Online preprocessing of handwritten Gurmukhi strokes

Authors:
Anuj Sharma;R. K. Sharma;Rajesh Kumar
Affiliations:
Department of Mathematics, Punjab University, Chandigarh, India;SMCA, Thapar University, Patiala, India;SMCA, Thapar University, Patiala, India
Venue:
Machine Graphics & Vision International Journal
Year:
2009

Citing 17
Cited 1

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Abstract

In this paper, the authors have implemented preprocessing algorithms for online handwritten Gurmukhi strokes in order to find the improvements in recognition of four high-level features (loop, headline, straight line and dot) of Gurmukhi strokes. Preprocessing algorithms include size normalization and centering, interpolating missing points, smoothing, slant correction and resampling of points. Recognition algorithms for the above mentioned four high-level features are also introduced in this paper. Experiments have been conducted across 60 writers and 5%, 3.33%, 6.66% and 8.34% improvements have been observed for recognition of loop, headline, straight line and dot features, respectively, after using preprocessing algorithms.