Abstract

Introduction Today, handwriting recognition is one of the most challenging tasks and exciting areas of research in computer science. Indeed, despite the growing interest in this field, no satisfactory solution is available. The difficulties encountered are numerous and include the huge variability of handwriting such as inter-writer and intra-writer variabilities, writing environment (pen, sheet, support, etc.), the overlap between characters, and the ambiguity that makes many characters unidentifiable without referring to context. Owing to these difficulties, many researchers have integrated the lexicon as a constraint to build lexicon-driven strategies to decrease the problem complexity. For small lexicons, as in bank-check processing, most approaches are global and consider a word as an indivisible entity [1] - [5]. If the lexicon is large, as in postal applications (city name or street name recognition) [6] - [10], one cannot consider a word as one entity, because of the huge num

Citations