3D pipeline reconstruction and diameter measurement method based on target segmentation

Abstract

3D reconstruction technology utilizes 3D data to create models of physical objects. Cameras, laser scanners, and other sensors can be used to gather 3D data of objects, which can be processed using computer graphics technology for creating 3D models through 3D reconstruction technology. In engineering, high-precision 3D reconstruction models can substitute physical pipes for automatic measuring of pipe diameters. This paper proposes a target segmentation-based optimization method for single-frame reconstruction, which enables precise diameter measurement of pipes. Experimental results show that single-frame reconstruction, based on target segmentation technology, produces excellent results in the current application scenario. The proposed method is better adapted to complex construction conditions than the complex reconstruction methods. Complex backgrounds include excessive and uneven distributed light and interfering objects. Using target segmentation technology based on image processing, the MIVOS user-interactive video can produce and distribute the target object mask based on the user's interaction with the video frame. Complex background removal can improve the quality of reconstructed sample images. MIVOS is used to segment the pipe area in the image and remove most of the background noise. Consequently, the process lessens the interference of background noise in the reconstruction results. The proposed method exhibits significant progress in measuring both the inner and outer diameters of pipes when compared to both multi-frame and single-frame reconstruction methods. Their measurements have an average error of no more than 1 mm. The proposed method provides technical guidance for measuring the inner and outer diameters of pipes under complex conditions.