Neural network based optical character recognition system

Author

Dojcinovic, N. ; Mihajlovic, I. ; Jokovic, Jugoslav ; Markovic, Vera ; Milovanovic, Bratislav

Author_Institution

Innovation Center of ETF, Univ. of Belgrade, Belgrade, Serbia

fYear

2012

fDate

20-22 Sept. 2012

Firstpage

111

Lastpage

114

Abstract

This paper presents an application of a neural network in the optical character recognition (OCR) system. It introduces general architecture of modern OCR systems, discussing each module in detail. Specific contribution of this paper is novelty of the character extraction and segmentation, by considering them as image features. MSER (Maximally Stable Extremal Regions) feature detector is applied, discussing numerical and practical restrictions for character segmentation and recognition. The neural network is trained for character recognition and applied on the appropriate example.

Keywords

feature extraction; image segmentation; learning (artificial intelligence); neural nets; optical character recognition; MSER feature detector; OCR systems; character extraction; character segmentation; image features; maximally stable extremal regions; neural network training; optical character recognition system; Accuracy; Biological neural networks; Character recognition; Feature extraction; Noise; Optical character recognition software; Training; Hu´s moments; MSER; OCR; character extraction; character segmentation; neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Network Applications in Electrical Engineering (NEUREL), 2012 11th Symposium on

Conference_Location

Belgrade

Print_ISBN

978-1-4673-1569-2

Type

conf

DOI

10.1109/NEUREL.2012.6419976

Filename

6419976