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Automated image-to-map discrepancy detection using iterative trimming / J. Radoux in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 2 (February 2010)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 76 n° 2 (February 2010) . - pp 173 - 181 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 géographique Résumé : (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 [article]