On the use of spectral minutiae in high-resolution palmprint recognition

2013 International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2013-04-04 DOI:10.1109/IWBF.2013.6547308

Ruifang Wang, R. Veldhuis, D. Ramos, L. Spreeuwers, Julian Fierrez, Hai-yun Xu

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引用次数: 4

Abstract

The spectral minutiae representation has been proposed as a novel method to minutiae-based fingerprint recognition, which can handle minutiae translation and rotation and improve matching speed. As high-resolution palmprint recognition is also mainly based on minutiae sets, we apply spectral minutiae representation to palmprints and implement spectral minutiae based matching. We optimize key parameters for the method by experimental study on the characteristics of spectral minutiae using both fingerprints and palmprints. However, experimental results show that spectral minutiae representation has much worse performance for palmprints than that for fingerprints. EER 15.89% and 14.2% are achieved on the public high-resolution palmprint database THUPALMLAB using location-based spectral minutiae representation (SML) and the complex spectral minutiae representation (SMC) respectively while 5.1% and 3.05% on FVC2002 DB2A fingerprint database. Based on statistical analysis, we find the worse performance for palmprints mainly due to larger non-linear distortion and much larger number of minutiae.

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光谱细节在高分辨率掌纹识别中的应用

谱特征表示是一种基于特征的指纹识别新方法，可以处理特征的平移和旋转，提高匹配速度。由于高分辨率掌纹识别也主要基于特征集，我们将光谱特征表示应用于掌纹，实现基于光谱特征的匹配。通过对指纹和掌纹光谱细节特征的实验研究，优化了该方法的关键参数。然而，实验结果表明，掌纹的光谱细节表征性能远不如指纹。基于位置的光谱细节表示(SML)和复杂光谱细节表示(SMC)在公共高分辨率掌纹数据库THUPALMLAB上的识别率分别达到15.89%和14.2%，而在FVC2002 DB2A指纹数据库上的识别率分别为5.1%和3.05%。基于统计分析，我们发现掌纹的性能较差主要是由于较大的非线性失真和大量的细节。

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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2013 International Workshop on Biometrics and Forensics (IWBF)

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