On the basis of a well accepted, HMM-based cursive script recognition system, an algorithm which automatically adapts the length of the models representing the letter writing variants is proposed. An average improvement in recognition performance of about 2.72 percent could be obtained. Two initialization methods for the algorithm have been tested, which show quite different behaviors; both prove to be useful in different application areas. To get a deeper insight into the functioning of the algorithm a method for the visualization of letter HMMs is developed. It shows the plausibility of most results, but also the limitations of the proposed method. However, these are mostly due to given restrictions of the training and recognition method of the underlying system.
Model length adaptation of an HMM based cursive word recognition system
01.01.2003
2061237 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Model Length Adaptation of an HMM-Based Cursive Word Recognition System
British Library Conference Proceedings | 2003
|Writer Adaptation Techniques in Off-Line Cursive Word Recognition
British Library Conference Proceedings | 2002
|An on-line cursive word recognition system
IEEE | 1994
|An On-Line Cursive Word Recognition System
British Library Conference Proceedings | 1994
|