一种基于分量分析的人脸识别方法

P. Shamna, C. Tripti, P. Augustine
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引用次数: 2

摘要

数字技术的发展加强了计算机与人之间的交流。人脸识别是开发人机交互(HCI)的一项重要技术。本文提出了一种基于差分分量分析(DCA)的模式识别方法,并介绍了其在人脸识别中的应用。DCA去除图像的所有一般特征,并计算图像的差异分量。DCA的原理是两个相似的图像具有最少的差异成分。利用耶鲁大学人脸数据库和美国电话电报公司人脸数据库进行了人脸识别仿真。实验结果表明,该方法对不同条件下的人脸识别效果显著。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DCA: An Approach for Face Recognition through Component Analysis
The developments in digital technologies is enhancing the communication between computers and Human. Face recognition is a vital technique that helps to develops user-friendly methods for Human Computer Interaction (HCI). In this paper we suggest a pattern recognition method using Difference Component Analysis (DCA) and present its application in face recognition. The DCA removes all the general features of images and compute the difference components of the images. The DCA is based on the principle that two similar images will have least difference components. Simulation of DCA is done by using Yale face database and AT&T face database. The experimental results indicate that, the presented approach is remarkably effective in recognizing faces under different conditions.
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