A flexible and robust matching scheme for character recognition to cope with variations in spatial interrelation among structural features

This paper presents a structural approach for classification of multi-font machine-printed or handwritten character samples. The issue of how to cope with variations that are found in the relative location of individual strokes of a character in the presence of variations in shape, size, orientation and spacing of the involved strokes is described in detail. The approach yields results closer to human aesthetic sense.