{"title":"基于Hausdorff-Shape上下文的人脸验证","authors":"Rerkchai Fooprateepsiri, W. Kurutach","doi":"10.1109/CAR.2009.83","DOIUrl":null,"url":null,"abstract":"This paper proposes a highly robust method for face recognition and authentication. Techniques introduced in this work are composed of two stages. Firstly, the feature of face is to be detected by the principle of Trace Transform. Then, in the second stage, the Hausdorff distance and Shape Context are employed to measure and determine of similarity between models and test images. From the experimental result of 6,325 images, the average of accuracy rate is higher than 84%.","PeriodicalId":320307,"journal":{"name":"2009 International Asia Conference on Informatics in Control, Automation and Robotics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Face Verification base-on Hausdorff-Shape Context\",\"authors\":\"Rerkchai Fooprateepsiri, W. Kurutach\",\"doi\":\"10.1109/CAR.2009.83\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a highly robust method for face recognition and authentication. Techniques introduced in this work are composed of two stages. Firstly, the feature of face is to be detected by the principle of Trace Transform. Then, in the second stage, the Hausdorff distance and Shape Context are employed to measure and determine of similarity between models and test images. From the experimental result of 6,325 images, the average of accuracy rate is higher than 84%.\",\"PeriodicalId\":320307,\"journal\":{\"name\":\"2009 International Asia Conference on Informatics in Control, Automation and Robotics\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Asia Conference on Informatics in Control, Automation and Robotics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAR.2009.83\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Asia Conference on Informatics in Control, Automation and Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAR.2009.83","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper proposes a highly robust method for face recognition and authentication. Techniques introduced in this work are composed of two stages. Firstly, the feature of face is to be detected by the principle of Trace Transform. Then, in the second stage, the Hausdorff distance and Shape Context are employed to measure and determine of similarity between models and test images. From the experimental result of 6,325 images, the average of accuracy rate is higher than 84%.
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