Please use this identifier to cite or link to this item: http://gukir.inflibnet.ac.in:8080/jspui/handle/123456789/3653
Full metadata record
DC FieldValueLanguage
dc.contributor.authorRajput G.G
dc.contributor.authorHorakeri R.
dc.date.accessioned2020-06-12T15:01:04Z-
dc.date.available2020-06-12T15:01:04Z-
dc.date.issued2011
dc.identifier.citation2011 2nd International Conference on Computer and Communication Technology, ICCCT-2011 , Vol. , , p. 135 - 141en_US
dc.identifier.uri10.1109/ICCCT.2011.6075175
dc.identifier.urihttp://gukir.inflibnet.ac.in:8080/jspui/handle/123456789/3653-
dc.description.abstractIn this paper, we discuss the implementation of shape based features, namely, Fourier descriptors and chain codes, for performing optical character recognition of binary images with application to Kannada handwritten characters. Invariant Fourier descriptors and normalized chain codes are obtained as features from preprocessed Kannada character binary images. Well known SVM classifier is used for recognition purpose. As an initial step towards recognition of handwritten characters, we have performed experiments on handwritten Kannada character numerals and vowels. The result computation is done using five-fold cross validation. The mean performance of the recognition system with the two shape based features together is 98.45% and 93.92%, for numeral characters and vowels, respectively. Further, the mean recognition rate of 95% is obtained for both vowels and characters taken together. © 2011 IEEE.en_US
dc.subjectchain codes
dc.subjectfive-fold cross validation
dc.subjectFourier descriptors
dc.subjectKannada characters
dc.subjectSVM
dc.titleShape descriptors based handwritten character recognition engine with application to Kannada charactersen_US
dc.typeConference Paper
Appears in Collections:2. Conference Papers

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.