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Copper Mountain, CO, USA
Jan. 7, 2008 to Jan. 9, 2008
ISBN: 978-1-4244-1913-5
pp: 1-6
Nirup Reddy , MILE, Department of Electrical Engineering, IISc Bangalore-560012, India, nirupreddy@gmail.com
R Kandan , MILE, Department of Electrical Engineering, IISc Bangalore-560012, India, kandan.r@gmail.com
K Shashikiran , MILE, Department of Electrical Engineering, IISc Bangalore-560012, India, shashi.1980@yahoo.com
Suresh Sundaram , MILE, Department of Electrical Engineering, IISc Bangalore-560012, India, suresh@ee.iisc.ernet.in
A G Ramakrishnan , MILE, Department of Electrical Engineering, IISc Bangalore-560012, India, ramkiag@ee.iisc.ernet.in
ABSTRACT
This paper introduces a scheme for classification of online handwritten characters based on polynomial regression of the sampled points of the sub-strokes in a character. The segmentation is done based on the velocity profile of the written character and this requires a smoothening of the velocity profile. We propose a novel scheme for smoothening the velocity profile curve and identification of the critical points to segment the character. We also porpose another method for segmentation based on the human eye perception. We then extract two sets of features for recognition of handwritten characters. Each sub-stroke is a simple curve, a part of the character, and is represented by the distance measure of each point from the first point. This forms the first set of feature vector for each character. The second feature vector are the coeficients obtained from the B-splines fitted to the control knots obtained from the segmentation algorithm. The feature vector is fed to the SVM classifier and it indicates an efficiency of 68% using the polynomial regression technique and 74% using the spline fitting method.
CITATION
Nirup Reddy, R Kandan, K Shashikiran, Suresh Sundaram, A G Ramakrishnan, "Online Character Recognition using Regression Techniques", WACV, 2008, Applications of Computer Vision, IEEE Workshop on, Applications of Computer Vision, IEEE Workshop on 2008, pp. 1-6, doi:10.1109/WACV.2008.4544038
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