Handwritten Character Recognition System using Gabor Filter and SVM Classifier

Journal

International Journal of Digital Applications and Contemporary Research (IJDACR)

ISSN

2319-4863

Volume / Issue

Vol.6 · Issue 9

Published

April 2018

Access

Open Access

Licence

CC BY-NC-SA 4.0

Sandli Bansal Komal Paliwal

The selection of features is an important step in any pattern recognition system. This selection of features is considered a combinatorial optimization problem and made the object of research in many disciplines. The main objective of the selection of features is to reduce the number of them by eliminating redundant and irrelevant features recognition system. The second objective of this feature selection is also to maintain and/or improve the performance of the classifier used by the recognition system. In this paper, support vector machine (SVM) based approach is proposed to solve this type of problem in the recognition of handwritten character. This work is capable of recognizing handwritten character with the help of morphological operation, edge detection, feature extraction using Gabor filter and support vector machine (SVM) based classifier

Sandli Bansal, Komal Paliwal (2018). Handwritten Character Recognition System using Gabor Filter and SVM Classifier. International Journal of Digital Applications and Contemporary Research (IJDACR), Vol.6, Issue 9. ISSN: 2319-4863.

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