基于Gabor小波和SLLE的人脸识别算法
首发时间:2009-04-21
摘要:为了提高人脸识别算法的识别率,提出了一种基于Gabor小波和SLLE的人脸识别算法。该算法首先采用Gabor小波对归一化的人脸图像进行多方向、多分辨率滤波,并提取其对应不同方向、不同尺度的多个Gabor幅值特征,然后采用监督的局部线性嵌入算法对Gabor特征进行维数约简,最后使用最近邻分类器进行分类判决。在ORL、YALE人脸库上进行实验,该算法平均识别率比其他算法提高3.5%-37.8%,有效提高了人脸识别算法的性能。
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An Algorithm of Face Recognition Based on Gabor Wavelet and SLLE
Abstract:In order to improve the recognition rate of face recognition algorithm, This paper presents a new algorithm of face recognition based on Gabor wavelet transform and Supervised Locally Linear Embedding (SLLE). First of all, Gabor wavelet is introduced as a method to extract Gabor magnitude features by convolving the normalized face image with multi-scale and multi-orientation Gabor filters. In the feature extraction module, the dimension of Gabor features is reduced by Supervised Locally Linear Embedding(SLLE). Finally, a minimum-distance classifier is trained for classification. The result of experiment on the ORL and YALE face database shows a 3.5 %~37.8% increase in recognition rate, compared to others, by using the proposed algorithm, which improves face recognition performance effectively.
Keywords: Face recognition Gabor wavelet SLLE Feature extraction
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