Recognition of Online Handwritten Isolated Kannada Characters using PCA and DTW | Zendy

Keerthi Prasad G | Zendy; Vinay Hegde | Zendy

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Recognition of Online Handwritten Isolated Kannada Characters using PCA and DTW

Author(s) -

Keerthi Prasad G,

Vinay Hegde

Publication year - 2019

Publication title -

international journal of recent technology and engineering (ijrte)

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 , dynamic time warping , natural language processing , artificial intelligence , principal component analysis , 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.

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