A Study of Representations for Pen based Handwriting Recognition of Tamil Characters

In this paper we study the important issue of choosing representations that are suitable for recognizing pen based handwriting of characters in Tamil, a language of India. Four different choices, based on the following set of features are considered: (1) a sequence of directions and curvature; (2) a sequence of angles; (3) Fourier transform coefficients; and (4) wavelet features. We provide arguments in support of the representation using wavelet features. A neural network designed using these features gives excellent accuracy for recognizing Tamil characters.

• Type: Conference
• Year: 1999
• Where: ICDAR
• Authors: C. S. Sundaresan, S. Sathiya Keerthi
• Keywords: Document Analysis, Fourier Transform Coefficients, ICDAR 1999, Pen Based Handwriting, Wavelet Features