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Robust detection of non-overlapping ellipses from points with applications to circular target extraction in images and cylinder detection in point clouds / Reza Maalek in ISPRS Journal of photogrammetry and remote sensing, vol 176 (June 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 176 (June 2021) . - pp 83 - 108 Titre : Robust detection of non-overlapping ellipses from points with applications to circular target extraction in images and cylinder detection in point clouds Type de document : Article/Communication Auteurs : Reza Maalek, Auteur ; Derek Litchi, Auteur Année de publication : 2021 Article en page(s) : pp 83 - 108 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] chevauchement [Termes IGN] cylindre [Termes IGN] détection de cible [Termes IGN] données localisées 3D [Termes IGN] ellipticité (géométrie) [Termes IGN] extraction de traits caractéristiques [Termes IGN] image 2D [Termes IGN] méthode de Monte-Carlo [Termes IGN] méthode robuste [Termes IGN] Ransac (algorithme) [Termes IGN] semis de points Résumé : (auteur) Detection of non-overlapping ellipses from 2-dimensional (2D) edge points is an essential step towards solving typical photogrammetry problems pertaining to feature detection, calibration, and registration of optical instruments. For instance, circular and spherical black and white calibration and registration targets are represented as ellipses in images. Furthermore, the intersection of a cut plane with cylindrical point clouds generates 2D points following elliptic patterns. To this end, this study proposes a collection of new methods for the automatic and robust detection of non-overlapping ellipses from 2D points. These methods will first be applied to detect circular and spherical targets in images and, second, to detect cylinders in 3D point clouds. The method utilizes the Euclidian ellipticity and a new systematic and generalizable threshold to decide if a set of connected points follow an elliptic pattern. When connected points include outliers, the newly proposed robust Monte Carlo-based ellipse fitting method will be deployed. This method includes three new developments: (i) selecting initial subsamples using a bucketing strategy based on the polar angle of the points; (ii) detecting inlier points by reducing the robust ellipse fitting to a robust circle fitting problem; and (iii) choosing the best inlier set amongst all subsamples using adaptive, systematic, and generalizable selection criteria. A new process is presented to extract cylinders from a point cloud by detecting non-overlapping ellipses from the points projected onto an intersecting cut plane. The proposed methods were compared to established state-of-the-art methods, using simulated and real-world datasets, through the design of four sets of original experiments. The experiments include (i) comparisons of robust ellipse fitting; (ii) sensitivity analysis of the ellipse validation criteria; (iii) comparison of non-overlapping ellipse detection; and (iv) detection of pipes from terrestrial laser scanner point clouds. It was found that the proposed robust ellipse detection was superior to four reliable robust methods, including the popular least median of squares, in both simulated and real-world datasets. The proposed process for detecting non-overlapping ellipses achieved F-measure of 99.3% on real images, compared to 42.4%, 65.6%, and 59.2%, obtained using the methods of Fornaciari, Patraucean, and Panagiotakis, respectively. The proposed cylinder extraction method identified all detectable mechanical pipes in two real-world point clouds collected in laboratory and industrial construction site conditions. The results of this investigation show promise for the application of the proposed methods for automatic extraction of circular targets from images and pipes from point clouds. Numéro de notice : A2021-413 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.isprsjprs.2021.04.010 Date de publication en ligne : 28/04/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.04.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97744 [article]

Multi-dimensional and multi-temporal motion estimation of a beam surface during dynamic testing using low-frame rate digital cameras / I. Detchev in Applied geomatics, vol 9 n° 3 (September 2017)  

Public [article]  inApplied geomatics > vol 9 n° 3 (September 2017) . - pp 127 - 141 Titre : Multi-dimensional and multi-temporal motion estimation of a beam surface during dynamic testing using low-frame rate digital cameras Type de document : Article/Communication Auteurs : I. Detchev, Auteur ; Derek Litchi, Auteur ; Ayman Habib, Auteur ; Mamdouh El-Badry, Auteur Année de publication : 2017 Article en page(s) : pp 127 - 141 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] ajustement de paramètres [Termes IGN] caméra numérique [Termes IGN] déviation de la verticale [Termes IGN] méthode des moindres carrés [Termes IGN] photogrammétrie métrologique Résumé : (Auteur) The combination of digital close-range photogrammetric systems and image processing techniques has been employed in structural health monitoring applications for more than 10 years. The use of off-the-shelf entry level digital single-lens reflex cameras has lately become a suitable choice even for applications requiring sub-millimetre- level precision especially when the involved devices need to be inexpensive. The drawback of such low-cost cameras is in the trade-off between spatial resolution, frame rate, and burst rate—at the highest available spatial resolution, a high frame rate is either not possible or it has a low burst rate. This may be problematic when monitoring a structural component during a dynamic/fatigue test. In order to estimate specimen motion in such a situation, this paper proposes an innovative sinusoidal fitting based on a least squares adjustment. This method simultaneously processes multiple bursts of data in order to synthetically increase the sampling frequency of the system. The input data for the adjustment comes from a full surface modelling procedure based on a newly proposed generalized 3D polynomial. The experimental results include a beam deformation test performed in a structures laboratory. The new sinusoidal fitting method effectively increased the system temporal resolution three-fold, which improved the precision of the derived parameters with up to two orders of magnitude. The root mean square error of the residuals were as good as 26 μm, and the one of the estimated amplitudes from the photogrammetric system versus a set of laser transducers used as control was as small as 43 μm. Numéro de notice : A2017-595 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s12518-017-0184-0 Date de publication en ligne : 10/04/2017 En ligne : https://doi.org/10.1007/s12518-017-0184-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86803 [article]