Coefficients' co-occurrence histogram of DWFT based feature extration with ONPP for face recognition

Xiaoshan Liu, Minghui Du, Lianwen Jin
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Abstract

The important step of face recognition based on subspace method is to obtain powerful features. In this paper, we propose a novel feature extraction technique based on discrete wavelet frame transform(DWFT), which capture the information about relationship between each high frequency subband and the low frequency subband of the decomposed image at the corresponding level. In the feature space, we use orthogonal neighborhood preserving profections (ONPP) algorithm to reduce dimension. experimental results show that the proposed algorithm is effective in face recognition. Comparisons with the other approachs are also provided.
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基于DWFT特征提取的系数共现直方图与ONPP人脸识别
基于子空间方法的人脸识别的重要步骤是获取强大的特征。本文提出了一种新的基于离散小波帧变换(DWFT)的特征提取技术,该技术在相应的层次上捕获分解图像的每个高频子带与低频子带之间的关系信息。在特征空间中,我们使用正交邻域保持保护(ONPP)算法进行降维。实验结果表明,该算法在人脸识别中是有效的。并与其他方法进行了比较。
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