Multiscale Handwriting Characterization for Writers’ Classification

  • Véronique Eglin
  • Stéphane Bres
  • Carlos Rivero
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3163)

Abstract

In this paper, we propose a method for handwritten text characterization based on a multiscale and multiresolution drawing analysis. The approach lies on the definition of four complementary handwritten text visual dimensions: the macro and micro orientation (obtained with a frequencies multiscale image analysis), the text linearity (defined by the merge of connected components), the curvature (measured as a multiresolution high profile deformation) and the complexity (expressed as multiscale drawing distribution entropy). Each feature is studied in an evolution graph that can be expressed as a unique handwritten curve signature. It leads to a description in separable writers families having individual visual characteristics. The results are very promising.

Keywords

Gabor Filter Text Line Multiscale Approach Evolution Graph Handwritten Text 
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 2004

Authors and Affiliations

  • Véronique Eglin
    • 1
  • Stéphane Bres
    • 1
  • Carlos Rivero
    • 1
  1. 1.LIRISINSA de LyonVilleurbanne CedexFrance

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