Fuzzy Segmentation of Characters in Web Images Based on Human Colour Perception

  • A. Antonacopoulos
  • D. Karatzas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2423)

Abstract

This paper describes a new approach for the segmentation of characters in images on Web pages. In common with the authors’ previous work in this subject, this approach attempts to emulate the ability of humans to differentiate between colours. In this case, pixels of similar colour are first grouped using a colour distance defined in a perceptually uniform colour space (as opposed to the commonly used RGB). The resulting colour connected components are then grouped to form larger (character-like) regions with the aid of a fuzzy propinquity measure. This measure expresses the likelihood for merging two components based on two features. The first feature is the colour distance in the L * a * b * colour space. The second feature expresses the topological relationship of two components. The results of the method indicate a better performance than the previous method devised by the authors and comparable (possibly better) performance to other existing methods.

Keywords

Membership Function Colour Space Fuzzy Inference System Colour Distance Neighbouring Component 
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 2002

Authors and Affiliations

  • A. Antonacopoulos
    • 1
  • D. Karatzas
    • 1
  1. 1.PRImA Group, Department of Computer ScienceUniversity of LiverpoolLiverpoolUK

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