A hidden Markov model approach for degraded and connected character recognition

This paper describes a method of representing a character according to shape profiles generated from vertical and horizontal scans through the lines of pixels constituting the character image. A pair of hidden Markov models is used to capture this shape profile information. Recognition is performed by combining knowledge from these two experts such that a test image may be "scored" against all character models, and a ranked recognition result can be output for further contextual processing. The success of this method in recognising degraded printed text is demonstrated here. Due to the powerful nature of the character representation, and particularly due to the method's suitability for the recognition of contextual characters, it is expected that the method can be applicable to hand-printed character recognition.<
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