2026-06-05T16:06:58Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/180452026-02-03T11:51:28Zcom_10630_2254col_10630_37959
A comparative study of image processing thresholding algorithms on residual oxide scale detection in stainless steel production lines
Cañero-Nieto, Juan Miguel
Solano-Martos, José Francisco
Martín-Fernández, Francisco de Sales
The present work is intended for residual oxide scale detection and classification through the application of image processing
techniques. This is a defect that can remain in the surface of stainless steel coils after an incomplete pickling process in a
production line. From a previous detailed study over reflectance of residual oxide defect, we present a comparative study of
algorithms for image segmentation based on thresholding methods. In particular, two computational models based on multi-linear
regression and neural networks will be proposed. A system based on conventional area camera with a special lighting was
installed and fully integrated in an annealing and pickling line for model testing purposes. Finally, model approaches will be
compared and evaluated their performance..
2019-07-15T07:12:33Z
2019-07-15T07:12:33Z
2019
2019-07-15
conference output
https://hdl.handle.net/10630/18045
eng
8th Manufacturing Engineering Society International Conference
Madrid, España
19/06/2019
http://creativecommons.org/licenses/by-nc-nd/4.0/
open access
Attribution-NonCommercial-NoDerivatives 4.0 Internacional