{"title":"基于距离变换和模板匹配的侧脸图像耳朵定位","authors":"S. Prakash, U. Jayaraman, P. Gupta","doi":"10.1109/IPTA.2008.4743786","DOIUrl":null,"url":null,"abstract":"The paper presents an efficient distance transform and template based technique for automatic ear localization from a side face image. The technique first segments skin and non-skin regions in the face and then uses template based approach to find the ear location within the skin regions. Ear detection proceeds as follows. First, edge map of the skin regions is computed and further processed to eliminate the spurious edges based on length and curvature based criterion. After getting the clean edge map, its distance transform is obtained on which ear localization process is carried out. Distance transform image of the edge map of an off-line created ear template is employed for ear localization. A Zernike moment based shape descriptor is used to verify the detections. The technique is tested on IIT Kanpur ear database which contains around 150 ear images and found to be giving 95.2% accuracy.","PeriodicalId":384072,"journal":{"name":"2008 First Workshops on Image Processing Theory, Tools and Applications","volume":"86 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"39","resultStr":"{\"title\":\"Ear Localization from Side Face Images using Distance Transform and Template Matching\",\"authors\":\"S. Prakash, U. Jayaraman, P. Gupta\",\"doi\":\"10.1109/IPTA.2008.4743786\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents an efficient distance transform and template based technique for automatic ear localization from a side face image. The technique first segments skin and non-skin regions in the face and then uses template based approach to find the ear location within the skin regions. Ear detection proceeds as follows. First, edge map of the skin regions is computed and further processed to eliminate the spurious edges based on length and curvature based criterion. After getting the clean edge map, its distance transform is obtained on which ear localization process is carried out. Distance transform image of the edge map of an off-line created ear template is employed for ear localization. A Zernike moment based shape descriptor is used to verify the detections. The technique is tested on IIT Kanpur ear database which contains around 150 ear images and found to be giving 95.2% accuracy.\",\"PeriodicalId\":384072,\"journal\":{\"name\":\"2008 First Workshops on Image Processing Theory, Tools and Applications\",\"volume\":\"86 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"39\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 First Workshops on Image Processing Theory, Tools and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPTA.2008.4743786\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 First Workshops on Image Processing Theory, Tools and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPTA.2008.4743786","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ear Localization from Side Face Images using Distance Transform and Template Matching
The paper presents an efficient distance transform and template based technique for automatic ear localization from a side face image. The technique first segments skin and non-skin regions in the face and then uses template based approach to find the ear location within the skin regions. Ear detection proceeds as follows. First, edge map of the skin regions is computed and further processed to eliminate the spurious edges based on length and curvature based criterion. After getting the clean edge map, its distance transform is obtained on which ear localization process is carried out. Distance transform image of the edge map of an off-line created ear template is employed for ear localization. A Zernike moment based shape descriptor is used to verify the detections. The technique is tested on IIT Kanpur ear database which contains around 150 ear images and found to be giving 95.2% accuracy.