{"title":"多手工方法融合的腕部静脉识别","authors":"F. O. Babalola, Önsen Toygar, Y. Bi̇ti̇ri̇m","doi":"10.1109/HORA52670.2021.9461367","DOIUrl":null,"url":null,"abstract":"A wrist vein recognition system is proposed in this paper. The system combines three texture-based feature descriptors, namely, multiple filters of Binarized Statistical Image Features (M-BSIF), 2D Gabor filter, and Histogram of Gradient orientation by Decision-Level Fusion. The method was tested on two publicly available datasets obtained from FYO and PUT databases. The proposed method outperforms the individual descriptors and achieves 95.63% and 93.92% accuracies on FYO and PUT databases, respectively.","PeriodicalId":270469,"journal":{"name":"2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Wrist Vein Recognition by Fusion of Multiple Handcrafted Methods\",\"authors\":\"F. O. Babalola, Önsen Toygar, Y. Bi̇ti̇ri̇m\",\"doi\":\"10.1109/HORA52670.2021.9461367\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A wrist vein recognition system is proposed in this paper. The system combines three texture-based feature descriptors, namely, multiple filters of Binarized Statistical Image Features (M-BSIF), 2D Gabor filter, and Histogram of Gradient orientation by Decision-Level Fusion. The method was tested on two publicly available datasets obtained from FYO and PUT databases. The proposed method outperforms the individual descriptors and achieves 95.63% and 93.92% accuracies on FYO and PUT databases, respectively.\",\"PeriodicalId\":270469,\"journal\":{\"name\":\"2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HORA52670.2021.9461367\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HORA52670.2021.9461367","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Wrist Vein Recognition by Fusion of Multiple Handcrafted Methods
A wrist vein recognition system is proposed in this paper. The system combines three texture-based feature descriptors, namely, multiple filters of Binarized Statistical Image Features (M-BSIF), 2D Gabor filter, and Histogram of Gradient orientation by Decision-Level Fusion. The method was tested on two publicly available datasets obtained from FYO and PUT databases. The proposed method outperforms the individual descriptors and achieves 95.63% and 93.92% accuracies on FYO and PUT databases, respectively.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
