DOIONLINE 
DOIONLINE Publish In |
International Journal of Industrial Electronics and Electrical Engineering (IJIEEE)-IJIEEE |
 Journal Home Volume Issue |
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Issue |
Volume-5,Issue-4 ( Apr, 2017 ) | |||||||||
Paper Title |
Uniform and Rotation Invariant Texture Model for Material Recognition | |||||||||
Author Name |
D.Anitha, M.Srikanth, Ponnekanti Prasanna Lakshmi | |||||||||
Affilition |
152W1D3806, GVR&S College of Engineering and Technology Asst. Prof., Dept. Of ECE GVR&S College of Engineering and Technology 3162W1D3805, GVR&S College of Engineering and Technology | |||||||||
Pages |
34-35 | |||||||||
Abstract |
Local binary pattern (LBP) and its variants have shown promising results in visual recognition applications. However, most existing approaches rely on a pre-defined structure to extract LBP features. We argue that the optimal LBP structure should be task-dependent and propose a new method to learn discriminative LBP structures. We formulate it as a point selection problem: Given a set of point candidates, the goal is to select an optimal subset to compose the LBP structure. In view of the problems of current feature selection algorithms, we propose a novel Maximal Joint Mutual Information criterion. Then, the point selection is converted into a binary quadratic programming problem and solved efficiently via the branch and bound algorithm. The proposed LBP structures demonstrate superior performance to the state-of-the-art approaches on classifying both spatial patterns in scene recognition and spatial-temporal patterns in dynamic texture recognition. Keywords- LBP structure optimization, maximal joint mutual information, binary quadratic programming, scene recognition, dynamic texture recognition | |||||||||
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