Journal of Computer and Communications
Volume 3, Issue 11 (November 2015)
ISSN Print: 2327-5219 ISSN Online: 2327-5227
Google-based Impact Factor: 1.12 Citations
Discriminant Neighborhood Structure Embedding Using Trace Ratio Criterion for Image Recognition ()
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ABSTRACT
Dimensionality reduction is very important in pattern recognition, machine learning, and image recognition. In this paper, we propose a novel linear dimensionality reduction technique using trace ratio criterion, namely Discriminant Neighbourhood Structure Embedding Using Trace Ratio Criterion (TR-DNSE). TR-DNSE preserves the local intrinsic geometric structure, characterizing properties of similarity and diversity within each class, and enforces the separability between different classes by maximizing the sum of the weighted distances between nearby points from different classes. Experiments on four image databases show the effectiveness of the proposed approach.
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