A New Extension of Locality Preserving Projections for Image Feature Extraction

Guo Hong Huang

doi:10.4028/www.scientific.net/AMM.241-244.1715

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Correct the Extreme Properties of Mono-Attribute Dependability
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A Robust and Efficient Face Recognition System Based on Luminance Distribution Using Maximum Likelihood
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Imploved Real Quantum Evolutionary Algorithm and Application
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A New Extension of Locality Preserving Projections for Image Feature Extraction
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The Research of Least Square Support Vector Machine Model and its Simplified Method
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A System of QR Barcode Recognition Based on Mobile Phone
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Real Time Dynamic Threshold Clustering Method for Ancient Chinese Character Identification
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Research on Automatic Identification of Airplane Targets on Infrared Images
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 241-244A New Extension of Locality Preserving Projections...

A New Extension of Locality Preserving Projections for Image Feature Extraction

Abstract:

This paper proposes a novel algorithm for image feature extraction, namely, the two-directional two-dimensional locality preserving projection, ((2D)2LPP), which can find an embedding from two directions that not only preserves local information and detect the intrinsic image manifold structure, but also combines the both information between rows and those between columns simultaneously. We also combine the advantages of (2D)2LPP and LDA, and propose a new framework for feature extraction as two-stage: “(2D)2LPP+LDA.” The LDA step is performed to further reduce the dimension of feature matrix in the (2D)2LPP subspace. Experimental results on ORL face databases demonstrate the effectiveness of the proposed methods.