Online Farsi Character Recognition Using Structural Features
Subject Areas : Renewable energy
Vahid Ghods
1
(
Lecture/Semnan Branch, Islamic Azad University
)
Ehsanollah Kabir
2
(
Professor/Tarbiat Modarres University, Tehran
)
Keywords: recognition, grouping, Farsi, Decision tree, Online handwriting, Discrete letters,
Abstract :
In this paper, grouping and recognition of online Farsi discrete characters are presented according to their structural features. The letters are divided into 9 groups based on the form and structure of their main bodies. After feature extraction, grouping is performed using a decision tree. Final recognition of letters is carried out in each group by delayed strokes. The proposed method is a rapid method in character recognition because time-consuming methods have not been used. Our proposed method was tested on TMU-OFS dataset, and a recognition rate of 94% and 92% was achieved for character grouping and recognition, respectively. The mean processing time for recognizing a letter was 3ms.
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