WSEAS Transactions on Signal Processing
Print ISSN: 1790-5052, E-ISSN: 2224-3488
Volume 11, 2015
A Robust System for Printed and Handwritten Character Recognition of Images Obtained by Camera Phone
Authors: , , ,
Abstract: In Recent years, character recognition has gained more importance in the area of pattern recognition owning to its application in various domains. The biggest challenge is to build an efficient optical character recognition system (OCR) able to recognize documents, also to allow overcoming the problems of blurred and noisy image. Many OCRs systems are been applied, but less interest have been given to document images obtained by camera phone. In this paper, we will present a complete offline handwritten and machine-printed character recognition system for isolated character acquired via camera-mobile. Our system includes five stages namely: preprocessing, segmentation, feature extraction and classification. We investigated various techniques in the preprocessing stage in order to select the best. In feature extraction and classification stages, we examined several features methods with three different types of classifiers The Support vector machines (SVM), The Naïve Bayes (NB) and the Multilayer Perceptron (MLP). We performed the experiments with two databases of handwritten and machine-printed character images. The results indicate that the proposed system is very effective and yields good recognition rate for character images obtained by camera phone.
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Pages: 9-22
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #2