Face recognition using Kekre's wavelets energy & performance analysis of feature vector variants

H. B. Kekre, V. Bharadi, P. Janrao, V. Singh
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引用次数: 9

Abstract

Biometric authentication technologies are based on measurable physiological or psychological characteristics of human beings. Face is one of the important physiological biometrics traits. Wavelets are useful in multi-resolution analysis of images, they are very good option for analyzing texture feature of images. In this paper a new family of wavelets called as kekre's wavelet is used for multiresolutoin analysis of face images. Different variants of feature vectors are generated and their performance for face recognition is analyzed. The analysis shows that kekre's wavelets are faster than Haar wavelets and the feature vector based on these wavelets gives good accuracy.
基于Kekre小波的人脸识别能量与特征向量变体性能分析
生物识别认证技术是基于人类可测量的生理或心理特征。人脸是重要的生理生物特征之一。小波在图像的多分辨率分析中非常有用,是分析图像纹理特征的一个很好的选择。本文提出了一种新的小波——kekre小波,用于人脸图像的多分辨率分析。生成了不同的特征向量变体,并分析了它们在人脸识别中的性能。分析表明,kekre小波比Haar小波更快,基于这些小波的特征向量具有较好的精度。
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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