{"title":"Constructing a high performance signature verification system using a GA method","authors":"Xuhua Yang, T. Furuhashi, K. Obata, Y. Uchikawa","doi":"10.1109/ANNES.1995.499465","DOIUrl":null,"url":null,"abstract":"To realize a high-peformance automatic signature verification system, it is necessary that the selected features are potentially difficult to imitate. One of the advantages of online signature verification is that the virtual strokes which are left in the pen-up situation can be obtained. These virtual strokes can be memorized by the computer but are invisible to humans. So there is little possibility of imitating these strokes deliberately. The features included in such strokes are expected to realize a high verification performance. This paper proposes to find the optimal features for signature verification from these virtual strokes by using a genetic algorithm (GA). Experiments are carried out to show the effectiveness of the new method.","PeriodicalId":123427,"journal":{"name":"Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ANNES.1995.499465","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 27
Abstract
To realize a high-peformance automatic signature verification system, it is necessary that the selected features are potentially difficult to imitate. One of the advantages of online signature verification is that the virtual strokes which are left in the pen-up situation can be obtained. These virtual strokes can be memorized by the computer but are invisible to humans. So there is little possibility of imitating these strokes deliberately. The features included in such strokes are expected to realize a high verification performance. This paper proposes to find the optimal features for signature verification from these virtual strokes by using a genetic algorithm (GA). Experiments are carried out to show the effectiveness of the new method.