{"title":"基于PCA和k-NN分类器的彩色人脸识别实现","authors":"Can Eyupoglu","doi":"10.1109/EICONRUSNW.2016.7448153","DOIUrl":null,"url":null,"abstract":"The topic of color face recognition has received significant attention in recent years and has become one of the important parts of image analysis and pattern recognition research. Furthermore, it is used in various applications related to person identification, video surveillance, access control, smart card, passport, information and social security, etc. In this study, k-Nearest Neighbors (k-NN) is used in order to classify color face images. Firstly, the classification is performed using only k-NN classifier. After that Principal Component Analysis (PCA) and k-NN classifier are used together. In addition, these two methods are implemented for different color space models and k values. Finally, the experiment results are compared with each other.","PeriodicalId":262452,"journal":{"name":"2016 IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Implementation of color face recognition using PCA and k-NN classifier\",\"authors\":\"Can Eyupoglu\",\"doi\":\"10.1109/EICONRUSNW.2016.7448153\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The topic of color face recognition has received significant attention in recent years and has become one of the important parts of image analysis and pattern recognition research. Furthermore, it is used in various applications related to person identification, video surveillance, access control, smart card, passport, information and social security, etc. In this study, k-Nearest Neighbors (k-NN) is used in order to classify color face images. Firstly, the classification is performed using only k-NN classifier. After that Principal Component Analysis (PCA) and k-NN classifier are used together. In addition, these two methods are implemented for different color space models and k values. Finally, the experiment results are compared with each other.\",\"PeriodicalId\":262452,\"journal\":{\"name\":\"2016 IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EICONRUSNW.2016.7448153\",\"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 IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EICONRUSNW.2016.7448153","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Implementation of color face recognition using PCA and k-NN classifier
The topic of color face recognition has received significant attention in recent years and has become one of the important parts of image analysis and pattern recognition research. Furthermore, it is used in various applications related to person identification, video surveillance, access control, smart card, passport, information and social security, etc. In this study, k-Nearest Neighbors (k-NN) is used in order to classify color face images. Firstly, the classification is performed using only k-NN classifier. After that Principal Component Analysis (PCA) and k-NN classifier are used together. In addition, these two methods are implemented for different color space models and k values. Finally, the experiment results are compared with each other.