Hand-Written Character/Digit Recognition using Shape Descriptor

S. Srisuk, M. Tamsri, R. Fooprateepsiri, W. Kurutach and J. Suwatcharakulthorn

Advanced Machine Intelligence Research Laboratory, Department of Computer Engineering

Department of Information Technology

Mahanakorn University of Technology, Bangkok, Thailand 10530

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Manuscript received October 30, 2003,

Revised January 22, 2004

 

 


Abstract

In this paper, we present a new approach for hand-written character and digit recognitions based on shape descriptor and the Hausdorff Context. We start at finding the corresponding points between two shapes by using shape context histogram. We then use these correspondences as key geometric points for shape alignment with the Thin Plate Spline model. After the transformation has been applied completely, the distance between two shapes is computed by a new distance measure, the Hausdorff Context. We achieve a very high recognition rate of 97.4% on 268 images.

 

Keywords: Hausdorff Context, Distorted Object Recognition, Shape Context, Thin Plate Spline

 

 

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