In this work, we present a panoramic 3D stereo reconstruction system composed of two catadioptric cameras. Each one consists of a CCD camera and a parabolic convex mirror that allows the acquisition of catadioptric images. We describe the calibration approach and propose the improvement of existing deep feature matching methods with epipolar constraints. We show that the improved matching algorithm covers more of the scene than classic feature detectors, yielding broader and denser reconstructions for outdoor environments. Our system can also generate accurate measurements in the wild without large amounts of data used in deep learning-based systems. We demonstrate the system’s feasibility and effectiveness as a practical stereo sensor with real experiments in indoor and outdoor environments.

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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.

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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.