Character Prototyping in Document Images Using Gabor Filters

  • Bénédicte Allier
  • Hubert Emptoz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2749)

Abstract

In this article we present a particular application of Gabor filtering for machine-printed document image understanding. To do so, we assume that the text can be seen as texture, characters being the smallest texture elements, and we verify this hypothesis by a series of experiments over different sets of character images. We first apply a bank of 24 Gabor filters (4 frequencies and 6 orientations) on each set, then we extract texture features, that are used to classify character images without a priori knowledge using a Bayesian classifier. Results are shown for different characters written in a same font, and for different font types given a character.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Bénédicte Allier
    • 1
  • Hubert Emptoz
    • 1
  1. 1.Reconnaissance des Formes et Vision Laboratory (RFV)INSA LyonVilleurbanne cedexFrance

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