基于小波变换和规范型纹理描述子的人耳识别

 在带有角度的人耳图像上提取有效特征一直是人耳识别的难点.本文提出一种基于Haar小波变换和规范型纹理描述子的人耳识别方法,即先对人耳图像进行Haar小波变换,然后利用更加合理的规范型纹理描述子,同时结合分块与多分辨率思想,共同描述经Haar小波变换后人耳子图像的纹理特征,最后用最近邻分类器进行分类识别.实验结果表明,Haar小波变换可以有效增强图像纹理基元的有效信息;利用规范型纹理描述子提取特征不仅速度快,而且具有很强的鲁棒性,尤其与分块、多分辨率方法相结合时,效果更为显著,明显优于经典的PCA和KPCA方法.

Ear Recognition Based on Wavelet Transform and Uniform Texture Descriptors

It has been an intractable problem for ear recognition to extract effective features from the posed ear images.This paper proposes a novel method based on Haar wavelet transform and uniform texture descriptors.Firstly,ear images are decomposed by Haar wavelet transform.Then using more rational uniform texture descriptors and combining simultaneously with block-based method and multi-resolution method describe together the texture features of ear sub-images transformed by Haar wavelet.Finally,the texture fea...