Using lexical knowledge for the recognition of poorly written words

Handwriting recognition systems usually need the support of lexical knowledge in order to achieve acceptable results. Lexicons of practical applications are often very large which results in prohibitive run time and recognition performance. So there is a need to reduce large lexicons efficiently without loosing the correct entry. Often it is possible to recognize some isolated or resegmented characters of a word but not the whole word. These recognition results may be used as hints for an initial lexicon reduction. In order to use these hints techniques are needed which are able to handle character alternatives as well as touched and broken characters. The article discusses lexicon techniques in respect to their efficiency and robustness. A hybrid approach is proposed which reduces large lexicons efficiently and shows a robust behavior when broken and touched characters are observed