Title :
Automatic classification of solder joint images
Author :
Poechmueller, W. ; Glesner, Manfred ; Listl, L.
Author_Institution :
Inst. for Microelectron. Syst., Darmstadt Univ. of Technol.
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;
Conference_Titel :
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-0164-1
DOI :
10.1109/IJCNN.1991.155523
