International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
Volume 92 - Issue 12 |
Published: April 2014 |
Authors: Anil R, Arjun Pradeep, Midhun E M, Manjusha K |
![]() |
Anil R, Arjun Pradeep, Midhun E M, Manjusha K . Malayalam Character Recognition using Singular Value Decomposition. International Journal of Computer Applications. 92, 12 (April 2014), 6-11. DOI=10.5120/16059-5167
@article{ 10.5120/16059-5167, author = { Anil R,Arjun Pradeep,Midhun E M,Manjusha K }, title = { Malayalam Character Recognition using Singular Value Decomposition }, journal = { International Journal of Computer Applications }, year = { 2014 }, volume = { 92 }, number = { 12 }, pages = { 6-11 }, doi = { 10.5120/16059-5167 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2014 %A Anil R %A Arjun Pradeep %A Midhun E M %A Manjusha K %T Malayalam Character Recognition using Singular Value Decomposition%T %J International Journal of Computer Applications %V 92 %N 12 %P 6-11 %R 10.5120/16059-5167 %I Foundation of Computer Science (FCS), NY, USA
This paper provides a classification methodology of Malayalam characters segmented from scanned document images. Optical Character Recognition (OCR) is one of the successful area which has wide variety of applications related to pattern recognition. This paper describes segmented character recognition using Singular Value Decom- position (SVD). Euclidean distance measure is used for finding the nearest character class of the segmented character image during testing. For each character class, a resultant template is created from training character images using the proposed approach, which in turn reduces the comparisons required for classification. The result obtained from the experiment shows that this method provides an accuracy of 97%.