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Efficient distance-based per-pixel texture classification with Gabor wavelet filters

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Abstract

This paper proposes an efficient solution to the problem of per-pixel classification of textured images with multichannel Gabor wavelet filters based on a selection scheme that automatically determines a subset of prototypes that characterize each texture class. Results with Brodatz compositions and outdoor images, and comparisons with alternative classification techniques are presented.

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Authors and Affiliations

  1. Intelligent Robotics and Computer Vision Group, Department of Computer Science and Mathematics, Rovira i Virgili University, Av. Països Catalans 26, 43007, Tarragona, Spain

    Jaime Melendez & Domenec Puig

  2. Department of Informatics Engineering, Autonomous University of Madrid, Francisco Tomas y Valiente 11, 28049, Madrid, Spain

    Miguel Angel Garcia

Authors
  1. Jaime Melendez
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  2. Miguel Angel Garcia
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  3. Domenec Puig
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Corresponding author

Correspondence to Jaime Melendez.

Additional information

This work has been partially supported by the Spanish Ministry of Education and Science under projects DPI2004-07993-C03-03 and DPI2007-66556-C03-03.

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Melendez, J., Garcia, M.A. & Puig, D. Efficient distance-based per-pixel texture classification with Gabor wavelet filters. Pattern Anal Applic 11, 365–372 (2008). https://doi.org/10.1007/s10044-007-0097-3

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  • DOI: https://doi.org/10.1007/s10044-007-0097-3

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