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Multi-criteria, graph-based road centerline vectorization using ordered weighted averaging operators / Fateme Ameri in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 2 (February 2016)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 2 (February 2016) . - pp 107 - 120 Titre : Multi-criteria, graph-based road centerline vectorization using ordered weighted averaging operators Type de document : Article/Communication Auteurs : Fateme Ameri, Auteur ; Mohammad Javad Valadan Zoej, Auteur ; Mehdi Mokhtarzade, Auteur Année de publication : 2016 Article en page(s) : pp 107 - 120 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] classification dirigée [Termes IGN] extraction du réseau routier [Termes IGN] graphe [Termes IGN] image satellite [Termes IGN] pondération [Termes IGN] réseau routier [Termes IGN] théorie des graphes [Termes IGN] vectorisation Résumé : (auteur) In this paper, a novel road vectorization methodology based on image space clustering technique and weighted graph theory is presented. The proposed methodology describes a road as a set of optimized points on the centerline which should be connected by defining a number of appropriate criteria. The main contribution of this paper is to design a weighting scheme for combining a small number of road identities using Ordered Weighted Averaging (OWA) operators by defining appropriate decision strategy. In this regard, a novel geometric criterion is introduced. Result of the OWA aggregation specifies weight of each edge in the road network graph. Comparing the proposed approach with two state-of-the-art image space clustering-based road vectorization methods proves its efficiency to deal with roads with different widths, parallel roads with different distances, different types of intersections, and also noise clusters. Obtaining improved quality measures for several high-resolution images, demonstrates the successfulness of the vectorization approach. Numéro de notice : A2016-054 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.2.107 En ligne : http://dx.doi.org/10.14358/PERS.82.2.107 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79655 [article]

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Road vectorisation from high-resolution imagery based on dynamic clustering using particle swarm optimisation / Fateme Ameri in Photogrammetric record, vol 30 n° 152 (December 2015 - February 2016)  

Public [article]  inPhotogrammetric record > vol 30 n° 152 (December 2015 - February 2016) . - pp 363 - 386 Titre : Road vectorisation from high-resolution imagery based on dynamic clustering using particle swarm optimisation Type de document : Article/Communication Auteurs : Fateme Ameri, Auteur ; Mohammad Javad Valadan Zoej, Auteur Année de publication : 2015 Article en page(s) : pp 363 - 386 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification automatique d'objets [Termes IGN] extraction automatique [Termes IGN] extraction du réseau routier [Termes IGN] image aérienne [Termes IGN] image Ikonos [Termes IGN] image Quickbird [Termes IGN] optimisation par essaim de particules [Termes IGN] réseau routier [Termes IGN] vectorisation Résumé : (auteur) This paper introduces an innovative automatic road-vectorisation algorithm based on dynamic pixel clustering using particle swarm optimisation. A new cost function is designed to optimise the number and position of road keypoints and is capable of deriving road centrelines without considering geometric, spectral or topological characteristics in the road model. The algorithm is applied to different high-resolution images (IKONOS, QuickBird and aerial photographs) and is evaluated with respect to RMSE, correctness and completeness. Moreover, a new quality parameter is defined to evaluate a “kinking” effect in roads. Extraction of different road shapes with an acceptable precision in both urban and rural environments proves the efficiency of the algorithm in yielding complete road networks. Numéro de notice : A2015-827 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12123 Date de publication en ligne : 15/12/2015 En ligne : https://doi.org/10.1111/phor.12123 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79123 [article]

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