Title :
Automatic visual inspection based upon a variant of the n-tuple technique
Author :
Ouslim, M. ; Curtis, K.M.
Author_Institution :
Parallel Process. Specialist Group, Nottingham Univ., UK
fDate :
10/1/1996 12:00:00 AM
Abstract :
The authors present a new rapid image analysis technique ideally suited for both production line and generalised flaw detection. It is a variant of the n-tuple technique and uses nine selected attributes based on five pixels arranged in a cross shape. The technique requires a flaw free image as well as the image under test. The estimation of the flaw size and its shape is given by recording frequencies of occurrence of the nine attributes by scanning both the corrupted image and the flaw free image. The application of this technique to the inspection of simple flaws in printed circuit boards, proved to be successful in detecting defects as small as one pixel in an image of 512×512 pixels with the object occupying as little as 3×3. Its application to defect identification within a multigrey level image is also shown to be successful. Its ease of implementation makes this technique a very good candidate for implementation as an embedded part within a front end processor for a real time automatic inspection system. It offers an improvement in speed of analysis, simplicity of operation, versatility in the type of problem it can tackle and cost-effectiveness over recently published methods
Keywords :
automatic optical inspection; electronic engineering computing; flaw detection; image processing; printed circuit testing; satellite computers; 262144 pixel; 512 pixel; analysis speed; automatic visual inspection; corrupted image; defect identification; flaw free image; flaw shape estimation; flaw size estimation; front end processor; generalised flaw detection; image analysis technique; image scanning; image under test; multigrey level image; n-tuple technique; occurrence frequency; pixel; printed circuit boards; production line; real time automatic inspection system;
Journal_Title :
Vision, Image and Signal Processing, IEE Proceedings -
DOI :
10.1049/ip-vis:19960616