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Auteur S. Leyk |
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Colors of the past: color image segmentation in historical topographic maps based on homogeneity / S. Leyk in Geoinformatica, vol 14 n° 1 (January 2010)
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Titre : Colors of the past: color image segmentation in historical topographic maps based on homogeneity Type de document : Article/Communication Auteurs : S. Leyk, Auteur ; R. Boesch, Auteur Année de publication : 2010 Article en page(s) : pp 1 - 21 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] archives
[Termes IGN] carte numérisée
[Termes IGN] carte topographique
[Termes IGN] détection de changement
[Termes IGN] image en couleur
[Termes IGN] qualité cartographique
[Termes IGN] segmentation d'image
[Termes IGN] système d'information géographiqueRésumé : (Auteur) A novel approach to color image segmentation (CIS) in scanned archival topographic maps of the 19th century is presented. Archival maps provide unique information for GIS-based change detection and are the only spatially contiguous data sources prior to the establishment of remote sensing. Processing such documents is challenging due to their very low graphical quality caused by ageing, manual production and scanning. Typical artifacts are high degrees of mixed and false coloring, as well as blurring in the images. Existing approaches for segmentation in cartographic documents are normally presented using well-conditioned maps. The CIS approach presented here uses information from the local image plane, the frequency domain and color space. As a first step, iterative clustering is based on local homogeneity, frequency of homogeneity-tested pixels and similarity. By defining a peak-finding rule, “hidden” color layer prototypes can be identified without prior knowledge. Based on these prototypes a constrained seeded region growing (SRG) process is carried out to find connected regions of color layers using color similarity and spatial connectivity. The method was tested on map pages with different graphical properties with robust results as derived from an accuracy assessment. Copyright Springer Numéro de notice : A2010-009 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-008-0074-z Date de publication en ligne : 16/01/2009 En ligne : https://doi.org/10.1007/s10707-008-0074-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30205
in Geoinformatica > vol 14 n° 1 (January 2010) . - pp 1 - 21[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 057-2010011 RAB Revue Centre de documentation En réserve L003 Disponible Extracting composite cartographic area features in low-quality maps / S. Leyk in Cartography and Geographic Information Science, vol 36 n° 1 (January 2009)
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Titre : Extracting composite cartographic area features in low-quality maps Type de document : Article/Communication Auteurs : S. Leyk, Auteur ; R. Boesch, Auteur Année de publication : 2009 Article en page(s) : pp 71 - 79 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] attribut géomètrique
[Termes IGN] carte ancienne
[Termes IGN] carte topographique
[Termes IGN] extraction automatique
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] forêt
[Termes IGN] méthode robuste
[Termes IGN] objet géographique zonal
[Termes IGN] signe conventionnelRésumé : (Auteur) We describe an extraction method for area features defined by composite cartographic elements and derived from historical, manually produced maps of low graphical quality. Composite elements appear in many topographic maps of the 19th and 20th century which provide unique information about the landscape of the past. We develop a method from prior research for extracting forest areas from the historic Siegfried Map, on which they are represented by sets of circular forest symbols within boundary regions. First, a prototype search identifies forest symbols characterized by a combination of geometric attributes of connected components, shape descriptions of the local neighborhood, and patterns formed by similar graphic elements. Next, the complete set of forest symbols is iteratively determined by testing forest symbol candidates in the vicinity of the prototypes if they belong to a group of sufficient other candidates. Finally, spatial expansion determines the forest net area described by the composition of recognized forest symbols and continues to fill gaps between forest areas and their boundaries, as well as larger objects within the forest area. Automated extraction from three map pages resulted in an accuracy of K = 95 percent, which indicates high robustness for automated processing of entire map series. The new approach presented in this paper represents a general methodological framework for the extraction of area features from composite map elements in low-quality maps. Copyright CaGISociety Numéro de notice : A2009-042 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1559/152304009787340115 En ligne : https://doi.org/10.1559/152304009787340115 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29672
in Cartography and Geographic Information Science > vol 36 n° 1 (January 2009) . - pp 71 - 79[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-09011 RAB Revue Centre de documentation En réserve L003 Disponible