Comparison of Smoothing Techniques and Recognition Methods for Online Kannada Character Recognition System

Shwetha, D and Ramya, S N (2014) Comparison of Smoothing Techniques and Recognition Methods for Online Kannada Character Recognition System. In: IEEE International Conference on Advances in Engineering & Technology Research, August 01-02, 2014, Dr. Virendra Swarup Group of Institutions, Unnao, India.

[img] PDF
07012888_Comparison_of_Smoothing_Techniques.pdf - Published Version
Restricted to Registered users only

Download (957kB) | Request a copy

Abstract

This paper aimed at working on Online Recognition of Handwritten Kannada Characters. The recognition was done for the Top, Middle and Bottom strokes of Kannada characters. Genius MousePen i608X was used to collect the handwritten character samples to build the database. Handwritten character samples were collected for each character from a particular target-group which includes people who are native to Kannada language and belong to different age groups. These samples were semi-automatically validated, pre-processed and features were extracted. Segmentation of characters was done to divide the strokes into top stroke, middle stroke and bottom stroke. These segmented strokes were individually processed. The pre-processing techniques used in the project include removal of duplicated points, smoothing, interpolating missing points, resampling of points and size normalization. Smoothing techniques was compared for Gaussian and Moving Average Smoothing. Dominant point, writing direction and the curvature features were also extracted. In addition to this, recognition was carried out by KNN and SVM pattern recognition methods and a second level of verification rules was incorporated, yielding a maximum recognition rate of 92.5% for KNN and 94.35% for SVM

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Handwritten Kannada Characters; Character Recognition; Smoothing Algorithms; KNN; SVM
Subjects: Engineering > MIT Manipal > Electronics and Communication
Depositing User: MIT Library
Date Deposited: 25 Feb 2016 14:15
Last Modified: 01 Mar 2016 14:35
URI: http://eprints.manipal.edu/id/eprint/145392

Actions (login required)

View Item View Item