基于旅客面部特征的实名制铁路车票检票身份认证算法  

Identity Authentication Algorithm for Railway Real-Name Ticket Checking System Based on the Facial Features of Passengers

作　　者：孙首群[1] 王晓东[1] 王冰[2] 刘硕研[2] 吕晓军[2] 

机构地区：[1]上海理工大学机械工程学院,上海200093 [2]中国铁道科学研究院电子计算技术研究所,北京100081

出　　处：《中国铁道科学》2013年第2期133-139,共7页China Railway Science

基　　金：国家"八六三"计划项目(2009AA11Z211);铁道部专项资金支持课题研究项目(J2011X007);上海市教委重点学科建设项目(J50503);中国铁道科学研究院行业服务技术创新项目(1151GC1103)

摘　　要：为了高效地完成实名制铁路车票的验票流程,提出1种基于旅客面部Gabor特征的身份认证算法。采用二维Gabor滤波器提取人脸图像的Gabor特征,并对这些特征进行变换和重组;对重组后得到的特征矩阵进行类内差和类间差运算,获得初始样本,并运用主成分分析法进行样本降维,构造出支持向量机分类器,从而通过支持向量机分类器实现旅客身份的认证。在F-Gnet人脸图像库上的实验结果表明,该算法的正确认证率可达94.14%,且对光照与人脸表情变化具有鲁棒性。In order to efficiently complete the checking process for real-name train tickets,an identity authentication algorithm based on the facial Gabor features of passengers was proposed.Firstly,the two dimensional Gabor filters were used to extract the Gabor features of face images,and the features were transformed and reconstructed.Secondly,the intra-personal differences and the extra-personal differences of the reconstructed feature matrix were calculated to acquire the initial samples.The dimension reduction of the initial samples was conducted with the principal component analysis（PCA）,and then the support vector machine（SVM） classifiers were established.Finally,the identity authentication of passengers was completed by SVM classifiers.The experiments demonstrate that the proposed algorithm achieves 94.14% correct identity authentication accuracy on the F-Gnet,and has the robustness to the changes of illumination and expression.

关 键 词：实名制检票 身份认证 人脸验证 支持向量机 分类器 图像处理 

分 类 号：U293.222[交通运输工程—交通运输规划与管理] TP391[交通运输工程—道路与铁道工程]