Implementation of color face recognition using PCA and k-NN classifier

• Published in: 2016 IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW)
• Main Author: Eyüpoğlu, Can
• Other Authors: Bölüm Yok
• Format: Conference Object
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2016
• Subjects: color face recognition; image analysis; k-NN classifier; PCA; North-West Russia
• Online Access: http://hdl.handle.net/11467/4178; https://doi.org/10.1109/EIConRusNW.2016.7448153

IEEE North West Russia Section Young Researchers in Electrical and Electronic Engineering Conference, EIConRusNW 2016 -- 2 February 2016 through 3 February 2016 -- -- 121142 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. © 2016 IEEE.