Title :
Neural network recognition and analysis of hand-printed characters
Author :
Singh, Sameer ; Amin, Adnan
Author_Institution :
Plymouth Univ., UK
Abstract :
The main objective of this paper is to introduce a novel method of feature extraction for character data and develop a neural network system for recognising different Latin characters. In this paper we describe feature extraction, neural network development for character recognition and perform further neural network analysis on noisy image segments to explain the qualitative and quantitative aspects of handwriting
Keywords :
feature extraction; image segmentation; neural nets; noise; optical character recognition; Latin characters; Roman letters; feature extraction; hand-printed character analysis; hand-printed character recognition; handwriting; neural network; noisy image segments; qualitative aspect; quantitative aspect; Artificial neural networks; Binary trees; Character recognition; Feature extraction; Gaussian noise; Image analysis; Image segmentation; Neural networks; Skeleton; Working environment noise;
Conference_Titel :
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4859-1
DOI :
10.1109/IJCNN.1998.687120
