| dc.contributor.author |
Sreeraj, M |
|
| dc.contributor.author |
Sumam, Mary Idicula |
|
| dc.date.accessioned |
2014-07-30T05:46:28Z |
|
| dc.date.available |
2014-07-30T05:46:28Z |
|
| dc.date.issued |
2009-12-09 |
|
| dc.identifier.uri |
http://dyuthi.cusat.ac.in/purl/4314 |
|
| dc.description |
2009 World Congress on Nature & Biologically Inspired Computing (NaBIC 2009) |
en_US |
| dc.description.abstract |
This paper presents an efficient Online Handwritten
character Recognition System for Malayalam Characters
(OHR-M) using Kohonen network. It would help in
recognizing Malayalam text entered using pen-like devices. It
will be more natural and efficient way for users to enter text
using a pen than keyboard and mouse. To identify the
difference between similar characters in Malayalam a novel
feature extraction method has been adopted-a combination of
context bitmap and normalized (x, y) coordinates. The system
reported an accuracy of 88.75% which is writer independent
with a recognition time of 15-32 milliseconds |
en_US |
| dc.description.sponsorship |
Cochin University of Science and Technology |
en_US |
| dc.language.iso |
en |
en_US |
| dc.publisher |
IEEE |
en_US |
| dc.subject |
Malayalam handwritten characters |
en_US |
| dc.subject |
Artificial Neural Network |
en_US |
| dc.subject |
Feature extraction |
en_US |
| dc.subject |
Kohonen network (SOM) |
en_US |
| dc.title |
On-Line Handwritten Character Recognition using Kohonen Networks |
en_US |
| dc.type |
Article |
en_US |