Reddy, Nirup and Kandan, R and Shashikiran, K and Suresh, S and Ramakrishnan, AG (2008) Online character recognition using regression techniques. In: Proc. IEEE Workshop on applications of computer vision (WACV 2008).Full text not available from this repository.
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.
|Item Type:||Conference Paper|
|Department/Centre:||Division of Electrical Sciences > Electrical Engineering|
|Date Deposited:||20 Sep 2011 07:07|
|Last Modified:||20 Sep 2011 07:07|
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