{"title":"Off-line signature recognition using parameterized Hough transform","authors":"T. Kaewkongka, K. Chamnongthai, B. Thipakorn","doi":"10.1109/ISSPA.1999.818209","DOIUrl":null,"url":null,"abstract":"This article describes a method of an off-line signature recognition by using the Hough transform to detect stroke lines from the signature image. The Hough transform is used to extract the parameterized Hough space from the signature skeleton as a unique characteristic feature of signatures. In the experiment, the backpropagation neural network is used as a tool to evaluate the performance of the proposed method. The system has been tested with 70 test signatures from different persons. The experimental results reveal a recognition rate 95.24%.","PeriodicalId":302569,"journal":{"name":"ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications (IEEE Cat. No.99EX359)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"46","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications (IEEE Cat. No.99EX359)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPA.1999.818209","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 46
Abstract
This article describes a method of an off-line signature recognition by using the Hough transform to detect stroke lines from the signature image. The Hough transform is used to extract the parameterized Hough space from the signature skeleton as a unique characteristic feature of signatures. In the experiment, the backpropagation neural network is used as a tool to evaluate the performance of the proposed method. The system has been tested with 70 test signatures from different persons. The experimental results reveal a recognition rate 95.24%.