The recognition of a printed word is traditionally limited by its segmentation into individual characters due to the noise introduced by facsimile transmission, photocopying, handling or ageing. In this paper, a character recogniser is described which does not require a prior segmentation of the word, and is thus suited to the recognition of noisy text images. A novel method is described whereby hidden Markov models are used to recognise a horizontal "profile" of a word generated from an analysis of each vertical line of pixels in its image.
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A.J. Elms (2002) studied this question.