Video Stitching method for a Surveillance System Deployed at a Fully Mechanized Mining Face

Abstract

Using video stitching technology, video images with overlapping parts can be stitched into a complete image, with characteristics such as intuitiveness, visualization, and measurable analysis. This technology could be applied in the operation of coal mines for a remote monitoring and control of coal production. However, when the technology is used in coal mines, there are several challenges such as non-uniform illumination, missing scenes, and oblique panorama. In this paper, methods were purposed to solve the above problems: (1) To overcome the non-uniform illumination on a mining face, we applied the wide dynamic range technology to the images from a single camera and histogram matching algorithm on multiple images to reduce the color difference between the images; (2) To overcome the missing scene problem due to the narrow field of view (FOV) of a single camera, the SURF matching and template recognition methods are combined to achieve a stable stitching; (3) To overcome the oblique panorama issue, we applied the vertical correction technology exploiting the posture information of the camera, and then the adjacent images are concatenated. The results of practical experiments show that the proposed methods are suitable for solving the above problems in a fully mechanized mining face. The research provides a new approach for displaying extended scenes of stope faces in the intelligent collieries.