{"title":"使用仿射弧长的视觉签名验证","authors":"Mario E. Munich, P. Perona","doi":"10.1109/CVPR.1999.784627","DOIUrl":null,"url":null,"abstract":"Signatures can be acquired with a camera-based system with enough resolution to perform verification. This paper presents the performance of a visual-acquisition signature verification system, emphasizing on the importance of the parameterisation of the signature in order to achieve good classification results. A technique to overcome the lack of examples in order to estimate the generalization error of the algorithm is also described.","PeriodicalId":20644,"journal":{"name":"Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)","volume":"115 1","pages":"180-186 Vol. 2"},"PeriodicalIF":0.0000,"publicationDate":"1999-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Visual signature verification using affine arc-length\",\"authors\":\"Mario E. Munich, P. Perona\",\"doi\":\"10.1109/CVPR.1999.784627\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Signatures can be acquired with a camera-based system with enough resolution to perform verification. This paper presents the performance of a visual-acquisition signature verification system, emphasizing on the importance of the parameterisation of the signature in order to achieve good classification results. A technique to overcome the lack of examples in order to estimate the generalization error of the algorithm is also described.\",\"PeriodicalId\":20644,\"journal\":{\"name\":\"Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)\",\"volume\":\"115 1\",\"pages\":\"180-186 Vol. 2\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CVPR.1999.784627\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPR.1999.784627","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Visual signature verification using affine arc-length
Signatures can be acquired with a camera-based system with enough resolution to perform verification. This paper presents the performance of a visual-acquisition signature verification system, emphasizing on the importance of the parameterisation of the signature in order to achieve good classification results. A technique to overcome the lack of examples in order to estimate the generalization error of the algorithm is also described.