A SOFM improves a real time quality assurance machine vision system

We present a high speed machine vision system for the inspection and quality assurance of canned tuna, which is currently working at a rate over 1000 cans per minute. The system inspects the geometry of the can and its contents at a resolution of 4 pixels/mm. It is the evolution of a first prototype through the introduction of a Kohonen network, which maps texture features into a two dimensional grid where the user defines quality neighbourhoods. The inspection time, increased from 35 ms to 38 ms per can, allows the introduction of the system in the same production lines without affecting total performance, but with higher accuracy and user satisfaction.