DocumentCode
2734770
Title
Automatic classification of solder joint images
Author
Poechmueller, W. ; Glesner, Manfred ; Listl, L.
Author_Institution
Inst. for Microelectron. Syst., Darmstadt Univ. of Technol.
fYear
1991
fDate
8-14 Jul 1991
Abstract
Summary form only given, as follows. Elaborate techniques have been developed to obtain data from specimens in industrial quality control tasks. However, a problem in the field of visual inspection is how to process complex data in real time. An approach to classification of solder joint images by means of a neuronlike binary associative memory has been developed. All the algorithms and architectures considered could easily be implemented with digital VLSI technology to realize an extremely fast classifier
Keywords
automatic optical inspection; computerised pattern recognition; content-addressable storage; neural nets; soldering; classification; classifier; digital VLSI; industrial quality control; neuronlike binary associative memory; real time; solder joint images; visual inspection; Electrical equipment industry; Image analysis; Industrial control; Inspection; Logistics; Microelectronics; Neural networks; Production systems; Quality control; Soldering;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location
Seattle, WA
Print_ISBN
0-7803-0164-1
Type
conf
DOI
10.1109/IJCNN.1991.155523
Filename
155523
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