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.
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Hafiane, A., Seetharaman, G., Zavidovique, B. (2007). Median Binary Pattern for Textures Classification. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2007. Lecture Notes in Computer Science, vol 4633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74260-9_35
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DOI: https://doi.org/10.1007/978-3-540-74260-9_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74258-6
Online ISBN: 978-3-540-74260-9
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