基于Gabor Wigner变换特征提取技术的掌纹识别系统

Nirmala Saini, A. Sinha
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引用次数: 5

摘要

本文利用最近提出的Gabor-Wigner变换(GWT)从掌纹图像中提取特征,提出了一个掌纹识别系统。该系统的新颖之处在于GWT首次用于生物识别系统的特征提取。采用粒子群优化技术选择重要特征,降低特征向量的维数,同时保持相同的性能水平。用受试者工作特征曲线(ROC)和等误差率(EER)来评价该技术的性能
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Palmprint Recognition System Based on Gabor Wigner Transform as Feature Extraction Technique
In the present paper, a palmprint recognition system has been proposed in which the recently proposed Gabor-Wigner transform (GWT) has been used to extract the features from the palmprint images. The novelty of the system lies in the fact that GWT has been used for the first time for feature extraction in a biometric system. A particle swarm optimization technique has been used to select the significant features and to reduce the dimension of the obtained feature vectors while keeping the same level of performance. The receiver operating characteristic (ROC) curve and the equal error rate (EER) have been used to evaluate the performance of the technique
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