Abstract
The research relevance is determined by the need to improve the processes of measurement of objects size in hard-to-reach conditions. In the modern industrial environment, where high measurement accuracy is critical for ensuring safety and maximizing the efficiency of production processes, the study of this topic is relevant in the context of rapid technological development and increased requirements for production quality. The study aims to evaluate the possibilities of using modern computer vision methods for measuring and reconstructing objects in difficult technical conditions, such as the enclosure of a water-water power reactor. The study employed 3D photogrammetry methods, including Depth from Stereo and Multi-View Stereo, as well as Structure from Motion methods. The study determined that modern computer vision methods, in particular machine learning methods, can be successfully used for measuring and reconstructing objects in hard-to-reach conditions. The study showed that the measurement accuracy can reach values close to 1 mm under ideal conditions and at a distance of 1.5 from the measuring device to the object. At the same time, the Multi-View Stereo method revealed greater uniformity of the spatial distribution of errors compared to the Depth from the Stereo method. In practice, in the conditions of real photos, the Multi-View Stereo method turned out to be more demanding to accurately determine the position of the camera. Due to its low demand for the exact coordinates of the cameras, the Depth from the Stereo method showed better results, showing less error in the measurements. The study highlighted the possibility of using the proposed method to distinguish fluctuations in the height of the surface of the object, which is important for further applications in the field of reactor maintenance and other areas of industry. The practical value of this research lies in the development and validation of methods for measuring and reconstructing objects in conditions where traditional methods become limited or impractical