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Double adaptive intensity-threshold method for uneven Lidar data to extract road markings / Chengming Ye in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 9 (September 2021)
[article]
Titre : Double adaptive intensity-threshold method for uneven Lidar data to extract road markings Type de document : Article/Communication Auteurs : Chengming Ye, Auteur ; Hongfu Li, Auteur ; Ruilong Wei, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 639-648 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction du réseau routier
[Termes IGN] filtre adaptatif
[Termes IGN] lidar mobile
[Termes IGN] méthode robuste
[Termes IGN] semis de points
[Termes IGN] seuillage de points
[Termes IGN] signalisation routièreRésumé : (Auteur) Due to the large volume and high redundancy of point clouds, there are many dilemmas in road-marking extraction algorithms, especially from uneven lidar point clouds. To extract road markings efficiently, this study presents a novel method for handling the uneven density distribution of point clouds and the high reflection intensity of road markings. The method first segments the point-cloud data into blocks perpendicular to the vehicle trajectory. Then it applies the double adaptive intensity-threshold method to extract road markings from road surfaces. Finally, it performs an adaptive spatial density filter based on the density distribution of point-cloud data to remove false road-marking points. The average completeness, correctness, and F measure of road-marking extraction are 0.827, 0.887, and 0.854, respectively, indicating that the proposed method is efficient and robust. Numéro de notice : A2021-672 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.20-00099 Date de publication en ligne : 01/09/2021 En ligne : https://doi.org/10.14358/PERS.20-00099 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98834
in Photogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 9 (September 2021) . - pp 639-648[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2021091 SL Revue Centre de documentation Revues en salle Disponible A multi-layer perceptron neural network to mitigate the interference of time synchronization attacks in stationary GPS receivers / N. Orouji in GPS solutions, vol 25 n° 3 (July 2021)
[article]
Titre : A multi-layer perceptron neural network to mitigate the interference of time synchronization attacks in stationary GPS receivers Type de document : Article/Communication Auteurs : N. Orouji, Auteur ; M. R. Mosavi, Auteur Année de publication : 2021 Article en page(s) : Article 84 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] décalage d'horloge
[Termes IGN] horloge du récepteur
[Termes IGN] méthode robuste
[Termes IGN] Perceptron multicouche
[Termes IGN] précision des données
[Termes IGN] récepteur GPS
[Termes IGN] station GPS
[Termes IGN] synchronisationRésumé : (Auteur) Accurate timing is one of the key features of the Global Positioning System (GPS), which is employed in many critical infrastructures. Any imprecise time measurement in GPS-based structures, such as smart power grids, economic activities, and communication towers, can lead to disastrous results. The vulnerability of the stationary GPS receivers to the time synchronization attacks (TSAs) jeopardizes the GPS timing precision and trust level. In the past few years, studies suggested the adoption of estimators to follow the authentic trend of the clock offset information under attack conditions. However, the estimators would lose track of the authentic signal without proper knowledge of the signal characteristics. Therefore, a multi-layer perceptron neural network (MLP NN) is proposed to follow the trend of the data. The main difference between the proposed method and typical estimators is the reliance of the network on the training information consisting of signal features. The proposed MLP NN performance has been evaluated through two real-world datasets and two well-known types of TSA. The root mean square error results exhibit an improvement of at least six times compared to other conventional and state-of-art methods. Numéro de notice : A2021-331 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-021-01124-z Date de publication en ligne : 05/04/2021 En ligne : https://doi.org/10.1007/s10291-021-01124-z Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97501
in GPS solutions > vol 25 n° 3 (July 2021) . - Article 84[article]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)
[article]
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 pointsRésumé : (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
in ISPRS Journal of photogrammetry and remote sensing > vol 176 (June 2021) . - pp 83 - 108[article]Uncertainty management for robust probabilistic change detection from multi-temporal Geoeye-1 imagery / Mahmoud Salah in Applied geomatics, vol 13 n° 2 (June 2021)
[article]
Titre : Uncertainty management for robust probabilistic change detection from multi-temporal Geoeye-1 imagery Type de document : Article/Communication Auteurs : Mahmoud Salah, Auteur Année de publication : 2021 Article en page(s) : pp 261 - 275 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] appariement d'histogramme
[Termes IGN] champ aléatoire de Markov
[Termes IGN] classification dirigée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection de changement
[Termes IGN] Egypte
[Termes IGN] géoréférencement
[Termes IGN] image à très haute résolution
[Termes IGN] image Geoeye
[Termes IGN] image multitemporelle
[Termes IGN] incertitude des données
[Termes IGN] méthode robuste
[Termes IGN] modèle de Markov caché
[Termes IGN] occupation du sol
[Termes IGN] réseau neuronal artificiel
[Termes IGN] utilisation du solRésumé : (auteur) Robust approaches for image change detection (ICD) are essential for a range of large-scale applications. However, the uncertainties involved in such approaches have not been fully addressed. To investigate this problem, this paper proposes a new approach for change detection from multi-temporal very high resolution (VHR) satellite imagery based on uncertainty detection and management. First, two GeoEye-1 images of Giza urban area (Egypt), acquired in 2009 and 2019, have been geographically co-registered and their histograms have been matched. Second, a set of feature attributes have been generated from the co-registered images. Third, the support vector machine (SVM) algorithm has been adopted to classify the data into four classes: building, tree, road, and ground. In this regard, the co-registered images along with the generated attributes have been applied as input data for the SVM to calculate the probability of each pixel belonging to each class. After that, the probability images for both epochs have been compared to model the uncertainty of changes. The uncertainty places are then evaluated to estimate their likelihood of being change or no change. Finally, the obtained results have been compared with manually digitized change detection map. Compared with using the widely used post-classification comparison (PCC) approach, the results suggest that (1) the proposed method has improved the overall accuracy of change detection by 13%; (2) the class-accuracies have been improved by 35.63%; and (3) the achieved accuracies for the proposed approach are less variable. Whereas the standard deviation (SD) of the accuracies obtained for the proposed approach is 6.80, the SD of those obtained for the PCC approach is 35.50. Numéro de notice : A2021-412 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s12518-020-00346-z Date de publication en ligne : 28/10/2020 En ligne : https://doi.org/10.1007/s12518-020-00346-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97737
in Applied geomatics > vol 13 n° 2 (June 2021) . - pp 261 - 275[article]Increasing efficiency of the robust deformation analysis methods using genetic algorithm and generalised particle swarm optimisation / Mehmed Batilović in Survey review, Vol 53 n° 378 (May 2021)
[article]
Titre : Increasing efficiency of the robust deformation analysis methods using genetic algorithm and generalised particle swarm optimisation Type de document : Article/Communication Auteurs : Mehmed Batilović, Auteur ; Zoran Sušić, Auteur ; Željko Kanović, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 193 - 205 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Topographie
[Termes IGN] algorithme génétique
[Termes IGN] barrage
[Termes IGN] déformation de la croute terrestre
[Termes IGN] itération
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] méthode des moindres carrés
[Termes IGN] méthode robuste
[Termes IGN] optimisation par essaim de particules
[Termes IGN] Serbie
[Termes IGN] surveillance d'ouvrage
[Termes IGN] transformation IWSTRésumé : (auteur) The paper analyses the possibility of increasing efficiency of the Iterative Weighted Similarity Transformation (IWST) method, which is a prototype of classic robust methods, using global optimisation approach instead of classical one, available in the literature. For the purpose of solving the optimisation problem of the IWST method, in addition to the Iterative Reweighted Least Squares (IRLS) method, the Genetic algorithm (GA) and Generalised Particle Swarm Optimisation (GPSO) algorithm were applied, in order to overcome some flaws of IRLS method. Experimental research was performed based on the Monte Carlo simulation using the mean success rate (MSR) on the example of the geodetic control network for monitoring the Šelevrenac dam in the Republic of Serbia. By using the GA and GPSO algorithms, the overall efficiency of the IWST method has been increased by about 18% compared to the IRLS method. Also, it has been determined that the efficiency of the IRLS method significantly reduces with the increase in the number of displaced potential reference points (PRPs), while the GA and GPSO algorithms’ efficiency does not change significantly. The values of overall absolute true errors due to the increased number of displaced PRPs in the GA and GPSO algorithms did not change notably while with the IRLS method their values increased significantly. Numéro de notice : A2021-402 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2019.1706294 Date de publication en ligne : 04/01/2020 En ligne : https://doi.org/10.1080/00396265.2019.1706294 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97715
in Survey review > Vol 53 n° 378 (May 2021) . - pp 193 - 205[article]Recurrent neural network for rain estimation using commercial microwave links / Hai Victor Habi in IEEE Transactions on geoscience and remote sensing, vol 59 n° 5 (May 2021)PermalinkDetection of subpixel targets on hyperspectral remote sensing imagery based on background endmember extraction / Xiaorui Song in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)PermalinkAn improved rainfall-threshold approach for robust prediction and warning of flood and flash flood hazards / Geraldo Moura Ramos Filho in Natural Hazards, Vol 105 n° 3 (February 2021)PermalinkCorrentropy-based spatial-spectral robust sparsity-regularized hyperspectral unmixing / Xiaorun Li in IEEE Transactions on geoscience and remote sensing, vol 59 n° 2 (February 2021)PermalinkApprentissage profond et IA pour l’amélioration de la robustesse des techniques de localisation par vision artificielle / Achref Elouni (2021)PermalinkDescription et recherche d’image généralisables pour l’interconnexion et l’analyse multi-source / Dimitri Gominski (2021)PermalinkExtraction of street pole-like objects based on plane filtering from mobile LiDAR data / Jingming Tu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 1 (January 2021)PermalinkPermalinkPermalinkMapping uncertain geographical attributes: incorporating robustness into choropleth classification design / Wangshu Mu in International journal of geographical information science IJGIS, vol 34 n° 11 (November 2020)Permalink