DocumentCode
285302
Title
Massively parallel neural network recognition
Author
Wilson, C.L.
Author_Institution
Nat. Inst. of Stand. & Technol., Gaithersburg, MD, USA
Volume
3
fYear
1992
fDate
7-11 Jun 1992
Firstpage
227
Abstract
The author discusses two complete neural network recognition systems, a character recognition system and a fingerprint classification system. The requirements for a total vision system must include the capability for image isolation, segmentation, and feature extraction, as well as recognition. The systems were developed on a massively parallel array processor which was used to illustrate the importance of these higher-level functions. Both of these systems demonstrated state-of-the-art accuracy but both need improvements to be commercially viable. The issue in the character recognition system is to provide this accuracy at a speed compatible with commercial requirements of 1 page/s. This will require more sophisticated higher-level image parsing functions without loss of accuracy. The issue in fingerprint classification is the requirement for 99.7% accuracy at current speeds
Keywords
character recognition; computer vision; image recognition; parallel processing; character recognition system; feature extraction; fingerprint classification system; higher-level image parsing functions; image isolation; massively parallel array processor; massively parallel neural network recognition; segmentation; total vision system; Character recognition; Concurrent computing; Feature extraction; Fingerprint recognition; Image converters; Image recognition; Image segmentation; Machine vision; NIST; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location
Baltimore, MD
Print_ISBN
0-7803-0559-0
Type
conf
DOI
10.1109/IJCNN.1992.227166
Filename
227166
Link To Document