Handwritten Word Recognition based on Structural Characteristics and Lexical Support

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Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 1

Edinburgh, Scotland

August 03-August 06

ISBN: 0-7695-1960-1

	ASCII Text	x
	E. Kavallieratou, K. Sgarbas, N. Fakotakis, G. Kokkinakis, "Handwritten Word Recognition based on Structural Characteristics and Lexical Support," Document Analysis and Recognition, International Conference on, vol. 1, pp. 562, Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 1, 2003.

	BibTex	x
	@article{ 10.1109/ICDAR.2003.1227727, author = {E. Kavallieratou and K. Sgarbas and N. Fakotakis and G. Kokkinakis}, title = {Handwritten Word Recognition based on Structural Characteristics and Lexical Support}, journal ={Document Analysis and Recognition, International Conference on}, volume = {1}, year = {2003}, isbn = {0-7695-1960-1}, pages = {562}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDAR.2003.1227727}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Document Analysis and Recognition, International Conference on TI - Handwritten Word Recognition based on Structural Characteristics and Lexical Support SN - 0-7695-1960-1 SP EP A1 - E. Kavallieratou, A1 - K. Sgarbas, A1 - N. Fakotakis, A1 - G. Kokkinakis, PY - 2003 KW - null VL - 1 JA - Document Analysis and Recognition, International Conference on ER -

E. Kavallieratou, University of Patras

K. Sgarbas, University of Patras

N. Fakotakis, University of Patras

G. Kokkinakis, University of Patras

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDAR.2003.1227727

In this paper a handwritten recognition algorithm based on structural characteristics, histograms and profiles, is presented. The well-known horizontal and vertical histograms are used, in combination with the newly introduced radial histogram, out-in radial and in- out radial profiles for representing 32x32 matrices of characters, as 280-dimension vectors.

The recognition process has been supported by a lexical component based on dynamic acyclic FSAs (Finite-State-Automata).

Citation:

E. Kavallieratou, K. Sgarbas, N. Fakotakis, G. Kokkinakis, "Handwritten Word Recognition based on Structural Characteristics and Lexical Support," icdar, vol. 1, pp.562, Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 1, 2003

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