Feature Descriptors Applied to Slag Characterization on Casting Process
Julio-Alejandro Romero-González1, Ana M. Herrera-Navarro2, Hugo Jiménez-Hernández3
1Julio-Alejandro Romero-González*, Universidad Autónoma de Querétaro, Querétaro, México.
2Ana M. Herrera-Navarro, Universidad Autónoma de Querétaro, Querétaro, México.
3Hugo Jiménez-Hernández, Project leader, Centro de Ingeniería y Desarrollo Industrial, Querétaro, México.
Manuscript received on January 05, 2020. | Revised Manuscript received on January 09, 2020. | Manuscript published on January 15, 2020. | PP: 11-15 | Volume-6, Issue-4, January 2020. | Retrieval Number: D1193026420/2020©BEIESP | DOI: 10.35940/ijisme.D1193.016420
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Vision systems are increasingly entering the field of metallurgy, carrying out operations where a human operator is not possible due to the process conditions. The purpose of these systems is the monitoring and control of the process to improve the quality and manufacturing of the products. Nevertheless, the amount of slag, the presence of gases and high temperatures are the main problems that make this task difficult. In this proposal the characterization of the slag is treated, through the analysis of the light changes with the functions of Fourier and Gabor, which allow to identify or locate the location of the slag in the material, so that, in future works the slag It can be segmented, measured or used to detect the level of the metal in the refractory. In addition, results obtained when evaluating sensitivity and precision curves are presented, with which the information recovered by the algorithms is evaluated.
Keywords: Features detection, Fourier Transform, Gabor Filter, Image Processing, Vision Computing.