A word recognition algorithm for machine-printed word images of multiple fonts and varying qualities

An algorithm for recognition of machine-printed word images of multiple font types and varying qualities is presented. The information provided by both the entire shape of the word and its component letters was utilized in recognition. The algorithm uses the general shape of a word as the primary cue in recognition, with a few letters, which are highly identifiable when compared with the others, as the supplementary cues. In determining word shape, an ideal word pattern approach was applied to deal with the difficulty introduced by large variety of font types and image qualities. The size of given lexicon was reduced by recognizing the first and last characters. Experimental results with over two thousands test images, which are printed in a wide range of font styles and qualities, are presented to demonstrate the proposed approach.