Title : 
Pruning large lexicons using generalized word shape descriptors
         
        
            Author : 
S. Madhvanath;V. Krpasundar
         
        
            Author_Institution : 
Center of Excellence for Document Anal. & Recognition, State Univ. of New York, Buffalo, NY, USA
         
        
        
        
        
            Abstract : 
We present a technique for pruning of large lexicons for recognition of cursive script words. The technique involves extraction and representation of downward pen-strokes from the cursive word (off-line or online) to obtain a generalized descriptor which provides a coarse characterization of word shape. The descriptor is matched with ideal descriptors of lexicon entries organized as a trie. When used with a static lexicon of 21,000 words, the accuracy of reduction to 1000 words exceeds 95%.
         
        
            Keywords : 
"Shape","Handwriting recognition","USA Councils","Text analysis","Computer science","Computational efficiency","Concatenated codes","System performance","Data mining","Yttrium"
         
        
        
            Conference_Titel : 
Document Analysis and Recognition, 1997., Proceedings of the Fourth International Conference on
         
        
            Print_ISBN : 
0-8186-7898-4
         
        
        
            DOI : 
10.1109/ICDAR.1997.620561