Authors:
Eva Volna
;
Vaclav Kocian
;
Michal Janosek
;
Hashim Habiballa
and
Vilem Novak
Affiliation:
University of Ostrava, Czech Republic
Keyword(s):
Hebb Network, Adaline, Backpropagation Network, Fuzzy Logic, Pattern Recognition, Classifiers.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Data Manipulation
;
Enterprise Information Systems
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Neural Network Software and Applications
;
Neural Networks
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Theory and Methods
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.