Learning enhancement of online handwritten telugu character modeling for various features sets

Abstract

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 (∆x, ∆y), (∆2 x,∆2 y). Finally it is observed that (∆2 x,∆2 y) 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.