Damaged Letter Recognition Methodology - A Comparison Study

Eva Volna, Vaclav Kocian, Michal Janosek, Hashim Habiballa, Vilem Novak

2013

Abstract

The problem of optical character recognition is often solved, not only in the field of artificial intelligence itself, but also in everyday computer usage. We encountered this problem within the industrial project solved for real-life application. Best solver of such a task still remains human brain. Human beings are capable of character recognition even for damaged and highly incomplete images. In this paper, we present alternative softcomputing methods based on application of neural networks and fuzzy logic with evaluated syntax. We proposed a methodology of damaged letters recognition, which was experimentally verified. All experimental results were mutually compared in conclusion. Training and test sets were provided by Company KMC Group, s.r.o.

Paper Citation

in Harvard Style

Volna E., Kocian V., Janosek M., Habiballa H. and Novak V. (2013). Damaged Letter Recognition Methodology - A Comparison Study . In Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2013) ISBN 978-989-8565-77-8, pages 535-541. DOI: 10.5220/0004631005350541

in Bibtex Style

@conference{ncta13,
author={Eva Volna and Vaclav Kocian and Michal Janosek and Hashim Habiballa and Vilem Novak},
title={Damaged Letter Recognition Methodology - A Comparison Study},
booktitle={Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2013)},
year={2013},
pages={535-541},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004631005350541},
isbn={978-989-8565-77-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2013)
TI - Damaged Letter Recognition Methodology - A Comparison Study
SN - 978-989-8565-77-8
AU - Volna E.
AU - Kocian V.
AU - Janosek M.
AU - Habiballa H.
AU - Novak V.
PY - 2013
SP - 535
EP - 541
DO - 10.5220/0004631005350541