Off-Line Signature Verification Based on Local Structural Pattern Distribution Features

摘要：

　　Handwritten signature is a widely used biometric.The most challenging problem in automatic signature verification is to detect skilled forgery which is similar to the genuine signatures.This paper presents a novel method for extracting features for off-line signature verification.These features is based on probability distribution function,which characterizes the frequent structural patterns distribution of a signature image.Experiments were conducted on an publicly available signature database MCYT corpus.Experimental results show that the proposed method was able to improve the verification accuracy.

关键词： Off-line signature verification Pattern recognition Local structural pattern Chi-square distance

作者: Wen Jing MoHan Chen JiaXin Ren

作者单位: College of Computer Science,Chongqing University,Chongqing,400044

会议类型: 国际会议

会议名称: Chinese Conference on Pattern Recognition, CCPR(2014年全国模式识别学术会议)

会议地点: 长沙

会议语种:英文

页码: 499-507

在线出版日期: 2014-11-01（万方平台首次上网日期，不代表论文的发表时间）