基于PCA和k-NN分类器的彩色人脸识别实现

Can Eyupoglu
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引用次数: 13

摘要

彩色人脸识别是近年来备受关注的课题,已成为图像分析和模式识别研究的重要组成部分之一。此外,它还用于与人员识别、视频监控、门禁、智能卡、护照、信息和社会安全等相关的各种应用。在本研究中,使用k-Nearest Neighbors (k-NN)对彩色人脸图像进行分类。首先,仅使用k-NN分类器进行分类。然后将主成分分析(PCA)和k-NN分类器结合使用。此外,这两种方法分别针对不同的色彩空间模型和k值实现。最后,对实验结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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