{"title":"一种基于轮廓和特征皮肤识别的人脸检测方法","authors":"M. Heshmat, M. Girgis, W. Abd-Elhafiez, S. Elaw","doi":"10.1109/ICCES.2015.7393056","DOIUrl":null,"url":null,"abstract":"Human face detection is very useful in many applications such as communications, automatic access control systems, video browsing, security control, verification of credit cards, identifying criminals and so on. This work provides a simple and efficient technique to detect human faces in still images. The new method based on skin color, contour drawing and feature extraction. The features under consideration are eyes, nose and mouth. The technique used to extract facial features developed based on feature location with respect to face dimensions. The proposed algorithm was tested on various images and its performance was found to be good in most cases. Experimental results show that our method of human face detection achieves very encouraging results with good accuracy, great speed and simple computations.","PeriodicalId":227813,"journal":{"name":"2015 Tenth International Conference on Computer Engineering & Systems (ICCES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"An efficient scheme for face detection based on contours and feature skin recognition\",\"authors\":\"M. Heshmat, M. Girgis, W. Abd-Elhafiez, S. Elaw\",\"doi\":\"10.1109/ICCES.2015.7393056\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Human face detection is very useful in many applications such as communications, automatic access control systems, video browsing, security control, verification of credit cards, identifying criminals and so on. This work provides a simple and efficient technique to detect human faces in still images. The new method based on skin color, contour drawing and feature extraction. The features under consideration are eyes, nose and mouth. The technique used to extract facial features developed based on feature location with respect to face dimensions. The proposed algorithm was tested on various images and its performance was found to be good in most cases. Experimental results show that our method of human face detection achieves very encouraging results with good accuracy, great speed and simple computations.\",\"PeriodicalId\":227813,\"journal\":{\"name\":\"2015 Tenth International Conference on Computer Engineering & Systems (ICCES)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Tenth International Conference on Computer Engineering & Systems (ICCES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCES.2015.7393056\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Tenth International Conference on Computer Engineering & Systems (ICCES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCES.2015.7393056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An efficient scheme for face detection based on contours and feature skin recognition
Human face detection is very useful in many applications such as communications, automatic access control systems, video browsing, security control, verification of credit cards, identifying criminals and so on. This work provides a simple and efficient technique to detect human faces in still images. The new method based on skin color, contour drawing and feature extraction. The features under consideration are eyes, nose and mouth. The technique used to extract facial features developed based on feature location with respect to face dimensions. The proposed algorithm was tested on various images and its performance was found to be good in most cases. Experimental results show that our method of human face detection achieves very encouraging results with good accuracy, great speed and simple computations.