人脸识别最佳光谱带选择系统的比较研究

Hamdi Jamel Bouchech, S. Foufou
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引用次数: 2

摘要

在人脸识别中,多光谱图像(MI)已经显示出解决高照度变化问题的良好能力。然而,如果不使用最佳光谱带选择系统(BSBS),则每个主题都有大量捕获的光谱带,因此使用MI是不切实际的。在这项工作中,首先,我们给出了一个最新的概述现有的BSBS技术提出的人脸识别。我们的目标是强调基于MI的系统中这个组件的重要性。然后使用多光谱人脸数据库IRIS - M3进行实验,比较它们的性能。据我们所知,这是第一项回顾和比较现有BSBS技术的研究。所获得的结果强调了建立基于MI系统的BSBS技术的重要性,以及对新技术的需求,以更好地研究图像处理工具的速度提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A comparative study of best spectral bands selection systems for face recognition
Multispectral images (MI) have shown promising capabilities to solve problems resulting from high illumination variation in face recognition. However, the use of MI, with the huge number of captured spectral bands for each subject, is impractical unless a system for best spectral bands selection (BSBS) is used. In this work, first we give an up to date overview of the existing BSBS techniques proposed for face recognition. We aim to highlight the imporatnce of this component of MI based systems. The reviewed techniques are then experimented using the multispectral face database IRIS - M3 to compare their performances. To the best of our knowledge this is the first study that reviews and compares existing techniques for BSBS. The Obtained results emphasized the importance of setting up techniques for BSBS with MI based systems as well as the need for new techniques that investigate better the increasing speed of image processing tools.
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