人群中，错误率低于1.7%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2007 Biometrics Symposium

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