Online Farsi Character Recognition Using Structural Features

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.