{"title":"基于外观的移动环境图像人脸识别方法","authors":"Abbas Memiş, F. Karabiber","doi":"10.1109/SIU.2016.7495704","DOIUrl":null,"url":null,"abstract":"In this paper, we present face recognition systems, which are performed by using appearance based methods on mobile environment face images, and their comparative performance analysis. In proposed systems, face detection process is performed by using Haar-like features and cascade classifiers on mobile environment face images. Color space transformation, dimensional normalization and histogram equalization operations are performed on detected face images as pre-processing steps. Principal Component Analysis, Fisher's Linear Discriminant Analysis and Local Binary Pattern Histograms methods are used to extract facial features. K-nearest neighbor classifier is employed for the performance analysis of implemented methods. Accuracy, precision, recall and F-measure values are measured and compared in performance evaluations of selected facial recognition methods on various dimensionally normalized face images. Experimental results obtained using MOBIO face database show that Local Binary Pattern Histograms method has high success rates on mobile environment images.","PeriodicalId":427250,"journal":{"name":"2016 24th Signal Processing and Communication Application Conference (SIU)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Face recognition on mobile environment images using appearance based methods\",\"authors\":\"Abbas Memiş, F. Karabiber\",\"doi\":\"10.1109/SIU.2016.7495704\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present face recognition systems, which are performed by using appearance based methods on mobile environment face images, and their comparative performance analysis. In proposed systems, face detection process is performed by using Haar-like features and cascade classifiers on mobile environment face images. Color space transformation, dimensional normalization and histogram equalization operations are performed on detected face images as pre-processing steps. Principal Component Analysis, Fisher's Linear Discriminant Analysis and Local Binary Pattern Histograms methods are used to extract facial features. K-nearest neighbor classifier is employed for the performance analysis of implemented methods. Accuracy, precision, recall and F-measure values are measured and compared in performance evaluations of selected facial recognition methods on various dimensionally normalized face images. Experimental results obtained using MOBIO face database show that Local Binary Pattern Histograms method has high success rates on mobile environment images.\",\"PeriodicalId\":427250,\"journal\":{\"name\":\"2016 24th Signal Processing and Communication Application Conference (SIU)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 24th Signal Processing and Communication Application Conference (SIU)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIU.2016.7495704\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 24th Signal Processing and Communication Application Conference (SIU)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU.2016.7495704","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Face recognition on mobile environment images using appearance based methods
In this paper, we present face recognition systems, which are performed by using appearance based methods on mobile environment face images, and their comparative performance analysis. In proposed systems, face detection process is performed by using Haar-like features and cascade classifiers on mobile environment face images. Color space transformation, dimensional normalization and histogram equalization operations are performed on detected face images as pre-processing steps. Principal Component Analysis, Fisher's Linear Discriminant Analysis and Local Binary Pattern Histograms methods are used to extract facial features. K-nearest neighbor classifier is employed for the performance analysis of implemented methods. Accuracy, precision, recall and F-measure values are measured and compared in performance evaluations of selected facial recognition methods on various dimensionally normalized face images. Experimental results obtained using MOBIO face database show that Local Binary Pattern Histograms method has high success rates on mobile environment images.