Recognition of Persian handwritten digits using image profiles of multiple orientations

Authors:
Hasan Soltanzadeh;Mohammad Rahmati
Affiliations:
Computer Engineering Department, Amirkabir University of Technology (Tehran Polytechniques), Tehran, Iran;Computer Engineering Department, Amirkabir University of Technology (Tehran Polytechniques), Tehran, Iran
Venue:
Pattern Recognition Letters
Year:
2004

Citing 6
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Abstract

In this paper a new approach for recognition of Persian (Arabic) handwritten digits is presented. This method utilizes the outer profiles of the digit image that are calculated at multiple orientations, as the main feature. Furthermore, the crossing counts and projection histograms of the image are used as complementary features. Similar to the profile features, these features are also calculated at multiple orientations. In the classification stage of our proposed method the support vector machines are applied. Evaluating the proposed system with approximately 4000 test samples the recognition rate of 99.57% is achieved.