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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Eglin, V., Bres, S., Rivero, C. (2004). Multiscale Handwriting Characterization for Writers’ Classification. In: Marinai, S., Dengel, A.R. (eds) Document Analysis Systems VI. DAS 2004. Lecture Notes in Computer Science, vol 3163. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28640-0_32
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DOI: https://doi.org/10.1007/978-3-540-28640-0_32
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