An interval approach to handwriting recognition

A language is a set of symbols, signs, sounds, .... Each language has its own signs (Arab, Japanese, Latin....) that people discern easily. In fact, one gives these symbols (isolated or regrouped in a words or sentences) senses or meaning. It is a means of communication to describe our desires, our thought, our needs, .... Nevertheless, there are always basic references through which one communicates. These references are not fixed. They evolve with time, knowledge, experience.... Thus, machines "which understand human languages" have to recognize a given situation "in different sentences". This language can be written (handwritten recognition) or spoken (signal processing) or with gestures (computer vision) and grimaces (face recognition). In this paper, one is interested in the handwriting recognition which is one of the most difficult problems because of the diversity, and the no homogeneity of writing. In fact, to solve this problem, one is going to use the notion of references excessively.