摘要
提出一种基于改进匹配滤波和图像梯度相关的指静脉认证算法。利用基于直方图统计法判别所获取图像是否为指静脉图,采用基于最大曲率模型的匹配滤波获取指静脉梯度图,并与登记的梯度模板做梯度相关运算,以最大互相关作为衡量两指静脉图像相似程度的度量,经阈值处理判断是否匹配。实验结果表明,该算法的误识率和拒识率分别为0.375%和1.20%,且对噪声不敏感,适合基于DSP的小型指静脉认证产品开发。
In this paper,an algorithm based on matched filtering and gradient correlation is presented for finger vein certification.A method based on histogram statistics is given,which can distinguish whether the image is finger vein or not.Matched filtering based on maximum curvature model is adopted to capture the gradient image of finger vein.Cross-correlation between two gradient images is figured out to estimate their similarity.The most correlation is threshold treated to decide whether matching or not.Experimental results show that the FAR and the FFR respectively is 0.375% and 1.20%.This algorithm is easy to realize and efficient,insensitive to noise,and its recognition rate is satisfactory,which is more suitable for the small DSP-based finger vein authentication equipments.
出处
《计算机工程》
CAS
CSCD
2013年第1期225-229,共5页
Computer Engineering
基金
广东省自然科学基金资助项目(8451008901000615)
广东省大学生创新实验基金资助项目(1055810089)
关键词
生物认证
曲率模型
直方图分析
梯度相关
指静脉认证
匹配滤波
creature authentication
curvature model
histogram analysis
gradient correlation
finger vein authentication
matched filtering
