1. A method of on-line input handwritten character recognition for recognizing individual handwritten characters each formed by ordinary strokes sampled on-line, wherein the ordinary strokes of a handwritten character are strokes defined by continuous pen movement on a writing surface from a position whereat the pen is placed on the writing surface to a position whereat the pen is lifted from the writing surface, comprising the steps of: converting each of said ordinary strokes of a handwritten character into component vectors having absolute angles representing directional information; determining and converting transition strokes of the handwritten character, defined by pen movement, off a writing surface, from an end of an ordinary stroke to a beginning of a next ordinary stroke of the handwritten character, into component vectors having absolute angles representing directional information; determining and converting start-end strokes of the handwritten character, defined by pen movement from a starting point of a first ordinary stroke to starting points and ending points of each of subsequent ordinary strokes of the handwritten character, into component vectors having absolute angles representing directional information; dividing said absolute angles into a group of fuzzy vectors for the handwritten character indicative of reference directions; converting said fuzzy vectors into membership grades of a plurality of directions representing similarity measures respectively corresponding to said reference directions by using a predetermined membership function; calculating one of a similarity measure and a dissimilarity measure between the group of fuzzy vectors described with said converted membership grades and character data from dictionary data described with a fuzzy vector group respectively corresponding to component vectors of ordinary strokes and at least one of transition strokes and starting-end strokes previously registered in the dictionary; and choosing a character from the dictionary data corresponding to said handwritten character based on one of the similarity measure being the greatest and the dissimilarity measure being the smallest.