|Table of Contents|

Face recognition based on curvelet transform and independentcomponent analysis(PDF)

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2017年01期
Page:
74-
Research Field:
Publishing date:

Info

Title:
Face recognition based on curvelet transform and independentcomponent analysis
Author(s):
Zhang LinmeiZhang Xuefeng
College of Information Engineering,Xinyang College of Agriculture and Forestry,Xinyang 464000,China
Keywords:
face recognition feature extraction curvelet transform independent component analysis wavelet transform
PACS:
TP391
DOI:
10.14177/j.cnki.32-1397n.2017.41.01.010
Abstract:
In order to obtain high recognition rate and accelerate the speed of face recognition,a face recognition algorithm is proposed by combining curvelet transform and independent component analysis.Firstly,face images are processed by curvelet transform and get curvelet coefficients in scale and direction.The obtained curvelet coefficients are weighted and fused and then independent component analysis is used to select the features which have important contributions,reducing the feature dimension to accelerate the recognition speed of face classifier.Finally,least square support vector machine is used to establish face recognition classifier,and the classical face database is used to test the performance of face recognition.The experimental results show that the average recognition rate of the proposed algorithm is more than 95%,and the average recognition time can meet the requirements of face recognition.

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Last Update: 2017-02-28