Authors: Mohammed H. Hassan; Safaa L. Diab
Addresses: Faculty of Engineering, Helwan University, 1 Sherief St. 11792, Helwan, Cairo, Egypt. ' Faculty of Science, Helwan University, Ain Helwan, 11792, Helwan, Cairo, Egypt
Abstract: Image analysis techniques are being increasingly used to automate industrial inspection. The manual activity of inspection could be subjective and highly dependent on the experience of human personnel. In this work, the authors introduce a novel visual inspection approach that can be used online to test simultaneously multiple quality characteristics. The approach utilises image processing tools to deal with the product image; and extract features of its geometrical characteristics. Based on tolerance bands of each characteristic, an index is experimentally developed to reflect the deviation of a quality characteristic dimension from its nominal value; and one can decide whether a characteristic complies with the pre-specified tolerance. The index is proved to have a linear association with the deviation from the nominal sizes. The research is extended to test shifts in a quality characteristic position.
Keywords: visual inspection; image processing; thresholding; tolerance; regression; ANOVA; quality characteristics; online testing; product images; feature extraction.
International Journal of Quality and Innovation, 2011 Vol.1 No.4, pp.326 - 337
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 03 Nov 2011 *