Please use this identifier to cite or link to this item: http://hdl.handle.net/10266/4203
Title: Segmentation of lā -consonant and duláwā -consonant combination strokes in online handwritten Gurmukhi script recognition
Authors: Kaleka, Navneet Kaur
Supervisor: Verma, Karun
Keywords: Preprocessing;Normalization;Interpolation;Resampling;Smoothing;Segmentation
Issue Date: 30-Aug-2016
Abstract: Online handwriting recognition has been spot of interest for research and has been worked upon for a long time now. Online Handwriting recognition has been done for some scripts all over the world. Great milestones have been reached in research on the online handwriting recognition for Indian scripts as well. I decided to work on Gurmukhi script. The fastness in writing Gurumukhi has led to the cursive nature of the script, there by leading to a combination of strokes written in a single stroke. These types of strokes are unrecognizable to the classifier. Segmentation algorithm has been proposed that use the slope calculation method at every point and find candidate points for segmenting the stroke into individual basic strokes. The algorithms demonstrated an accuracy of 95% in segmenting various stroke combinations when written in a single stroke.
URI: http://hdl.handle.net/10266/4203
Appears in Collections:Masters Theses@CSED

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