Multi-phase recognition of multifont photoscript Arabic text

A new system for the recognition of a multifont photoscript Arabic text is introduced. The distinguishing feature of such text is that it is written cursively. This imposes an additional requirement of isolating each character or set of overlapping characters before recognition. The proposed system is composed of three interleaved phases. The segmentation phase attempts to produce an initial set of characters from the connected text according to a set of predefined rules. The output is then passed to a preliminary classification phase that attempts to label the unknown characters into one of ten possible classes according to a set of rules that acquire their parameter values through learning. The last phase contains a more elaborate set of rules that recognize characters within each class. This recognition phase is designed to allow errors during segmentation and/or classification to be rectified through an adaptive recognition technique. The system has been implemented and tested on several fonts with a recognition rate of 130 words/min and an error rate of less than 6%.<>