DocumentCode :
1851061
Title :
Generating feature detectors with discovery algorithms
Author :
ZMUDA, MICHAEL A. ; Tamburino, L.A. ; Rizki, Mateen M.
Author_Institution :
Wright Res. & Dev. Center, Wright-Patterson AFB, OH, USA
fYear :
1993
fDate :
24-28 May 1993
Firstpage :
825
Abstract :
Traditional techniques for extracting features from images are highly structured processes which require human experts to convert their intuition and experience into algorithms that solve problems such as image classification, target recognition, or assembly line inspection. Intelligent systems such as rule-based expert systems have been used to assist in the development process; however, these approaches still require significant human intervention to achieve acceptable results. This paper describes a system called MORPH which synthesizes complex feature extraction routines using only classification information provided by the image analyst. This system generates a multiplicity of very accurate solutions for several classification tasks
Keywords :
feature extraction; feedforward neural nets; image recognition; learning (artificial intelligence); mathematical morphology; optical character recognition; MORPH; artificial intelligence; assembly line inspection; binary images; complex feature extraction; computer vision; discovery algorithms; feature detectors; handwritten characters; image classification; learning; morphonets; rule-based expert systems; structured processes; target; target recognition; Assembly; Computer vision; Detectors; Feature extraction; Humans; Image classification; Image converters; Inspection; Intelligent systems; Target recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Aerospace and Electronics Conference, 1993. NAECON 1993., Proceedings of the IEEE 1993 National
Conference_Location :
Dayton, OH
Print_ISBN :
0-7803-1295-3
Type :
conf
DOI :
10.1109/NAECON.1993.290836
Filename :
290836
Link To Document :
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