Median binary pattern for textures classification

Authors:
Adel Hafiane;Guna Seetharaman;Bertrand Zavidovique
Affiliations:
Laboratoire Vision Robotique, ENSI de Bourges-Université d'Orléans, Bourges Cedex France;Departement of Electrical and Computer Engineering, Air Force Institute of Technology, Dayton, OH;Institut d'Electronique Fondamentale, Université de Paris-Sud, Orsay Cedex, France
Venue:
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Year:
2007

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Abstract

A texture classification method using a binary texture metric is presented. The method consists of extracting local structures and describing their distribution by a global approach. Texture primitives are determined by a localized thresholding against the local median. The local spatial signature of the thresholded image is uniquely encoded as a scalar value, whose histogram helps characterize the overall texture. A multi resolution approach has been tried to handle variations in scale. Also, the encoding scheme facilitates a rich class of equivalent structures related by image rotation. Then, we demonstrate - using a set of classifications, that the proposed method significantly improves the capability of texture recognition and outperforms classical algorithms.