Unconstrained Handwritten Malayalam Character Recognition using Wavelet Transform and Support vector Machine Classifier


Autoria(s): Kannan, Balakrishnan; Jomy, John; Pramod, K V
Data(s)

22/07/2014

22/07/2014

31/12/2012

Resumo

This paper presents the application of wavelet processing in the domain of handwritten character recognition. To attain high recognition rate, robust feature extractors and powerful classifiers that are invariant to degree of variability of human writing are needed. The proposed scheme consists of two stages: a feature extraction stage, which is based on Haar wavelet transform and a classification stage that uses support vector machine classifier. Experimental results show that the proposed method is effective

Procedia Engineering 30 (2012) 598 – 605

Cochin University of Science and Technology

Identificador

1877-7058

http://dyuthi.cusat.ac.in/purl/4195

Idioma(s)

en

Publicador

Elsevier

Palavras-Chave #handwritten character recognition #Haar wavelet transfor #support vector machine #RBF kernel
Tipo

Article