DocumentCode :
2059551
Title :
Words recognition using associative memory
Author :
Navoni, Loris ; Canegallo, Roberto ; Chinosi, Mauro ; Gozzini, Giovanni ; Kramer, Alan ; Rolandi, Pier Luigi
Author_Institution :
Central R&D, SGS-Thomson Microelectron., Agrate Brianza, Italy
Volume :
1
fYear :
1997
fDate :
18-20 Aug 1997
Firstpage :
97
Abstract :
Introduces the application of an analog associative memory chip to word recognition, which is a fundamental topic of the text recognition process. The word recognition method takes advantage of a statistical evaluation of the behavior of the optical character recognition system preceding it. That statistical information leads to the creation of a coding that is used to store a lexicon of the most used words in the chip. An input pattern is matched against the full database of the associative memory, and a set of closest patterns is returned. The precision reached by this operation ranges from 93% to 99%. These encouraging results demonstrate the general aptitude of the chip to solve classes of problems that need to use an associative memory
Keywords :
content-addressable storage; encoding; neural chips; optical character recognition; statistical analysis; analog associative memory chip; closest patterns; coding; database; input pattern matching; lexicon; most used words; optical character recognition system; precision; statistical evaluation; text recognition process; word recognition; Active appearance model; Associative memory; Character recognition; Concurrent computing; Databases; Microelectronics; Optical character recognition software; Optical noise; Pattern matching; Text recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 1997., Proceedings of the Fourth International Conference on
Conference_Location :
Ulm
Print_ISBN :
0-8186-7898-4
Type :
conf
DOI :
10.1109/ICDAR.1997.619821
Filename :
619821
Link To Document :
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