International Journal of Image, Graphics and Signal Processing (IJIGSP)
IJIGSP Vol. 5, No. 4, 8 Apr. 2013
Cover page and Table of Contents: PDF (size: 523KB)
A System for Offline Recognition of Handwritten Characters in Malayalam Script
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Author(s)
Index Terms
Character recognition, Malayalam, Gradient, Curvature, Principal Component Analysis, SVM, RBF
Abstract
In this paper, we propose a handwritten character recognition system for Malayalam language. The feature extraction phase consists of gradient and curvature calculation and dimensionality reduction using Principal Component Analysis. Directional information from the arc tangent of gradient is used as gradient feature. Strength of gradient in curvature direction is used as the curvature feature. The proposed system uses a combination of gradient and curvature feature in reduced dimension as the feature vector. For classification, discriminative power of Support Vector Machine (SVM) is evaluated. The results reveal that SVM with Radial Basis Function (RBF) kernel yield the best performance with 96.28% and 97.96% of accuracy in two different datasets. This is the highest accuracy ever reported on these datasets.
Cite This Paper
Jomy John,Kannan Balakrishnan,Pramod K. V,"A System for Offline Recognition of Handwritten Characters in Malayalam Script", IJIGSP, vol.5, no.4, pp.53-59, 2013. DOI: 10.5815/ijigsp.2013.04.07
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