Persian cursive script recognition
Mahmoud Reza Hashemi, Omid Fatemi, Rojin Safavi · 2002
The main objective of this paper is to design a Persian text recognition system. As even typed Persian scripts are cursive, our system includes a segmentation stage in order to separate the constituent characters. This stage is also useful for highly declined or italic Latin texts. A new segmentation algorithm with two consecutive steps is introduced in this paper. The first step separates isolated and non overlapped characters as well as some overlapped ones. The second step segments not connected overlapped characters. The novel segmentation method has been tested on some real world script and has shown an accuracy rate of more than 99.7%. In the recognition stage which involves a statistical approach, two types of feature sets along with different classification methods are evaluated.