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Multiscale handwriting characterization for writers, classification

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.
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Submitted on : Sunday, July 2, 2017 - 10:23:35 PM
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  • HAL Id : hal-01552443, version 1


Véronique Eglin, Stéphane Bres, Carlos Rivero-Moreno. Multiscale handwriting characterization for writers, classification. DAS: Document Analysis System VI, Jan 2004, Florence, Italy, Italy. pp.337-341. ⟨hal-01552443⟩



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