{"title":"构建手掌静脉提取系统","authors":"Jing-Wein Wang, Tzu-Hsiung Chen","doi":"10.1109/ICSEng.2011.61","DOIUrl":null,"url":null,"abstract":"The palm vein pattern is unique to individuality which pattern does not change over time apart from size. This feature makes it suitable for one-to-many matching, for which fingerprint and face recognition may not be robust. In this paper, we set up a creatively vein-image capturing system and present a novel framework, composed of image enhancement, feature extraction, noise removal, thinning, skeletonization, and pruning for vein pattern extraction. In our experiments, 25 persons of different ages above 20 including five girls and twenty boys, each has 20 images per person was acquired at different intervals, 10 images for left hand and 10 images for right hand. The performance of the accurate extraction rate is 93.4% on average, 94.8% on right hand and 91.9% on left hand, respectively.","PeriodicalId":387483,"journal":{"name":"2011 21st International Conference on Systems Engineering","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Building Palm Vein Capturing System for Extraction\",\"authors\":\"Jing-Wein Wang, Tzu-Hsiung Chen\",\"doi\":\"10.1109/ICSEng.2011.61\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The palm vein pattern is unique to individuality which pattern does not change over time apart from size. This feature makes it suitable for one-to-many matching, for which fingerprint and face recognition may not be robust. In this paper, we set up a creatively vein-image capturing system and present a novel framework, composed of image enhancement, feature extraction, noise removal, thinning, skeletonization, and pruning for vein pattern extraction. In our experiments, 25 persons of different ages above 20 including five girls and twenty boys, each has 20 images per person was acquired at different intervals, 10 images for left hand and 10 images for right hand. The performance of the accurate extraction rate is 93.4% on average, 94.8% on right hand and 91.9% on left hand, respectively.\",\"PeriodicalId\":387483,\"journal\":{\"name\":\"2011 21st International Conference on Systems Engineering\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-08-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 21st International Conference on Systems Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSEng.2011.61\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 21st International Conference on Systems Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSEng.2011.61","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Building Palm Vein Capturing System for Extraction
The palm vein pattern is unique to individuality which pattern does not change over time apart from size. This feature makes it suitable for one-to-many matching, for which fingerprint and face recognition may not be robust. In this paper, we set up a creatively vein-image capturing system and present a novel framework, composed of image enhancement, feature extraction, noise removal, thinning, skeletonization, and pruning for vein pattern extraction. In our experiments, 25 persons of different ages above 20 including five girls and twenty boys, each has 20 images per person was acquired at different intervals, 10 images for left hand and 10 images for right hand. The performance of the accurate extraction rate is 93.4% on average, 94.8% on right hand and 91.9% on left hand, respectively.
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