1. A method for online character recognition of Arabic text, the method comprising the procedures of: receiving handwritten Arabic text from a user in the form of handwriting strokes; sampling said handwriting strokes to acquire a sequence of two-dimensional point representations thereof, including associated temporal data; geometrically pre-processing and extracting features on said point representations; detecting delayed strokes and word-parts in said pre-processed point representations; projecting said delayed strokes onto the body of said word-parts; constructing feature vector representations for each said word-part, thereby generating an observation sequence; generating at least one word-part dictionary indexed in accordance with word features, wherein: said at least one word-part dictionary is a sub-dictionary of a dictionary that includes a set of valid words; and said at least one word-part dictionary contains words having a predetermined integer number of word-parts; and determining the word in part according to said at least one word-part dictionary with maximum probability given said observation sequence, resulting in a list of word probabilities; wherein each said word-part refers to an intra-connected portion of a word, which is bounded on each side by a minimal amount of space in the text.
6. The method according to claim 1 , wherein said features are selected from the list consisting of: the number of word-parts in a word; the local-angle; the super-segment; the presence of loops; the position of a loop in a word-part; the presence of cusps; the presence of crossings; the number of closed curves; the number of indented sections; the number of dots; the location of a dot; the type of a delayed stroke; an indication whether a word-part begins with a curved shape; and the context of a word.