基于2DFLD的手背静脉识别算法  

Palm-dorsa vein recognition based on two-dimensional Fisher linear discriminant

作　　者：苑玮琦[1,2] 王爇[1,2] 孙书会[1] 

机构地区：[1]沈阳工业大学视觉检测技术研究所,沈阳110178 [2]沈阳工业大学信息科学与工程学院,沈阳110870

出　　处：《计算机应用》2010年第3期646-649,共4页journal of Computer Applications

摘　　要：手背静脉识别技术采用非接触式,为了避免在采集图片时由于手背的旋转和平移给识别带来干扰,提出一种手背静脉有效区域的定位方法,在手背截取出一个包含静脉信息最多的矩形。该算法主要利用基于不变特征点的图像定位方法来寻找手背外侧边缘的特征点,然后定位分割出手背静脉有效区域的图像。实验证明该算法具有自适应性,定位准确,速度快。由于经典的Fisher线性判别算法类内散度矩阵通常会是奇异的,提出一种基于二维Fisher线性判别(2DFLD)的手背静脉识别方法。该方法直接进行图像矩阵投影,避免高维运算。对于手背静脉图像库,用2DFLD方法提取静脉特征空间,再将测试图像投影到该特征子空间上,最后用最近邻欧氏距离方法进行匹配。实验结果表明,该方法识别率达98%。The palm-dorsa vein recognition uses non-contact technology.A locating algorithm was presented in order to avoid the interference brought by the rotation and translation of the palm-dorsa when collecting pictures.This method ultimately intercepted a rectangle on the palm-dorsa containing the information of vein as much as it can.The feature points of palm-dorsa edge were located by the location method based on unchanged feature points,and then the effective region was obtained.Experimental results show that the algorithm is self-adaptive,accurate and fast.To solve the problem that the within-class scatter matrix is always singular based on Fisher Linear Discriminant（FLD）,a new way based on Two-Dimensional FLD（2DFLD）was used in the palm-dorsa vein recognition.The image matrix was directly projected to avoid high dimension operation.In the experiments,2DFLD was applied to extract the vein feature subspace from palm-dorsa vein database.The test sample images to be recognized were projected on small dimension subspace.Lastly,a nearest neighbor classifier for palm-dorsa vein matching based on Euclidean distance was used and the recognition rate reached as high as 98%.

关 键 词：手背静脉识别 图像定位 有效区域 二维Fisher线性判别 最近邻分类器 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]