HANDWRITTEN CHARACTER RECOGNITION OF SIMILAR LOOKING LETTERS USING ANGULAR FEATURE EXTRACTION METHOD

Authors

  • APARNA S MENON Research Student, Electronics and Communication Dept. NSS College of Engineering, Palakkad, Kerala, India
  • KALA L Associate Professor, Electronics and Communication Dept. NSS College of Engineering, Palakkad, Kerala, India.

Keywords:

HCR, k –NN, Fuzzy logic and machine learning

Abstract

Classification of similar looking handwritten characters in Indian languages is challenging. Especially in the case of Malayalam, a Dravidian language from the Brahmic script which is characterized by its highly curvy and looped nature.  So by considering such a nature of the language, a new feature extraction method in the field of HCR (Handwritten Character Recognition) named as Angular Method is used by using fuzzy logic classifiers with k –NN algorithm.

Downloads

Published

2021-02-19

How to Cite

APARNA S MENON, & KALA L. (2021). HANDWRITTEN CHARACTER RECOGNITION OF SIMILAR LOOKING LETTERS USING ANGULAR FEATURE EXTRACTION METHOD. JournalNX - A Multidisciplinary Peer Reviewed Journal, 4(07), 1–4. Retrieved from https://repo.journalnx.com/index.php/nx/article/view/2002

Issue

Vol. 4 No. 07 (2018): journalnx

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Similar Articles

<< < 5 6 7 8 9 10 11 12 13 14 > >> 

You may also start an advanced similarity search for this article.