Integration of an on-line handwriting recognition system in a smart phone device

International audienceThis paper presents the evolving of our academic development to a technology driven application: the integration of an unconstraint cursive on-line handwritten character recognition system into a smart phone device. The ultimate goal of this work is to implement an accuracy handwriting recognizer into mobile devices with limited computing and memory resources. A hierarchical fuzzy modeling is used to obtain a compact and robust knowledge representation and the decision process is based on an adapted fuzzy inference system to reduce computing without decreasing the performances. We describe in this paper the basic architecture of the recognition system called " ResifCar " , its practical adaptation to the mobile device constraints and the recognition rates both on cursive isolated letters (91.9%) and on isolated digits (92.3%) in a writer independent context based on 100 different writers