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Detection and vectorization of roads from lidar data / S. Clode in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 5 (May 2007)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 5 (May 2007) . - pp 517 - 535 Titre : Detection and vectorization of roads from lidar data Type de document : Article/Communication Auteurs : S. Clode, Auteur ; Franz Rottensteiner, Auteur ; P. Kootsookos, Auteur ; E. Zelniker, Auteur Année de publication : 2007 Article en page(s) : pp 517 - 535 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Australie [Termes IGN] axe médian [Termes IGN] convolution (signal) [Termes IGN] détection automatique [Termes IGN] détection de contours [Termes IGN] données lidar [Termes IGN] extraction du réseau routier [Termes IGN] lasergrammétrie [Termes IGN] milieu urbain [Termes IGN] réseau routier [Termes IGN] semis de points [Termes IGN] vectorisation Résumé : (Auteur) A method for the automatic detection and vectorization of roads from lidar data is presented. To extract roads from a lidar point cloud, a hierarchical classification technique is used to classify the lidar points progressively into road and non-road points. During the classification process, both intensity and height values are initially used. Due to the homogeneous and consistent nature of roads, a local point density is introduced to finalize the classification. The resultant binary classification is then vectorized by convolving a complex-valued disk named the Phase Coded Disk (PCD) with the image to provide three separate pieces of information about the road. The centerline and width of the road are obtained from the resultant magnitude image while the direction is determined from the corresponding phase image, thus completing the vectorized road model. All algorithms used are described and applied to two urban test sites. Completeness values of 0.88 and 0.79 and correctness values of 0.67 and 0.80 were achieved for the classification phase of the process. The vectorization of the classified results yielded RMS values of 1.56 m and 1.66 m, completeness values of 0.84 and 0.81 and correctness values of 0.75 and 0.80 for two different data sets. Copyright ASPRS Numéro de notice : A2007-244 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.5.517 En ligne : https://doi.org/10.14358/PERS.73.5.517 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28607 [article]

A filtering strategy for interest point detecting to improve repeatability and information content / Q. Zhu in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 5 (May 2007)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 5 (May 2007) . - pp 547 - 553 Titre : A filtering strategy for interest point detecting to improve repeatability and information content Type de document : Article/Communication Auteurs : Q. Zhu, Auteur ; B. Wu, Auteur ; N. Wan, Auteur Année de publication : 2007 Article en page(s) : pp 547 - 553 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse comparative [Termes IGN] détection automatique [Termes IGN] filtrage de points [Termes IGN] point d'intérêt [Termes IGN] texture d'image Résumé : (Auteur) This paper compares several stereo image interest point detectors with respect to their repeatability and information content through experimental analysis. The Harris-Laplace detector gives better results than other detectors in areas of good texture; however, in areas of poor texture, the Harris-Laplace detector may be not the best choice. A feature-related filtering strategy is designed for the Harris-Laplace detector (as well as the standard Harris detector) to improve the repeatability and information content for imagery with both good and poor texture: (a) the local information entropy is computed to describe the local feature of the image; and (b) the redundant interest points are filtered according to the interest strength and the local information entropy. After the filtering process, the repeatability and information content of the final interest points are improved, and the mismatching then can be reduced. This conclusion is supported by experimental analysis with actual stereo images. Copyright ASPRS Numéro de notice : A2007-245 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.5.547 En ligne : https://doi.org/10.14358/PERS.73.5.547 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28608 [article]