The Abstract of the Project:

              The project describes a system for recognizing unconstrained Turkish handwritten text. Turkish has agglutinative morphology and theoretically an infinite number of words that can be generated by adding more suffixes to the word. This makes lexicon-based recognition approaches, where the most likely word is selected among all the alternatives in a lexicon, unsuitable for Turkish. We describe our approach to the problem using a Turkish prefix recognizer. First results of the system demonstrates the promise of this approach, with top-10 word recognition rate of about 40% for a small test data of mixed handprint and cursive writing. The lexicon-based approach with a 17,000 word-lexicon (with test words added) achieves 56% top-10 word recognition rate. Following that, an online handwritten text recognition system for Turkish has been developed using a Tablet PC as an interface. In recent years, although there has been great developments in the Tablet PC technology, still there are no applications for recognition in Turkish language. In this work, we have developed a prototype system using Hidden Markov Models which recognizes handwritten words from a small vocabulary list. This system has achieved a recognition rate over %90 percent... (for detailed information)