基于Gabor-HOG特征的人脸识别方案

H. Ouanan, M. Ouanan, B. Aksasse
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引用次数: 15

摘要

不变特征的提取是人脸识别系统的核心。本文提出了一种新的特征提取融合方案,该方案使用两个功能强大的特征描述符Gabor滤波器(GFs)和定向梯度直方图(HOG),该方案使用多尺度多分辨率Gabor滤波器组对人脸图像进行滤波,生成多个Gabor量级图像(gmi),然后对下采样的gmi进行滤波,并应用定向梯度直方图形成特征。在FERET人脸数据库上的实验结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Gabor-HOG Features based Face Recognition Scheme
Extraction of invariant features is the core of Face RecognitionSystems (FRS). This work proposes a novel feature extractor-fusion scheme using two powerful feature descriptor known as Gabor Filters (GFs) and Histogram of Oriented Gradient (HOG), which the face image is filtered with the multiscale multiresolution Gabor filter bank to generate multiple Gabor magnitude images (GMIs), then the down-sampled GMIs and apply Histogram of Oriented Gradient to form the features. The experimental results on the FERET face database show the effectiveness of our methods.
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