{"title":"利用耳朵外螺旋曲线定位耳朵","authors":"Saeeduddin Ansari, Phalguni Gupta","doi":"10.1109/ICCTA.2007.82","DOIUrl":null,"url":null,"abstract":"This paper presents an efficient approach for localization of ear from an arbitrary 2D side face image with varying background. Outer helix curves of ears moving parallel to each other are used as feature for localizing ear in an image. Using Canny edge detector, edges are extracted from the whole image. These edges are segmented in convex and concave edges. From these segmented edges expected outer helix edges are determined after eliminating non-ear edges. Final outer helix edge of an ear is constructed using expected outer helix curves. Decision is made on a constructed curve whether it belongs to outer helix of ear or not. This technique is implemented on IITK, India database containing 700 samples. Accuracy of localization is more than 93%","PeriodicalId":308247,"journal":{"name":"2007 International Conference on Computing: Theory and Applications (ICCTA'07)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"85","resultStr":"{\"title\":\"Localization of Ear Using Outer Helix Curve of the Ear\",\"authors\":\"Saeeduddin Ansari, Phalguni Gupta\",\"doi\":\"10.1109/ICCTA.2007.82\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an efficient approach for localization of ear from an arbitrary 2D side face image with varying background. Outer helix curves of ears moving parallel to each other are used as feature for localizing ear in an image. Using Canny edge detector, edges are extracted from the whole image. These edges are segmented in convex and concave edges. From these segmented edges expected outer helix edges are determined after eliminating non-ear edges. Final outer helix edge of an ear is constructed using expected outer helix curves. Decision is made on a constructed curve whether it belongs to outer helix of ear or not. This technique is implemented on IITK, India database containing 700 samples. Accuracy of localization is more than 93%\",\"PeriodicalId\":308247,\"journal\":{\"name\":\"2007 International Conference on Computing: Theory and Applications (ICCTA'07)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-03-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"85\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Conference on Computing: Theory and Applications (ICCTA'07)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCTA.2007.82\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Computing: Theory and Applications (ICCTA'07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCTA.2007.82","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Localization of Ear Using Outer Helix Curve of the Ear
This paper presents an efficient approach for localization of ear from an arbitrary 2D side face image with varying background. Outer helix curves of ears moving parallel to each other are used as feature for localizing ear in an image. Using Canny edge detector, edges are extracted from the whole image. These edges are segmented in convex and concave edges. From these segmented edges expected outer helix edges are determined after eliminating non-ear edges. Final outer helix edge of an ear is constructed using expected outer helix curves. Decision is made on a constructed curve whether it belongs to outer helix of ear or not. This technique is implemented on IITK, India database containing 700 samples. Accuracy of localization is more than 93%