A New Chain-code Quantization Approach Enabling High Performance Handwriting Recognition based on Multi-Classifier Schemes

Authors:
S. Hoque;K. Sirlantzis;M. C. Fairhurst
Affiliations:
-;-;-
Venue:
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Year:
2003

Citing 7
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Abstract

In this paper initially we propose a novel approach toclassify handwritten characters based on a directional decompositionof the corresponding chain-code representation.This is alternative to previous transformations of thechain-codes proposed by the authors, namely the orderedand random decomposition of the bit-planes resulting fromthe binary representation of the chain-codes. Subsequentlywe utilize the power of the recently developed multiple classifierschemes using sntuple classifiers to integrate the complimentaryinformation encapsulated in all three transformationsinto a more powerful and robust character recognitionsystem. The results obtained through a series ofcross-validation experiments show that the proposed fusionscheme not only outperforms its constituent parts and anumber of other successful classifiers, but also enables significantsavings in memory requirements compared to theoriginal sntuple-based recognition system.