Title :
Pattern recognition for infrared profiles of steel strips based on fuzzy knowledge
Author :
Usamentiaga, Rubén ; García, Daniel F. ; González, Diego ; Molleda, Julio
Author_Institution :
Dept. of Comput. Sci., Oviedo Univ., Asturias
Abstract :
The recent demand for extremely thin high-quality steel products makes temperature control an increasingly determining factor in the final quality. In fact, uneven temperature during thin steel production makes the steel fracture rate increase sharply. This work proposes a method to recognize a common uneven temperature pattern known as the hot-shoulders pattern. The proposed recognition method is carried out in three steps. Firstly, the infrared image obtained from the steel strip is processed in order to calculate the infrared profiles. Next, each of these profiles is processed in order to determine its shape. Finally, a fuzzy approach is used to determine the membership degree of each profile to the hot-shoulders temperature pattern
Keywords :
feature extraction; fuzzy set theory; image recognition; image segmentation; infrared imaging; steel industry; temperature; feature extraction; fuzzy knowledge; hot-shoulders temperature pattern; image processing; image segmentation; infrared image; infrared profiles; pattern recognition; steel production; steel strips; temperature control; Cooling; Elasticity; Image segmentation; Infrared imaging; Manufacturing; Pattern recognition; Shape; Steel; Strips; Temperature; fuzzy knowledge; image processing; pattern recognition;
Conference_Titel :
Computational Intelligence for Measurement Systems and Applications, Proceedings of 2006 IEEE International Conference on
Conference_Location :
La Coruna
Print_ISBN :
1-4244-0244-1
Electronic_ISBN :
1-4244-0245-X
DOI :
10.1109/CIMSA.2006.250759
