Off-line Nepali Handwritten Character Recognition Using MLP and RBF Neural Networks
Date
2012
Authors
Pant, Ashok Kumar
Journal Title
Journal ISSN
Volume Title
Publisher
Department of Computer Science & Information Technology
Abstract
An off-line Nepali handwriting recognition, based on the neural networks, is described in this
research work. For the recognition of off-line handwritings with high classification rate a good
set of features as a descriptor of image is required. Two important categories of the features are
described, geometric and statistical features for extracting information from character images.
Directional features are extracted from geometry of skeletonized character image and statistical
features are extracted from the pixel distribution of skeletonized character image. The research
primarily concerned with the problem of isolated handwritten character recognition for Nepali
language. Multilayer Perceptron (MLP)& Radial Basis Function (RBF) classifiers are used for
classification. The principal contributions presented here are preprocessing, feature extraction
and MLP& RBF classifiers. The another important contribution is the creation of benchmark
dataset for off-line Nepali handwritings. There are three datasets for Nepali handwritten numerals,
Nepali handwritten vowels and Nepali handwritten consonants respectively. Nepali
handwritten numeral dataset contains total 288 samples for each 10 classes of Nepali numerals,
Nepali handwritten vowel dataset contains 221 samples for each 12 classes of Nepali vowels
and Nepali handwritten consonant dataset contains 205 samples for each 36 classes of Nepali
consonants. The strength of this research is efficient feature extraction and the comprehensive
classification schemes due to which, the recognition accuracy of 94.44% is obtained for Nepali
handwritten numeral dataset, 86.04% is obtained for Nepali handwritten vowel dataset and
80.25% is obtained for Nepali handwritten consonant dataset.
Keywords:
Off-line handwriting recognition, Image processing, Neural networks, Multilayer perceptron,
Radial basis function, Preprocessing, Feature extraction, Nepali handwritten datasets
Description
Keywords
Image processing, Feature extraction, Neural networks