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Gabor wavelet based face recognition under varying lighting, pose and expression conditions

机译:基于Gabor小波的面部识别在不同的照明,姿势和表达条件下

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Automated face recognition is a rapidly growing field that uses computer algorithms to determine the similarity between two face images. One of the major challenges in face recognitions to extract features from face images varying in facial expression, varying in lighting condition and varying in poses. The objective of this paper is to present the recognition of face images based on Gabor wavelets. Performance comparison of recognizing face images taken under varying facial expressions, varying lighting condition and varying poses are presented. Experimental results of Gabor wavelets for face recognition under varying lighting, poses and expression conditions are provided. For experiments face images from the three datasets (ORL, Yale and FERET) are used.
机译:自动面部识别是一种快速生长的字段,它使用计算机算法来确定两个面部图像之间的相似性。面部识别中的主要挑战之一,以从面部表情变化的面部图像中提取特征,在照明条件下变化并在姿势变化。本文的目的是呈现基于Gabor小波的脸部图像的识别。呈现了在不同面部表情下识别的面部图像的性能比较,不同的照明条件和变化的姿势。提供了在不同照明,姿势和表达条件下进行面部识别的Gabor小波的实验结果。对于实验,使用来自三个数据集(ORL,耶鲁和机构)的面部图像。

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