Title: A handwritten Bangla numeral recognition scheme based on expanded two-layer SOM

Authors: Shujing Lu, Xiao Tu, Yue Lu

Addresses: ECNU-SRI Joint Lab for Pattern Analysis and Intelligence System, Department of Computer Science and Technology, East China Normal University, Shanghai 200241, China. ' ECNU-SRI Joint Lab for Pattern Analysis and Intelligence System, Department of Computer Science and Technology, East China Normal University, Shanghai 200241, China. ' ECNU-SRI Joint Lab for Pattern Analysis and Intelligence System, Department of Computer Science and Technology, East China Normal University, Shanghai 200241, China

Abstract: This paper proposes a system for handwritten Bangla numeral recognition based on expanded two-layer self-organising map (SOM), in which every map in the second layer expands from a corresponding neuron in the first layer map. It carries out multiple classifications in the second layer for each character sample. The exact classification of the character image is obtained by a fusion algorithm using confidence coefficients. The discriminability of SOM is improved by this structure. With the directional and density features as the input vector, the experiments on handwritten Bangla numeral samples have achieved satisfactory recognition performance.

Keywords: handwritten Bangla; numeral recognition; two-layer SOM; self-organising maps; confidence coefficients; multiple classification; character images; number recognition.

DOI: 10.1504/IJISTA.2011.039020

International Journal of Intelligent Systems Technologies and Applications, 2011 Vol.10 No.2, pp.203 - 213

Available online: 11 Mar 2011 *

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