Digital cameras are limited by a narrow field of view and a large photosensitive unit, resulting in images with a small frame size and low resolution. This reduces the acquisition range and measurement accuracy of stereo vision in close-range photogrammetry, making it difficult to meet the requirements for precise close-range photogrammetry in high-precision industrial engineering fields, and limiting the significant development of digital close-range photogrammetry. For this reason, based on the characteristics of ground close-range photogrammetry, this paper proposes a large-format image acquisition method for rotating cameras. By designing a simple and structurally relaxed rotating camera, a rigorous seamless stitching model for large-format images is constructed, forming a large-format equivalent central projection image acquisition mechanism that meets the requirements of precise close-range photogrammetry. Finally, the effectiveness of the proposed method is verified through experiments. The results show that the proposed method effectively increases the coverage of a single camera station. The large-format image obtained through three degrees of rotation increases the image size from 916 × 687 pixels in a single image to 4977 × 671 pixels in a large-format image. This method solves the problem of the small view field of digital cameras, complementing the theory of precision close-range photogrammetry and providing necessary theoretical support for technological development in the field of precision industrial engineering.
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http://dx.doi.org/10.1038/s41598-024-80295-4 | DOI Listing |
Sensors (Basel)
November 2024
School of Rural & Surveying Engineering, Aristotle University of Thessaloniki, University Box 439, GR-54 124 Thessaloniki, Greece.
The evaluation of smartphone camera technology for close-range photogrammetry includes assessing captured photos for 3D measurement. In this work, experiments are conducted on many smartphones to study distortion levels and accuracy performance in close-range photogrammetry applications. Analytical methods and specialized digital tools are employed to evaluate the results.
View Article and Find Full Text PDFSci Rep
November 2024
School of Geodesy and Geomatics, Jiangsu Normal University, Xuzhou, China.
Sensors (Basel)
July 2024
School of Rural & Surveying Engineering, Aristotle University of Thessaloniki, University Box 439, GR-54 124 Thessaloniki, Greece.
The comparative evaluation of the performance of a mobile device camera and an affordable full-frame mirrorless camera in close-range photogrammetry applications involves assessing the capabilities of these two types of cameras in capturing images for 3D measurement purposes. In this study, experiments are conducted to compare the distortion levels, the accuracy performance, and the image quality of a mobile device camera against a full-frame mirrorless camera when used in close-range photogrammetry applications in various settings. Analytical methodologies and specialized digital tools are used to evaluate the results.
View Article and Find Full Text PDFSensors (Basel)
July 2024
College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China.
To determine both the size of a satellite antenna and the thermal deformation of its surface shape, a novel high-accuracy close-range photogrammetric technique is used in this study. The method is also applied to assess the performance of the antenna in orbit. The measurement principle and solution method of close-range photogrammetry were thoroughly investigated, and a detailed measurement test scheme was developed.
View Article and Find Full Text PDFDepending on the size, shape, and gray intensity distribution of charge-coupled device (CCD) imaging retro-reflective targets (RRTs) in close-range photogrammetry, and based on conventional grayscale centroiding, this paper proposes grayscale threshold variable-index weighted centroiding (GTVIWC). The centroid location accuracy of CCD imaging RRTs was analyzed and compared using simulated and measured target images, respectively. The experimental results demonstrated that the centroid location accuracy of the algorithms used in the experiment was relatively high, reaching the subpixel level.
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