Offline Handwritten Malayalam Word Recognition using Wavelet Transform

Authors

  • Jino P J  Artificial Intelligence Lab,Department of Computer Applications, Cochin University, Kerala, India
  • Kannan Balakrishnan  Department of Computer Applications , Cochin University,Kerala ,India

Keywords:

Offline Handwritten Recognition, Wavelet Transform ,Feature Extraction method, Pattern Recognition.

Abstract

Wavelet transforms of malaylam handwritten images are used for the recogntion. A comparative study with Haar, Daubechies wavelets are also performed. Lexicon contains fourteen district names and a total of 736 samples.More than 90 % of recogntion is achieved.Low Frequency components are considered as features. For the classification SVM used with RBF kernel.The Dimensionality of the wavelet coefficients are reduced by Principal Component Analysis(PCA).

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2017-10-31

Issue

Volume 2, Issue 5, September-October-2017

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Jino P J, Kannan Balakrishnan, " Offline Handwritten Malayalam Word Recognition using Wavelet Transform, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 5, pp.948-954, September-October-2017.