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Handwritten Character Segmentation Using Transformation-Based Learning

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Handwritten Character Segmentation Using Transformation-Based Learning
This paper presents a character segmentation algorithm for unconstrained cursive handwritten text. The transformation-based learning method and a simplified variation of it are used in order to extract automatically rules that detect the segment boundaries. Comparative experimental results are given for a collection of multiwriter handwritten words. The achieved accuracy in detecting segment boundaries exceeds 82%. Moreover, limited training data can provide very satisfactory results.
Ergina Kavallieratou, Efstathios Stamatatos, Nikos
Added 31 Jul 2010
Updated 31 Jul 2010
Type Conference
Year 2000
Where ICPR
Authors Ergina Kavallieratou, Efstathios Stamatatos, Nikos Fakotakis, George K. Kokkinakis
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