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Textural Features for Scribble-Based Image Colorization

  • Michal Kawulok
  • Jolanta Kawulok
  • Bogdan Smolka
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 95)

Abstract

In this paper we propose how to exploit image textural features to improve scribble-based image colorization. The existing techniques work by propagating color from the user-added scribbles over the whole image. The color propagation paths are determined so as to minimize the luminance changes integrated along the path. In our method, at first linear discriminant analysis is performed over the scribble pixels to extract discriminative textural features (DTF). Our contribution to image colorization lies in using DTF for the path optimization instead of the luminance. The colorization results presented in the paper explain and confirm the method’s robustness compared with the alternative existing techniques.

Keywords

Textural Feature Linear Discriminant Analysis Propagation Path Local Binary Pattern Color Propagation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Michal Kawulok
    • 1
  • Jolanta Kawulok
    • 1
  • Bogdan Smolka
    • 1
  1. 1.Faculty of Automatic Control, Electronics and Computer ScienceSilesian University of TechnologyGliwicePoland

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