RECOGNITION OF PERSIAN ONLINE HANDWRITING USING ELASTIC FUZZY PATTERN RECOGNITION

摘要

Persian is a fully cursive handwriting in which each character may take different forms in different parts of the word, characters overlap and there is a wide range of possible styles. These complexities make automatic recognition of Persian a very hard task. This paper presents a novel approach on recognition of such writings systems which is based on the description of input stream by a sequence of fuzzy linguistic terms; representation of character patterns with the same descriptive language; and comparison of inputs with character patterns using a novel elastic pattern matching approach. As there is no general benchmark for recognition of Persian handwriting, the approach has been tested on the set of words in first primary Iranian school books including 1250 words resulting in 78% correct recognition without dictionary and 96% with dictionary.