Defect identification algorithm for sequential and parallel computers

This paper introduces sequential and parallel versions of an algorithm that compares original (reference) and processed images in the time and frequency domains. This comparison combined with histogram data from both domains can identify differences in the images. Extracted data is also compared to database data in an attempt to pinpoint specific changes, such as rotations, translations, defects, etc. The first application considered here is recognition of an object which has been translated and/or rotated. For illustration purposes, an original image of a computer-simulated centered needle is compared to a second image of the hypodermic needle in a different position.