Open AccessLearning Enhancement of Online Handwritten Telugu Character Modeling for Various Features Sets
Author(s) -
Goda Srinivasarao,
Rajeswara Rao Ramisetty
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.a3087.109119
Subject(s) - telugu , character (mathematics) , computer science , artificial intelligence , feature (linguistics) , artificial neural network , pattern recognition (psychology) , feature extraction , natural language processing , speech recognition , mathematics , linguistics , philosophy , geometry
Feature extraction plays vital role in online hand written character recognition. Local Features captured through co-ordinate system approach plays significant role in determining the online telugu character recognition. In this paper, we have instigated the performance of various features using Artificial Neural Networks( ANNs). ANN model is tested with various combination such as (x,y) co-ordinates , pen-up and pen-down ) , ( y x , ( ) y x 2 2 , . Finally it is observed that ( ) y x 2 2 , features have given better accuracy. 95.18 % performance is obtained for 300 epochs for 52 Telugu characters. The database used for the study is HP-online Telugu database.