关于签名识别中人类评分的评价

D. Morocho, J. Hernandez-Ortega, A. Morales, Julian Fierrez, J. Ortega-Garcia
{"title":"关于签名识别中人类评分的评价","authors":"D. Morocho, J. Hernandez-Ortega, A. Morales, Julian Fierrez, J. Ortega-Garcia","doi":"10.1109/CCST.2016.7815681","DOIUrl":null,"url":null,"abstract":"This work explores the human ability to recognize the authenticity of signatures. We use crowdsourcing to analyze the different factors affecting the performance of humans without Forensic Document Examiner experience. We present different experiments according to different scenarios in which laymen, people without Forensic Document Examiner experience, provide similarity measures related with the perceived authenticity of a given signature. The human responses are used to analyze the performance of humans according to each of the scenarios and main factors. The experiments comprise 240 signatures from BiosecurlD public database and responses from more than 400 people. The results shows the difficulties associated to these tasks, with special attention to the false acceptance of forgeries with rates ranging from 50% to 75%. The results suggest that human recognition abilities in this scenario are strongly dependent on the characteristics considered and the signature at hand. Finally the combination of human ratings clearly outperfoms the individual performance and and a state-of-the-art automatic signature verification system.","PeriodicalId":6510,"journal":{"name":"2016 IEEE International Carnahan Conference on Security Technology (ICCST)","volume":"1 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"On the evaluation of human ratings for signature recognition\",\"authors\":\"D. Morocho, J. Hernandez-Ortega, A. Morales, Julian Fierrez, J. Ortega-Garcia\",\"doi\":\"10.1109/CCST.2016.7815681\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work explores the human ability to recognize the authenticity of signatures. We use crowdsourcing to analyze the different factors affecting the performance of humans without Forensic Document Examiner experience. We present different experiments according to different scenarios in which laymen, people without Forensic Document Examiner experience, provide similarity measures related with the perceived authenticity of a given signature. The human responses are used to analyze the performance of humans according to each of the scenarios and main factors. The experiments comprise 240 signatures from BiosecurlD public database and responses from more than 400 people. The results shows the difficulties associated to these tasks, with special attention to the false acceptance of forgeries with rates ranging from 50% to 75%. The results suggest that human recognition abilities in this scenario are strongly dependent on the characteristics considered and the signature at hand. Finally the combination of human ratings clearly outperfoms the individual performance and and a state-of-the-art automatic signature verification system.\",\"PeriodicalId\":6510,\"journal\":{\"name\":\"2016 IEEE International Carnahan Conference on Security Technology (ICCST)\",\"volume\":\"1 1\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Carnahan Conference on Security Technology (ICCST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCST.2016.7815681\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Carnahan Conference on Security Technology (ICCST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCST.2016.7815681","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

这个作品探讨了人类识别签名真实性的能力。我们使用众包来分析在没有法医文件审查员经验的情况下影响人类表现的不同因素。我们根据不同的场景提出了不同的实验,在这些场景中,外行人,没有法医文件审查员经验的人,提供了与给定签名的感知真实性相关的相似性测量。人的反应被用来根据每个场景和主要因素分析人的表现。这些实验包括来自BiosecurlD公共数据库的240个签名和400多人的回复。结果显示了与这些任务相关的困难,特别注意伪造品的错误接受率从50%到75%不等。结果表明,在这种情况下,人类的识别能力强烈依赖于所考虑的特征和手头的签名。最后,人类评分的组合明显优于个人表现和最先进的自动签名验证系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
On the evaluation of human ratings for signature recognition
This work explores the human ability to recognize the authenticity of signatures. We use crowdsourcing to analyze the different factors affecting the performance of humans without Forensic Document Examiner experience. We present different experiments according to different scenarios in which laymen, people without Forensic Document Examiner experience, provide similarity measures related with the perceived authenticity of a given signature. The human responses are used to analyze the performance of humans according to each of the scenarios and main factors. The experiments comprise 240 signatures from BiosecurlD public database and responses from more than 400 people. The results shows the difficulties associated to these tasks, with special attention to the false acceptance of forgeries with rates ranging from 50% to 75%. The results suggest that human recognition abilities in this scenario are strongly dependent on the characteristics considered and the signature at hand. Finally the combination of human ratings clearly outperfoms the individual performance and and a state-of-the-art automatic signature verification system.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
AI facial recognition and biometric detection: balancing consumer rights and corporate interests Radar Error Calculation and Correction System Based on ADS-B and Business Intelligent Tools MIMO Cable Guided Radar Assessing the common authorship of a set of questioned signature images A fuzzy interval valued fusion technique for multi-modal 3D face recognition
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1