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