A comparative study for character recognition using neural networks

Abstract

In this paper, a comparative study is conducted on a number of networks to find the best classification performance for printed English characters. Hierarchical Artificial Neural Network (HANN) architecture is used to reduce the misclassifications due to noisy patterns. The training patterns are extracted features of the characters using Fast Fourier Transforms and/or H-V scanning features.

Keywords:

• Pattern classification
• hierarchical ANN
• waveform analyses

C.R. Categories::

• I. 5.2
• I. 5.4