TITLE:
Shape Retrieval Using Fourier Descriptors Applied to Industrial Process
AUTHORS:
Julio-Alejandro Romero-González, Rosamaría Romero-González, Marcela Herrera-Navarro, Diana-Margarita Córdova-Esparza, Hugo Jiménez-Hernández
KEYWORDS:
Convex Hull, Shape Retrieval, Features Detection, Fourier Transform, Vision Computing
JOURNAL NAME:
Journal of Computer and Communications,
Vol.8 No.3,
March
9,
2020
ABSTRACT: Nowadays, manufacturing processes are carried out at speeds that they themselves demand and subject to rigorous standards to maintain the quality of materials. An important step to define the quality of products in metalworking is the casting process, which principal focus is seeking control and monitoring of properties of materials. Nevertheless, it is not easy due to the high temperatures and gas produced in the vessel. Although some researchers have been attempting to solve these problems, it is difficult to carry out due to hard conditions. This article proposes the analysis of the surface of the liquid metal, that is, the slag on the surface, which is considered as connected spaces characterized by the topology of their discrete surface. These spaces are described through Fast Fourier Transform, associating changes of intensities to the frequency domain and obtaining main features of these frequencies, these features are used to define an enveloping shape that represents the liquid metal. Finally, the results obtained are presented, which, according to them shows that it is possible to characterize the slag, and by which it is possible to spatially locate the molten metal liquid in the refractory. Therefore, this research serves as the basis for the development of new algorithms for level detection and measurement, preventing overflows and damage to refractories.