Handwritten Character Segmentation Using Transformation-Based Learning

15th International Conference on Pattern Recognition (ICPR'00) - Volume 2 p. 2634
Handwritten Character Segmentation Using Transformation-Based Learning
E. Kavallieratou, University of Patras
E. Stamatatos, University of Patras
N. Fakotakis, University of Patras
G. Kokkinakis, University of Patras

Full Article Text:

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2000.906155
Send link to a friend

Abstract
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 multi-writer handwritten words. The achieved accuracy in detecting segment boundaries exceeds 82%. Moreover, limited training data can provide very satisfactory results.
Back to Top Additional Information
Citation: E. Kavallieratou, E. Stamatatos, N. Fakotakis, G. Kokkinakis, "Handwritten Character Segmentation Using Transformation-Based Learning," icpr, p. 2634, 15th International Conference on Pattern Recognition (ICPR'00) - Volume 2, 2000

	Advanced Search
CS Search Google Search