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A rule-based parameter aided with object-based classification approach for extraction of building and roads from WorldView-2 images / Zahra Ziaei in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)  

Public [article]  inGeocarto international > vol 29 n° 5 - 6 (August - October 2014) . - pp 554-569 Titre : A rule-based parameter aided with object-based classification approach for extraction of building and roads from WorldView-2 images Type de document : Article/Communication Auteurs : Zahra Ziaei, Auteur ; Biswajeet Pradhan, Auteur ; Shattri Bin Mansor, Auteur Année de publication : 2014 Article en page(s) : pp 554-569 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification à base de connaissances [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] détection du bâti [Termes IGN] eCognition [Termes IGN] image Worldview [Termes IGN] plus proche voisin, algorithme du Résumé : (auteur) Roads and buildings constitute a significant proportion of urban areas. Considerable amount of research has been done on the road and building extraction from remotely sensed imagery. However, a few of them have been concentrating on using only spectral information. This study presents a comparison between three object-based models for urban features’ classification, specifically roads and buildings, from WorldView-2 satellite imagery. The three applied algorithms are support vector machines (SVMs), nearest neighbour (NN) and proposed rule-based system. The results indicated that the proposed rules in this study, despite the spectral complexity of land cover types, performed a satisfactory output with an overall accuracy of 92.92%. The advantages offered by the proposed rules were not provided by other two applied algorithms and it revealed the highest accuracy compared to SVM and NN. The overall accuracy for SVM was 76.76%, which is almost similar to the result achieved by NN (77.3%). Numéro de notice : A2014-412 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2013.819039 En ligne : https://doi.org/10.1080/10106049.2013.819039 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73949 [article]

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