Robust Preprocessing Algorithm for Face Recognition

G. Mittal, S. Sasi
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引用次数: 5

Abstract

The face recognition includes enhancement and segmentation of face image, detection of face boundary and facial features, matching of extracted features against the features in a database, and finally recognition of the face. The face detection algorithms are based on either gray level template matching or computation of geometric relationships among facial features. Though a number of algorithms are devised for face recognition, the technology is not matured enough to recognize the face of a person with and without beard to be the same. This research proposes a robust algorithm for preprocessing the face image with beard for face recognition. Simulation is done using eighteen JPEG images of 9 different persons having beard and without beard. This research finds application in homeland security where it can increase the robustness of the existing face recognition algorithms.
人脸识别的鲁棒预处理算法
人脸识别包括人脸图像的增强和分割,人脸边界和人脸特征的检测,提取的特征与数据库中的特征进行匹配,最后对人脸进行识别。人脸检测算法要么基于灰度模板匹配,要么基于面部特征之间的几何关系计算。虽然人脸识别已经有了很多算法,但技术还不够成熟,无法识别出有胡子和没有胡子的人的脸是一样的。本研究提出一种鲁棒的胡须人脸图像预处理算法,用于人脸识别。模拟使用18张JPEG图像,9个不同的人有胡子和没有胡子。本研究发现在国土安全领域的应用,可以提高现有人脸识别算法的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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