Character recognition based on global feature extraction

This paper presents a enhanced feature extraction method which is a combination and selected of two feature extraction techniques of Gray Level Co occurrence Matrix (GLCM) and Edge Direction Matrixes (EDMS) for character recognition purpose. It is apparent that one of the most important steps in a c...

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Bibliographic Details
Published inProceedings of the 2011 International Conference on Electrical Engineering and Informatics pp. 1 - 4
Main Authors Naeimizaghiani, M., Abdullah, S. N. H. S., Bataineh, B., PirahanSiah, F.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2011
Subjects
Accuracy
Character recognition
Decision trees
Feature extraction
Image edge detection
image processing
OCR
Support vector machines
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ISBN1457707535
9781457707537
ISSN2155-6822
DOI10.1109/ICEEI.2011.6021649

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Summary:This paper presents a enhanced feature extraction method which is a combination and selected of two feature extraction techniques of Gray Level Co occurrence Matrix (GLCM) and Edge Direction Matrixes (EDMS) for character recognition purpose. It is apparent that one of the most important steps in a character recognition system is selecting a better feature extraction technique, while the variety of method makes difficulty for finding the best techniques for character recognition. The dataset of images that has been applied to the different feature extraction techniques includes the binary character with different sizes. Experimental results show the better performance of proposed method in compared with GLCM and EDMS method after performing the feature selection with neural network, bayes network and decision tree classifiers.
ISBN:1457707535
9781457707537
ISSN:2155-6822
DOI:10.1109/ICEEI.2011.6021649