Mustafa Agil Muhamad Balbed, Sharifah Mumtazah Sy Ahmad, Asma Shakil
{"title":"基于方差分析的hmm离线签名验证系统特征分析与选择","authors":"Mustafa Agil Muhamad Balbed, Sharifah Mumtazah Sy Ahmad, Asma Shakil","doi":"10.1109/CITISIA.2009.5224240","DOIUrl":null,"url":null,"abstract":"This paper presents an analysis performance of different features in distinguishing between genuine and forged signatures for HMM based offline signature verification systems. The four offline features include pixel density, centre of gravity, distance and angle. All features considered are local in nature. The analysis technique used here is based on analysis of variance (ANOVA). Experimental results show that the combination of center of gravity and pixel density features are good for distinguishing between genuine and skilled forgeries for an HMM based offline signature verification system.","PeriodicalId":144722,"journal":{"name":"2009 Innovative Technologies in Intelligent Systems and Industrial Applications","volume":"29 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"ANOVA-based feature analysis and selection in HMM-based offline signature verification system\",\"authors\":\"Mustafa Agil Muhamad Balbed, Sharifah Mumtazah Sy Ahmad, Asma Shakil\",\"doi\":\"10.1109/CITISIA.2009.5224240\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an analysis performance of different features in distinguishing between genuine and forged signatures for HMM based offline signature verification systems. The four offline features include pixel density, centre of gravity, distance and angle. All features considered are local in nature. The analysis technique used here is based on analysis of variance (ANOVA). Experimental results show that the combination of center of gravity and pixel density features are good for distinguishing between genuine and skilled forgeries for an HMM based offline signature verification system.\",\"PeriodicalId\":144722,\"journal\":{\"name\":\"2009 Innovative Technologies in Intelligent Systems and Industrial Applications\",\"volume\":\"29 3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Innovative Technologies in Intelligent Systems and Industrial Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CITISIA.2009.5224240\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Innovative Technologies in Intelligent Systems and Industrial Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CITISIA.2009.5224240","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ANOVA-based feature analysis and selection in HMM-based offline signature verification system
This paper presents an analysis performance of different features in distinguishing between genuine and forged signatures for HMM based offline signature verification systems. The four offline features include pixel density, centre of gravity, distance and angle. All features considered are local in nature. The analysis technique used here is based on analysis of variance (ANOVA). Experimental results show that the combination of center of gravity and pixel density features are good for distinguishing between genuine and skilled forgeries for an HMM based offline signature verification system.