A New Approach to Face Image Coding using Gabor Wavelet Networks

A. Chaari, F. Cabestaing, D. Sellami-Masmoudi
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引用次数: 2

Abstract

In this paper, we describe a new approach to face image coding using Gabor Wavelet Networks (GWN). This type of network yields good results in many signal coding applications and was already used for face representation by Kruger in 2001. The main idea is to approximate the face image, considered as a two dimensional function, with a set of Gabor wavelets. We describe an improved network training technique, which uses several face images of the same person rather than a single one. This technique yields the model of the face image, but also statistical criteria defining the significance of each Gabor wavelet in this model.
基于Gabor小波网络的人脸图像编码新方法
本文提出了一种基于Gabor小波网络的人脸图像编码方法。这种类型的网络在许多信号编码应用中产生了良好的效果,克鲁格在2001年已经将其用于人脸表示。其主要思想是用一组Gabor小波逼近作为二维函数的人脸图像。我们描述了一种改进的网络训练技术,它使用同一个人的多张人脸图像而不是一张。这种技术产生了人脸图像的模型,而且还定义了该模型中每个Gabor小波的显著性的统计标准。
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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