Close-range precision photogrammetry for industrial purposes

Faig, Wolfgang

doi:10.1016/0031-8663(81)90014-4

Cited by 7 publications

(6 citation statements)

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“…Photogrammetry reconstructs the shape, color, and texture of the surface of objects from multiple pictures (Kraus, 2007) using a leastsquares algorithm (Evin et al, 2016;Rüther et al, 2012). Since the beginning of digital photogrammetry, the processing algorithms have continuously improved and the resolution has increased from several millimeters (Faig, 1981;Lichti et al, 2002) to a few micrometers (Gonzáles et al, 2015;Rüther et al, 2012). Nowadays it is an accurate, precise, and cheap technique (Munoz-Munoz et al, 2016).…”

Section: Photogrammetrymentioning

confidence: 99%

Three‐dimensional surface scanning methods in osteology: A topographical and geometric morphometric comparison

Waltenberger

Rebay‐Salisbury

Mitterœcker

2021

American J Phys Anthropol

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Objectives: Three-dimensional (3D) data collected by structured light scanners, photogrammetry, and computed tomography (CT) scans are increasingly combined in joint analyses, even though the scanning techniques and reconstruction software differ considerably. The aim of the present study was to compare the quality and accuracy of surface models and landmark data obtained from modern clinical CT scanning, 3D structured light scanner, photogrammetry, and MicroScribe digitizer. Material and methods: We tested 13 different photogrammetric software tools and compared surface models obtained by different methods for four articulated human pelves in a topographical analysis. We also measured a set of 219 landmarks and semilandmarks twice on every surface as well as directly on the dry bones with a MicroScribe digitizer. Results: Only one photogrammetric software package yielded surface models of the complete pelves that could be used for further analysis. Despite the complex pelvic anatomy, all three methods (CT scanning, 3D structured light scanning, photogrammetry) yielded similar surface representations with average deviations among the surface models between 100 and 200 μm. A geometric morphometric analysis of the measured landmarks showed that the different scanning methods yielded similar shape variables, but data acquisition via MicroScribe digitizer was most prone to error. Discussion: We demonstrated that three-dimensional models obtained by different methods can be combined in a single analysis. Photogrammetry proved to be a cheap, quick, and accurate method to generate 3D surface models at useful resolutions, but photogrammetry software packages differ enormously in quality.

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Section: Photogrammetrymentioning

confidence: 99%

Three‐dimensional surface scanning methods in osteology: A topographical and geometric morphometric comparison

Waltenberger

Rebay‐Salisbury

Mitterœcker

2021

American J Phys Anthropol

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“…Innovative technologies developed for experimental monitoring, on the basis of computer vision, can significantly improve the data recorded and, consequently, the quality of the structural analysis. Application of photogrammetry on structural monitoring can be found and are already spread . Initially, these studies are focused on evaluation of displacements in key sections.…”

Section: Background and Significancementioning

confidence: 99%

“…Application of photogrammetry on structural monitoring can be found and are already spread. [8,[21][22][23][24][25][26][27][28] Initially, these studies are focused on evaluation of displacements in key sections. Nowadays, strain fields and cracks pattern evolution are being computed on the basis of image correlation and image processing.…”

Section: Background and Significancementioning

confidence: 99%

Method for assessing beam column joints in RC structures using photogrammetric computer vision

Valença

Carmo

2017

Struct Control Health Monit

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Summary The response of beam column joints is fundamental for structural analysis of reinforcement concrete frames, particularly, when subjected to dynamic actions. Monitoring the key parameters of those joints is essential to perform a detailed analysis of the structure. These are often difficult to obtain, and only a few sections in critical regions are assessed. High‐end technologies can bring huge advantages in such measurements. Methods based on computer vision have been applied to monitoring reinforced concrete structures with excellent results, considering the accuracy achieved and the large quantity of information recorded. In this paper, a new method, named “Photo‐Node,” based on photogrammetry and image processing is presented. Photo‐Node is a noncontact method used to directly monitoring concrete surfaces, developed to measure the relevant physical parameters of reinforcement concrete beam column joints during experimental tests. The method addresses several postprocessing features to evaluate joint rotation, joint distortion, principal directions and stresses, cracks pattern, and load path. Additionally, the critical sections of the beam, that is, the region adjacent to the joint where the formation of the plastic hinge is expected, can be also evaluated. Photo‐Node provides a large amount of data, which can be processed to properly assess the joints behaviour. The degree of discretisation achieved enables to identify behaviours impossible to detect using traditional and less discretised approaches. The application of the method showed promising and accurate results, proving to be an efficient and a wide‐ranging tool to be used in experimental programs.

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“…Remote sensing image segmentation is the first step towards image analysis and application, and it's the important components of image understanding [1]. The so-called remote sensing image segmentation, based on the objectives and background of a priori knowledge, is marked target image and positioned background, and it is said to be physically meaningful regional connectivity collection of remote sensing for further lay the foundation for image classification [2][3][4]. Segmentation final result of the image is decomposed into a number of characteristics with the minimum components.…”

Section: Introductionmentioning

confidence: 99%

Research on Gridding Algorithm of Remote Sensing Image Segmentation by Region Growth

Zhu

Liu

Jiang

2014

AMM

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Region growth is an important method based on regional information, and its gridding process also is an important problem. This research is satisfied with the needs of the remote sensing massive data real time and fast transmission and processing, and developed of the theory and methods research of remote sensing processing based on grid operation. This paper starts with basic principle and mathematical models of region growth. Then some new serial region growth algorithms proposed in recent years are classified and analyzed, based on which their related gridding strategies are emphatically discussed. Then this research analyze and put forward the algorithm, which should be feasible when designing gridding parallel segmentation, and give an evaluation of the parallel regional segment algorithm. Finally, the problems and challenges of future research were pointed out.

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Close-range precision photogrammetry for industrial purposes

Cited by 7 publications

References 0 publications

Three‐dimensional surface scanning methods in osteology: A topographical and geometric morphometric comparison

Three‐dimensional surface scanning methods in osteology: A topographical and geometric morphometric comparison

Method for assessing beam column joints in RC structures using photogrammetric computer vision

Research on Gridding Algorithm of Remote Sensing Image Segmentation by Region Growth

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