DocumentCode
1120550
Title
INSPECTOR: A Computer Vision System that Learns to Inspect Parts
Author
Perkins, W.A.
Author_Institution
Computer Science Department, General Motors Research Laboratories, Warren, MI 49090; Lockheed Palo Alto Research Laboratory, Palo Alto, CA 94304.
Issue
6
fYear
1983
Firstpage
584
Lastpage
592
Abstract
A computer vision inspection system has been developed that learns the difference between good and bad parts by being shown several identified good and bad parts. The model, formed during the training session, contains identifying points which are used for locating parts and inspection tests which apply only to pertinent regions of the part. Using the model, the system can distinguish between good parts and bad parts with an arbitrary number of defects. It can also learn to classify parts if it is shown the different parts during the training session. Examples of INSPECTOR inspecting industrial parts are shown.
Keywords
Cameras; Computer vision; Gray-scale; Industrial training; Inspection; Laboratories; Pattern classification; Pattern recognition; TV; Testing; Automatic inspection; inspection; learning; part registration; pattern classification; visual learning;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/TPAMI.1983.4767447
Filename
4767447
Link To Document