Open AccessRecognition of Online Handwritten Isolated Kannada Characters using PCA and DTW
Author(s) -
Khiem H. G,
Vinay Hegde
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d7810.118419
Subject(s) - kannada , computer science , scripting language , handwriting , speech recognition , natural language processing , dynamic time warping , artificial intelligence , principal component analysis , documentation , pattern recognition (psychology) , programming language
Handwriting is a natural means of documentation and communication for several years. Human beings communicating with computers through handwritten input would be the best and easiest way of exchanging the information. It is difficult to input data for computers for Indian language scripts because of their complex typing nature. This paper focuses on exploring performance of Principal Component Analysis (PCA) and Dynamic Time Wrapping (DTW) approaches for recognizing online handwritten isolated Kannada characters. Methodology proposed in this paper is writer independent model which recognizes basic 50 Kannada characters including 16 vowels and 34 consonants.