Authors:
Fahimeh Mostofi
and
Adnan Khashman
Affiliation:
Near East University, Turkey
Keyword(s):
Ancient Script, Persian Cuneiform Language, Character Recognition, Image Processing, Neural Networks.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Image Processing and Artificial Vision Applications
;
Methodologies and Methods
;
Neural Based Data Mining and Complex Information Processing
;
Neural Networks
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Theory and Methods
Abstract:
This paper presents an intelligent character recognition system based on utilising a back propagation neural network model. The characters in question are unique and rare to be addressed in such applications. These are the ancient Persian Cuneiform alphanumerical characters. The recognition system comprises firstly, image processing phase where clear and noisy or degraded images of the ancient script are prepared for processing by the neural model in the second phase. The importance of such application lies in its potential to make translating ancient scripts and language easier, faster and more efficient. Experimental results indicate that our proposed method can be further applied successfully to other ancient languages and may be utilised in museums and similar environments.