采样式多通道Gabor滤波对掌纹的特征提取和分类

掌纹识别已被证实为最方便和有效的身份识别方法之一。根据掌纹的性质提出了一种掌纹方向特征提取的新方法,该方法首先利用选取掌纹中最拟合椭圆的方法寻找感兴趣区域,然后利用适应人感官系统的多通道采样式Gabor滤波器进行滤波,并提出用根据掌纹纹理和方向特性动态选取Gabor滤波器参数的方法来设计滤波器。在滤波过程中,从不同分辨率入手,利用不同方向和宽度的滤波器分别对掌纹的主线、褶皱、嵴线进行提取,在极坐标系下用改进的环行方向投影算法计算块能量,并且进行编码。经过模糊C均值聚类方法验证,结果表明,该方法对于掌纹具有很强的识别能力。

Extracting Texture Features in Palmprint via Multichannel-sampling Gabor Filters

Palmprint has been demonstrated as one of the most convenient and powerful method in personal verification.This paper proposes a new characteristic called "orientation-texture feature" in palmprint when analyzing its features.First we adopt method to extract the region of interest by tracking the optimal ellipse in the palmprint area.The method is robust to shift,rotation,stretch and other interference.Then we use multichannel-sampling Gabor filters,which simulates certain characteristics of the human visual system,to process and filter our image.The filter we design can automatically adapt to the image via selecting parameters according to our analysis of the width and orientation of the texture.In the filtering stage,we use different filters from different orientations and widths to extract features in palmprint from ridge,wrinkle,and principle line resolutions,and compute its block energy in polar axis by using an optimized ring-orientation projective algorithm.By adopting FCM clustering algorithm,demonstrate that this approach has its advantage of high verification rate in palm print.