Hand-printed character recognition system using artificial neural networks

Author

Amin, Adnan ; Wilson, W.H.

Author_Institution

Sch. of Comput. Sci. & Eng., Univ. of South Wales, Kensington, NSW, Australia

fYear

1993

fDate

20-22 Oct 1993

Firstpage

943

Lastpage

946

Abstract

A new technique is proposed for the recognition of hand-printed Latin characters using artificial neural networks together with conventional techniques. One advantage of this technique is that it combines rule-based (structural) and classification tests. Another advantage is that it it more efficient for large and complex sets. The technique can be divided into five major steps: (1) digitization of the image; (2) thinning of the binary image using a parallel thinning algorithm; tracing of the tree; (3) tracing of the skeleton of the image and construction of a binary tree; (4) extraction of features from the structural information; and (5) classification of the segmented descriptions as particular characters by a feedforward neural network trained by backpropagation

Keywords

character recognition; feature extraction; feedforward neural nets; image recognition; pattern classification; artificial neural networks; backpropagation; binary image thinning; binary tree; classification tests; complex sets; feedforward neural network; hand-printed Latin characters; hand-printed character recognition; image digitisation; image skeleton tracing; parallel thinning algorithm; rule-based structural tests; segmented descriptions; structural information; Artificial neural networks; Backpropagation algorithms; Binary trees; Character recognition; Classification tree analysis; Data mining; Feature extraction; Image segmentation; Skeleton; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on

Conference_Location

Tsukuba Science City

Print_ISBN

0-8186-4960-7

Type

conf

DOI

10.1109/ICDAR.1993.395581

Filename

395581