一种新的指横纹与静脉加权融合算法  

A New Fusion Algorithm of Weighted Information from Knuckleprint and Vein

作　　者：毛贤光[1] 赖晓铮[1] 赖声礼[1] 

机构地区：[1]华南理工大学电子与信息学院,广东广州510640

出　　处：《华南理工大学学报（自然科学版）》2009年第1期74-78,共5页Journal of South China University of Technology(Natural Science Edition)

摘　　要：为解决静脉识别中静脉细节特征信息量相对较少、误拒率和误识率偏高等问题,提出了一种新的手指指横纹与静脉加权融合算法.该算法在指横纹图像预处理阶段,通过一种基于八邻域的曲线曲率法准确定位手掌基准点,并以直线拟合技术拟合手指外轮廓,进而定位指横纹感兴趣区域;在图像匹配阶段,采用Gabor滤波器提取指横纹特征信息,并将指横纹和静脉进行加权信息融合.仿真实验表明,此算法能提高系统的识别率和稳定性.In order to solve the problems of few detail information and relatively high false-rejection and falseacceptance rates in vein recognition, a new fusion algorithm of the weighted information from knuckleprint and vein is presented. In the preprocessing stage of knuckleprint, an 8-neighborhood method is used to accurately locate the basic points of palm, and the straight-line fitting technique is adopted to fit the contour of finger and to further locate the region of interest （ROI） of knuckleprint. In the matching stage of image, the characteristics of knuckleprint are extracted using a Gabor filter and is then fused with vein information via the weighted fusion technology. Simulated results indicate that the proposed algorithm improves the recognition rate and system stability.

关 键 词：静脉识别 指横纹 直线拟合 GABOR滤波器 加权信息融合 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]