Offline Handwritten Malayalam Word Recognition using Wavelet Transform

Authors(2) :-Jino P J, Kannan Balakrishnan

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).

Authors and Affiliations

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

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

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Publication Details

Published in : Volume 2 | Issue 5 | September-October 2017
Date of Publication : 2017-10-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 948-954
Manuscript Number : CSEIT1725221
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Jino P J, Kannan Balakrishnan, "Offline Handwritten Malayalam Word Recognition using Wavelet Transform", International 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.
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