Analysis of Handwritten Hindi Character Recognition using Advanced Feature Extraction Technique and Back propagation Neural Network
Dayashankar Singha, J. P. Sainib, D. S. Chauhan · International Journal of Computer Applications · 2014
Feature extraction techniques play an important role in pattern recognition. Neural networks are being used for character/pattern recognition since last many years but most of the works are confined to English character recognition. Till date, a very little work has been reported for Handwritten Hindi Character recognition. The main challenge is to maintain high performance level with samples, which are distorted or written in more personal style. Handwritings of every person are different due to the great variations of individual writing styles, different size and orientation angle of the characters. In this paper, conventional feature extraction (Global pixel), Gradient feature extraction and 8-Directional Gradient Feature (8-DGF) Extraction, 16- Directional Gradient Feature Extraction (16-DGF) technique for handwritten Hindi character recognition