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Two-level dimensionality reduced local directional pattern for face recognition

Two-level dimensionality reduced local directional pattern for face recognition Face recognition can be done efficiently using local approaches. Local directional pattern (LDP) is one such approach that serves as a descriptor for face recognition. It assigns a code for each pixel and the image is encoded. Histogram binning is done on the LDP encoded image to represent the face. A two-level dimensionality reduced local directional pattern () is proposed in this paper. The proposed is robust in recognising the faces with maximum recognition rate. The proposed descriptor codes the image by dividing the image into regions and for each region, a code is defined. The same process is repeated for one more level and hence named as . At each level, the dimensions of the feature vector are drastically reduced and performance of the descriptor maintains the higher recognition rate. The proposed descriptor is tested on standard benchmark databases like FERET, Extended YALE B and ORL. The results obtained prove that the is exemplary. Keywords: local directional pattern; LDP; dimensionality reduction; face recognition; feature descriptor; face descriptor; face detection; local patterns. Reference to this paper should be made as follows: Ramalingam, S.P. and Chandra Mouli, P.V.S.S.R. (2016) `Two-level dimensionality reduced local directional pattern for face recognition', Int. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Biometrics Inderscience Publishers

Two-level dimensionality reduced local directional pattern for face recognition

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Publisher
Inderscience Publishers
Copyright
Copyright © 2016 Inderscience Enterprises Ltd.
ISSN
1755-8301
eISSN
1755-831X
DOI
10.1504/IJBM.2016.077150
Publisher site
See Article on Publisher Site

Abstract

Face recognition can be done efficiently using local approaches. Local directional pattern (LDP) is one such approach that serves as a descriptor for face recognition. It assigns a code for each pixel and the image is encoded. Histogram binning is done on the LDP encoded image to represent the face. A two-level dimensionality reduced local directional pattern () is proposed in this paper. The proposed is robust in recognising the faces with maximum recognition rate. The proposed descriptor codes the image by dividing the image into regions and for each region, a code is defined. The same process is repeated for one more level and hence named as . At each level, the dimensions of the feature vector are drastically reduced and performance of the descriptor maintains the higher recognition rate. The proposed descriptor is tested on standard benchmark databases like FERET, Extended YALE B and ORL. The results obtained prove that the is exemplary. Keywords: local directional pattern; LDP; dimensionality reduction; face recognition; feature descriptor; face descriptor; face detection; local patterns. Reference to this paper should be made as follows: Ramalingam, S.P. and Chandra Mouli, P.V.S.S.R. (2016) `Two-level dimensionality reduced local directional pattern for face recognition', Int.

Journal

International Journal of BiometricsInderscience Publishers

Published: Jan 1, 2016

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