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An intelligent approach towards automatic shape modelling and object extraction from satellite images using cellular automata based algorithm / P. V. Arun in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)  

Public [article]  inGeocarto international > vol 29 n° 5 - 6 (August - October 2014) . - pp 628-638 Titre : An intelligent approach towards automatic shape modelling and object extraction from satellite images using cellular automata based algorithm Type de document : Article/Communication Auteurs : P. V. Arun, Auteur Année de publication : 2014 Article en page(s) : pp 628-638 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] champ aléatoire de Markov [Termes IGN] classification par réseau neuronal [Termes IGN] extraction de traits caractéristiques [Termes IGN] image IRS-LISS [Termes IGN] image Landsat [Termes IGN] interpolation Résumé : (auteur) Automatic feature extraction domain has witnessed the application of many intelligent methodologies over past decade; however detection accuracy of these approaches were limited as object geometry and contextual knowledge were not given enough consideration. In this paper, we propose a frame work for accurate detection of features along with automatic interpolation, and interpretation by modelling feature shape as well as contextual knowledge using advanced techniques such as SVRF, Cellular Neural Network, Core set, and MACA. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the CNN approach. CNN has been effective in modelling different complex features effectively and complexity of the approach has been considerably reduced using corset optimization. The system has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prologue approach. System has been also proved to be effective in providing intelligent interpolation and interpretation of random features. Numéro de notice : A2014-419 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2013.826738 En ligne : https://doi.org/10.1080/10106049.2013.826738 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73955 [article]

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