Quality control of production has always been a necessity
in stainless Steel mills. The users of stainless
Steel set ever-increasing requirements on product
quality. Many material properties can still only be
measured in laboratory but more and more measurements
are now made on-line during the production.
Especially surface defects have to be detected on-line
with a surface inspection system because of their random
appearance.
In this paper, we describe the development of a rapidly reconfigurable system in which the users’ tacit knowledge and requirements are
elicited via a process of Interactive Evolution, finding the image processing parameters to achieve the required goals without any need for
specialised knowledge of the machine vision system. We show that the resulting segmentation can be quickly and easily evolved from
scratch, and achieves detection rates comparable to those of a hand-tuned system on a hot-rolled Steel defect recognition problem.
