Facial feature extraction and recognition based on Curvelet transform and SVD

机译：基于Curvelet变换和SVD的人脸特征提取与识别

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This paper proposed a new algorithm of facial feature extraction and recognition based on Curvelet transform and SVD (Singular Value Decomposition). Firstly, the method carries on the Curvelet transform to the face images, extracts the Curvelet energy features of low frequency and the high frequency, and then carries on the singular value compression and feature fusion to this component. Finally, by using the nearest neighbor classifier in the ORL person face database, the classified recognition was carried out so that to confirm the validity of the algorithm.

机译：提出了一种基于Curvelet变换和奇异值分解的人脸特征提取与识别算法。该方法首先对人脸图像进行Curvelet变换，提取低频和高频的Curvelet能量特征，然后对该分量进行奇异值压缩和特征融合。最后，通过使用ORL人脸数据库中的最近邻分类器，进行了分类识别，以确认算法的有效性。

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来源
《International Conference on Apperceiving Computing and Intelligence Analysis (ICACIA 2009)》|2009年|104-107|共4页
会议地点 Chengdu(CN);Chengdu(CN)
作者
He Jia; Zhang Xiangfeng;
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作者单位

College of Computer Science Technology, Chengdu University of Information Technology, 610225, China;

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原文格式 PDF
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中图分类
关键词
Curvelet transform; feature fusion; singular value decomposition;

机译：Curvelet变换;特征融合;奇异值分解;

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Facial feature extraction and recognition based on Curvelet transform and SVD

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