{"title":"银行安全系统采用手势识别","authors":"Ashutosh Gupta, Yogesh Kumar, Sanal Malhotra","doi":"10.1109/RDCAPE.2015.7281403","DOIUrl":null,"url":null,"abstract":"This paper presents hand gesture analysis for human-security system interaction. Hand gesture recognition consisted of five processes such as image acquisition, skin color information for recognizing hand gesture which is obtained from the arm region of the hand, background removal, canny edge detection and contour detection. This proposed system is used for the banking security and can be used for companies or at personal secured places for security purposes. We have evaluated an improved hand gesture recognition using web camera and successfully implemented a prototype for security in bank from robbery which is having a detection accuracy rate of 95.7%.","PeriodicalId":403256,"journal":{"name":"2015 International Conference on Recent Developments in Control, Automation and Power Engineering (RDCAPE)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Banking security system using hand gesture recognition\",\"authors\":\"Ashutosh Gupta, Yogesh Kumar, Sanal Malhotra\",\"doi\":\"10.1109/RDCAPE.2015.7281403\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents hand gesture analysis for human-security system interaction. Hand gesture recognition consisted of five processes such as image acquisition, skin color information for recognizing hand gesture which is obtained from the arm region of the hand, background removal, canny edge detection and contour detection. This proposed system is used for the banking security and can be used for companies or at personal secured places for security purposes. We have evaluated an improved hand gesture recognition using web camera and successfully implemented a prototype for security in bank from robbery which is having a detection accuracy rate of 95.7%.\",\"PeriodicalId\":403256,\"journal\":{\"name\":\"2015 International Conference on Recent Developments in Control, Automation and Power Engineering (RDCAPE)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Recent Developments in Control, Automation and Power Engineering (RDCAPE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RDCAPE.2015.7281403\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Recent Developments in Control, Automation and Power Engineering (RDCAPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RDCAPE.2015.7281403","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Banking security system using hand gesture recognition
This paper presents hand gesture analysis for human-security system interaction. Hand gesture recognition consisted of five processes such as image acquisition, skin color information for recognizing hand gesture which is obtained from the arm region of the hand, background removal, canny edge detection and contour detection. This proposed system is used for the banking security and can be used for companies or at personal secured places for security purposes. We have evaluated an improved hand gesture recognition using web camera and successfully implemented a prototype for security in bank from robbery which is having a detection accuracy rate of 95.7%.