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http://hdl.handle.net/20.500.12358/24857
TitleFace recognition using curvelet transform
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Abstract

This paper presents a new method for the problem of human face recognition from still images. This is based on a multiresolution analysis tool called Digital Curvelet Transform. Curvelet transform has better directional and edge representation abilities than wavelets. Due to these attractive attributes of curvelets, we introduce this idea for feature extraction by applying the curvelet transform of face images twice. The curvelet coefficients create a representative feature set for classification. These coefficients set are then used to train gradient descent backpropagation neural network (NN). A comparative study with wavelet-based, curvelet-based, and traditional Principal Component Analysis (PCA) techniques is also presented. High accuracy rate of 97 achieved by the proposed method for two well-known databases indicates the potential of this curvelet based curvelet feature extraction method.

Authors
Hejazi, Hana
Alhanjouri, Mohammed A.
TypeJournal Article
Date2010
Subjects
face recognition
digital curvelet transform
backpropagation neural network
Published inInternational Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems
PublisherSpringer, Berlin, Heidelberg
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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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