Measurement of Critical Dimensions of Cold Roll Formed Sections Using Digital Image Processing

Abstract

A research investigation is presented which discusses the practicality of using several image processing and knowledge based techniques for the measurement and classification of cold rolled steel sections. Image analysis techniques can be applied to many different applications and assessing the quality and the accuracy of cold roll formed steel sections is no exception. The operations detailed within this paper are both traditional image processing methods and novel neural network based techniques which are combined together to give a bespoke alternative to the manual processing currently employed to test these sections. The results show the suitability of using image analysis and image processing to aid in the quality control of cold steel roll forming and initial tests have demonstrated great potential for this work.