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An improved segmentation approach for planar surfaces from undestructured 3D point clouds / T.M. Awwad in Photogrammetric record, vol 25 n° 129 (March - May 2010)
[article]
Titre : An improved segmentation approach for planar surfaces from undestructured 3D point clouds Type de document : Article/Communication Auteurs : T.M. Awwad, Auteur ; Q. Zhu, Auteur ; Z. Du, Auteur ; Y. Zhang, Auteur Année de publication : 2010 Article en page(s) : pp 5 - 23 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] Ransac (algorithme)
[Termes IGN] segmentation d'image
[Termes IGN] semis de points
[Termes IGN] surface planeRésumé : (Auteur) The extraction of object features from massive unstructured point clouds with different local densities, especially in the presence of random noisy points, is not a trivial task even if that feature is a planar surface. Segmentation is the most important step in the feature extraction process. In practice, most segmentation approaches use geometrical information to segment the 3D point cloud. The features generally include the position of each point (X, Y and Z), locally estimated surface normals and residuals of best fitting surfaces; however, these features could be affected by noisy points and in consequence directly affect the segmentation results. Therefore, massive unstructured and noisy point clouds also lead to bad segmentation (over-segmentation, under-segmentation or no segmentation). While the RANSAC (random sample consensus) algorithm is effective in the presence of noise and outliers, it has two significant disadvantages, namely, its efficiency and the fact that the plane detected by RANSAC may not necessarily belong to the same object surface; that is, spurious surfaces may appear, especially in the case of parallel-gradual planar surfaces such as stairs. The innovative idea proposed in this paper is a modification for the RANSAC algorithm called Seq-NV-RANSAC. This algorithm checks the normal vector (NV) between the existing point clouds and the hypothesised RANSAC plane, which is created by three random points, under an intuitive threshold value. After extracting the first plane, this process is repeated sequentially (Seq) and automatically, until no planar surfaces can be extracted from the remaining points under the existing threshold value. This prevents the extraction of spurious surfaces, brings an improvement in quality to the computed attributes and increases the degree of automation of surface extraction. Thus the best fit is achieved for the real existing surfaces. Copyright RS&PS + Blackwell Publishing Numéro de notice : A2010-060 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/j.1477-9730.2009.00564.x Date de publication en ligne : 11/03/2010 En ligne : https://doi.org/10.1111/j.1477-9730.2009.00564.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30256
in Photogrammetric record > vol 25 n° 129 (March - May 2010) . - pp 5 - 23[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 106-2010011 RAB Revue Centre de documentation En réserve L003 Disponible Land-cover change detection using one-class support vector machine / P. Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 3 (March 2010)
[article]
Titre : Land-cover change detection using one-class support vector machine Type de document : Article/Communication Auteurs : P. Li, Auteur ; H. Xu, Auteur Année de publication : 2010 Article en page(s) : pp 255 - 263 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection de changement
[Termes IGN] données multitemporelles
[Termes IGN] Kappa de Cohen
[Termes IGN] occupation du sol
[Termes IGN] traitement d'imageRésumé : (Auteur) Change detection using remote sensing has considerable potential for monitoring land-cover change. Commonly, one specific class of change is of interest in many applications. In this paper, a recently developed one-class classifier, the One-Class Support Vector Machine (OCSVM), is proposed for the change detection of one specific class by multitemporal classification. The classifier only requires samples from the change class of interest as the training data. The performance of the proposed method was evaluated in two applications by comparing with conventional post-classification comparison methods. The results demonstrated the proposed method achieved both higher overall accuracy and higher kappa coefficient than the conventional methods, and demonstrated good potential for further application. The study also indicated that with the ocsvm, the analysis can focus only on the specific class of interest and does not need to treat other classes, thus providing highly accurate change detection. The OCSVM-based change detection method, as a general and easily implemented method, can be used for applications where only the change of one specific class is of interest. Copyright ASPRS Numéro de notice : A2010-087 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.76.3.255 En ligne : https://doi.org/10.14358/PERS.76.3.255 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30283
in Photogrammetric Engineering & Remote Sensing, PERS > vol 76 n° 3 (March 2010) . - pp 255 - 263[article]Object-based image analysis: definiens' egognition server software / E. Van Rees in Geoinformatics, vol 13 n° 2 (01/03/2010)
[article]
Titre : Object-based image analysis: definiens' egognition server software Type de document : Article/Communication Auteurs : E. Van Rees, Auteur Année de publication : 2010 Article en page(s) : pp 22 - 24 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse d'image numérique
[Termes IGN] eCognition
[Termes IGN] médecine humaine
[Termes IGN] sciences de la Terre et de l'universRésumé : (Auteur) Definiens is a company active in image analysis. Not restricted to the geospatial market only, the company offers solutions for all kinds of imagery used in life sciences and the medical world. GeoInformatics interviewed Ralph D. Humberg, Vice President of Definiens Earth Sciences division. Mr. Humberg joined Definiens in 2002 and is responsible for Definiens' global Earth Sciences business. He talks about eCognition, Definiens' image analysis software used for Earth Sciences. The latest release of the software is eCognition version 8, issued in November last year, along with a new internet portal. Copyright GEOinformatics Numéro de notice : A2010-075 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30271
in Geoinformatics > vol 13 n° 2 (01/03/2010) . - pp 22 - 24[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 262-2010021 RAB Revue Centre de documentation En réserve L003 Disponible Segmentation and reconstruction of polyhedral building roofs from aerial lidar points clouds / A. Sampath in IEEE Transactions on geoscience and remote sensing, vol 48 n° 3 Tome 2 (March 2010)
[article]
Titre : Segmentation and reconstruction of polyhedral building roofs from aerial lidar points clouds Type de document : Article/Communication Auteurs : A. Sampath, Auteur ; J. Shan, Auteur Année de publication : 2010 Article en page(s) : pp 1554 - 1567 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse de groupement
[Termes IGN] cohérence géométrique
[Termes IGN] détection du bâti
[Termes IGN] diagramme de Voronoï
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] intégrité topologique
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] similitude
[Termes IGN] toitRésumé : (Auteur) This paper presents a solution framework for the segmentation and reconstruction of polyhedral building roofs from aerial LIght Detection And Ranging (lidar) point clouds. The eigenanalysis is first carried out for each roof point of a building within its Voronoi neighborhood. Such analysis not only yields the surface normal for each lidar point but also separates the lidar points into planar and nonplanar ones. In the second step, the surface normals of all planar points are clustered with the fuzzy k-means method. To optimize this clustering process, a potential-based approach is used to estimate the number of clusters, while considering both geometry and topology for the cluster similarity. The final step of segmentation separates the parallel and coplanar segments based on their distances and connectivity, respectively. Building reconstruction starts with forming an adjacency matrix that represents the connectivity of the segmented planar segments. A roof interior vertex is determined by intersecting all planar segments that meet at one point, whereas constraints in the form of vertical walls or boundary are applied to determine the vertices on the building outline. Finally, an extended boundary regularization approach is developed based on multiple parallel and perpendicular line pairs to achieve topologically consistent and geometrically correct building models. This paper describes the detail principles and implementation steps for the aforementioned solution framework. Results of a number of buildings with diverse roof complexities are presented and evaluated. Numéro de notice : A2010-272 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2009.2030180 Date de publication en ligne : 03/11/2009 En ligne : https://doi.org/10.1109/TGRS.2009.2030180 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30466
in IEEE Transactions on geoscience and remote sensing > vol 48 n° 3 Tome 2 (March 2010) . - pp 1554 - 1567[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2010031B RAB Revue Centre de documentation En réserve L003 Disponible Automated image-to-map discrepancy detection using iterative trimming / J. Radoux in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 2 (February 2010)
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Titre : Automated image-to-map discrepancy detection using iterative trimming Type de document : Article/Communication Auteurs : J. Radoux, Auteur ; P. Defourny, Auteur Année de publication : 2010 Article en page(s) : pp 173 - 181 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse d'image orientée objet
[Termes IGN] appariement de données localisées
[Termes IGN] base de données vectorielles
[Termes IGN] détection de changement
[Termes IGN] forêt
[Termes IGN] image numérique
[Termes IGN] itération
[Termes IGN] segmentation d'image
[Termes IGN] seuillage d'image
[Termes IGN] système d'information géographiqueRésumé : (Auteur) Keeping existing vector databases up to date is a real challenge for GIS data providers. This study directly compares a map with a more recent image in order to detect the discrepancies between them. An automatic workflow was designed to process the image based on existing information extracted from the vector database. First, geographic object-based image analysis provided automatically labeled image segments after matching the vector database to the image. Then, discrepan-cies were detected using a statistical iterative trimming, where outliers were excluded based on a likelihood threshold. Applied on forest map updating, the proposed workflow was able to detect about 75 percent of the forest regeneration, and 100 percent of the clear cuts with less than 10 percent of commission errors. This discrepancy detection approach assumes that discrepancy corresponds to small proportion of the map area and is very promising in diverse applications thanks to its flexibility. Copyright ASPRS Numéro de notice : A2010-051 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.76.2.173 En ligne : https://doi.org/10.14358/PERS.76.2.173 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30247
in Photogrammetric Engineering & Remote Sensing, PERS > vol 76 n° 2 (February 2010) . - pp 173 - 181[article]Fuzzy image segmentation for urban land-cover classification / I. Lizarazo in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 2 (February 2010)PermalinkMapping an annual weed with colour-infared aerial photography and image analysis / James H. Everitt in Geocarto international, vol 25 n° 1 (February 2010)PermalinkReal world objects in geobia through the exploitation of existing digital cartography and image segmentation / G. Smith in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 2 (February 2010)PermalinkAmélioration d'une base de données d'empreintes de bâtiments pour la reconstruction 3D : une approche par découpe et fusion / Bruno Vallet (2010)PermalinkAutomatic change detection of buildings in urban environment from very high spatial resolution images using existing geodatabase and prior knowledge / M. Bouziani in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 1 (January - February 2010)PermalinkChange detection in submetric optical images using land cover classification tools / Arnaud Le Bris (2010)PermalinkColors of the past: color image segmentation in historical topographic maps based on homogeneity / S. Leyk in Geoinformatica, vol 14 n° 1 (January 2010)PermalinkDétection et reconnaissance de la signalisation verticale par analyse d'images, ch 4. Détection et reconnaissance par ajustement de modèles géométriques et radiométriques / Bahman Soheilian (2010)PermalinkDetermining changes and flows in European landscapes 1990 - 2000 using CORINE land cover data / Jan Feranec in Applied Geography, vol 30 n° 1 (January 2010)PermalinkPermalinkPermalinkExtracting wire-frame models of street facades from 3D point clouds and the corresponding cadastral map / Karim Hammoudi (2010)PermalinkPermalinkExtraction et reconstruction des bâtiments en milieu urbain à partir d’images satellitaires optiques et radar à haute résolution / Hélène Sportouche (2010)PermalinkForest object-oriented classification with customized and automatic attribute selection / Olivier de Joinville (2010)PermalinkA formulation for unsupervised hierarchical segmentation of facade images with periodic models / Jean-Pascal Burochin (2010)PermalinkFusion d'images optique et radar à haute résolution pour la mise à jour de bases de données cartographiques / Vincent Poulain (2010)PermalinkPermalinkInfluence of image characteristics on image quality / T. Royer (2010)PermalinkIntegration of geographic information systems and remote sensing / Jeffrey L. Star (2010)Permalink