Handwritten word recognition using statistics
T. Caesar, J.M. Gloger, Alfred Kaltenmeier, E. Mandler · 1994
In this paper, a system for the recognition of images of handwritten cursive words is presented. Since all the features of the described system are based on symbolic representation of the contour and skeleton, they can be computed very efficiently. The hidden Markov technique, already been used successfully for speech recognition, scores noteworthy results in handwriting recognition, too. In fact, the recognition results are better the larger the number of images contained in the training set. The system has been tested exhaustively with US city names as well as names of German cities. >