Face Recognition Based on Curvelet Transform and Independent Component Analysis
LIU Song
WANG Chunning
Abstract：As the main features of the faces can be better represented by the curvelet coefficients, and higher-order feature can be extracted by independent component analysis, a method of face recognition based on curvelet transform and ICA is proposed in this paper.Firstly, each of the images is decomposed using curvelet trasnform, and the low-frequency face image is selected as a sub-image;secondly,ICA is adopted to obtain independent components,and part of independent components are selected to constitute the feature space.Finally, the nearest neighbor classifier is used for identification.The experiment result on ORL and Yale face databases shows that the proposed method improved the recognition performance in comparison with comparative approach.
Keywords：face recognitioncurvelet transformindependent component analysisfeature extractthe nearest neighbor classifier
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 300-303 )