| dc.contributor.author |
Kannan, Balakrishnan |
|
| dc.contributor.author |
Jomy, John |
|
| dc.contributor.author |
Pramod, K V |
|
| dc.date.accessioned |
2014-07-22T05:35:24Z |
|
| dc.date.available |
2014-07-22T05:35:24Z |
|
| dc.date.issued |
2012-12-31 |
|
| dc.identifier.issn |
1877-7058 |
|
| dc.identifier.uri |
http://dyuthi.cusat.ac.in/purl/4195 |
|
| dc.description |
Procedia Engineering 30 (2012) 598 – 605 |
en_US |
| dc.description.abstract |
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 |
en_US |
| dc.description.sponsorship |
Cochin University of Science and Technology |
en_US |
| dc.language.iso |
en |
en_US |
| dc.publisher |
Elsevier |
en_US |
| dc.subject |
handwritten character recognition |
en_US |
| dc.subject |
Haar wavelet transfor |
en_US |
| dc.subject |
support vector machine |
en_US |
| dc.subject |
RBF kernel |
en_US |
| dc.title |
Unconstrained Handwritten Malayalam Character Recognition using Wavelet Transform and Support vector Machine Classifier |
en_US |
| dc.type |
Article |
en_US |