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Is the orthometric height a holonomic coordinate? The sad story of a differential that could never be total / Fernando Sanso in Section 4 Bulletin IAG, n° 1 tome 1995 (January 1995)
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Titre : Is the orthometric height a holonomic coordinate? The sad story of a differential that could never be total Type de document : Article/Communication Auteurs : Fernando Sanso, Auteur Année de publication : 1995 Article en page(s) : pp 1 - 8 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] altitude orthométrique
[Termes IGN] calcul différentiel
[Termes IGN] coordonnées géographiques
[Termes IGN] hauteur ellipsoïdale
[Termes IGN] système de coordonnées
[Vedettes matières IGN] AltimétrieNuméro de notice : A1995-060 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33695
in Section 4 Bulletin IAG > n° 1 tome 1995 (January 1995) . - pp 1 - 8[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 18282-01 30.50 Tiré à part Centre de documentation Géodésie Disponible Kartographische Mustererkennung : rasterorientierte Verfahren zur Erfassung von Geo-informationen / Roland Eduard Stengele (1995)
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Titre : Kartographische Mustererkennung : rasterorientierte Verfahren zur Erfassung von Geo-informationen Titre original : [Reconnaissance de modèle cartographique : procédés orienté raster pour la saisie de l'information géographique] Type de document : Thèse/HDR Auteurs : Roland Eduard Stengele, Auteur Editeur : Zurich : Institut für Geodäsie und Photogrammetrie IGP - ETH Année de publication : 1995 Collection : IGP Mitteilungen, ISSN 0252-9335 num. 054 Importance : 147 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-3-906513-66-9 Note générale : Bibliographie Langues : Allemand (ger) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] appariement de modèles conceptuels de données
[Termes IGN] base de connaissances
[Termes IGN] base de données localisées
[Termes IGN] données maillées
[Termes IGN] extraction automatique
[Termes IGN] reconnaissance de formes
[Termes IGN] similitude
[Termes IGN] vectorisationIndex. décimale : 33.30 Photogrammétrie numérique Résumé : (Auteur) Geographic Information Systems (GIS) is a key technology in future. Even today this technology is indispensable to a lot of applications for acquisition, management, processing and presentation of spatial data. Usually the acquisition of spatial data is time- and staff consuming and thus an expensive process. Therefore it seems reasonable to open up the information of existing analogue maps and schemes available in great variety for modern GIS-technology. Due to their neutral geometry and thematic contents topographic maps are particularly suitable as basic information for many applications. The scanner technology offers the basis for automating the acquisition of analogue storage media. Management of spatial data beyond the task of pure visualization requires analytic image processing to extract the logical features. This complex problem can be automated by simulating the capabilities of human perception with computers. These activities are focused on the discipline of pattern recognition, a branch of artificial intelligence.
This paper presents an overall view of pattern recognition techniques suitable for cartographic products, subsequently designated as cartographic pattern recognition. A study on the characteristics of this application and the investigations done so far resulted in the requirement to integrate more and more raster-based tools into the recognition-process. Previous approaches are mainly based on a raster-to-vector conversion of images and the patterns are classified by topological and metric features derived from vector-data. However, the analysis of patterns is affected adversely by unavoidable loss of information due to this conversion.
In the field of image processing two raster images are compared by correlation techniques. Template matching is a special correlation technique and describes the search for patterns in the raster image by calculating similarity of the covered image part and a synthetic prototype of a feature class at each position. This technique has to be optimized with regard to two aspects for exposing its potential for cartographic pattern recognition:
1- Higher recognition rates are obtained by calculating similarity, which is robust against small variations of patterns belonging to the same feature class (different size, orientation, thickness of lines etc.).
2- Acceptable calculating periods can only be achieved by a hierarchic strategy.
The measurement of similarity with different weights is of vital importance in regard to both objectives. The basis of this approach is the variable importance of individual pixels for the pattern shape and its identification. High-significant, significant and insignificant pixels of fore-and background are distinguished. The user can assign the weights to the pixels by editing different colors. In this way the acquisition of knowledge describing the characteristics of a template and the small differences between similar templates can be done easily and very efficiently in a graphic manner.
The library of all available templates represents a graphic-designed knowledge base and is far more than a pure database. For instance the method of knowledge-based template matching is suitable for recognition of map text in horizontal orientation. Extensive random samples proved recognition rates of 95.8% for topographic maps of the Swiss Federal Office of Topography on a scale of 1:25'000. Furthermore any cartographic symbols can be located reliable. Above all this is practicable even for symbols, which are not isolated from the graphic context, but also touch or overlap other graphic elements.
Various local raster operators are specifically combined in order to extract the black-colored signature for buildings in topographic maps. 98% of approximately 10'000 buildings can be recognized automatically in a typical map sheet on a scale of 1:25'000.
The development and implementation of a raster-based system for cartographic pattern reco-gnition was a focal research topic. Some special requirements had to be considered. The variety of possible applications for GIS and cartography is indicated by means of several examples: Data acquisition for the establishment of nationwide spatial information systems (e.g. data base of geographic names, project Vector25 of the Swiss Federal Office of Topography), support for cartographic tasks (e.g. map revision, placement of map text) and acquisition of specific data for various GIS-projects (e.g. to document the change of landscape, modeling of objects for generating SD-images of landscape).Numéro de notice : 27136 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère DOI : 10.3929/ethz-a-001442656 En ligne : http://dx.doi.org/10.3929/ethz-a-001442656 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=56330 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 27136-01 33.30 Livre Centre de documentation Photogrammétrie - Lasergrammétrie Disponible 27136-02 33.30 Livre Centre de documentation Photogrammétrie - Lasergrammétrie Disponible
contenu dans Workshop on progress in automated map generalization, ICC 1995, 1 - 3 September 1995, Barcelona, Spain / Barbara P. Buttenfield (1995)
Titre : Knowledge formalization for automated relief generalization Type de document : Article/Communication Auteurs : Pascale Monier , Auteur
Editeur : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 1995 Conférence : ICA 1995, 1st Workshop on progress in Automated Map Generalization 01/09/1995 03/09/1995 Barcelone Espagne Importance : 1 p. Format : 21 x 30 cm Langues : Anglais (eng) Descripteur : [Termes IGN] figuré du terrain
[Termes IGN] modèle numérique de terrain
[Termes IGN] relief
[Termes IGN] transformation en ondelettes
[Vedettes matières IGN] GénéralisationNuméro de notice : C1995-048 Affiliation des auteurs : COGIT (1988-2011) Thématique : GEOMATIQUE Nature : Communication Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92589 Documents numériques
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contenu dans Workshop on progress in automated map generalization, ICC 1995, 1 - 3 September 1995, Barcelona, Spain / Barbara P. Buttenfield (1995)
Titre : Knowledge formalization of linear feature geometry for generalization Type de document : Article/Communication Auteurs : Corinne Plazanet , Auteur
Editeur : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 1995 Conférence : ICA 1995, 1st Workshop on progress in Automated Map Generalization 01/09/1995 03/09/1995 Barcelone Espagne Importance : 3 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] base de règles
[Termes IGN] classification
[Termes IGN] formalisation
[Termes IGN] objet géographique linéaire
[Termes IGN] précision des mesures
[Termes IGN] segmentation
[Vedettes matières IGN] GénéralisationNuméro de notice : C1995-049 Affiliation des auteurs : COGIT (1988-2011) Thématique : GEOMATIQUE Nature : Communication Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92591 Documents numériques
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Titre : Kontextsensitive Bildinterpretation mit Markoff-Zufallsfeldern Titre original : [Photo-interprétation en tenant compte du contexte avec les champs aléatoires de Markov] Type de document : Thèse/HDR Auteurs : M. Köster, Auteur Editeur : Munich : Bayerische Akademie der Wissenschaften Année de publication : 1995 Collection : DGK - C Sous-collection : Dissertationen num. 444 Importance : 73 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-3-7696-9487-1 Note générale : Bibliographie Langues : Allemand (ger) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] champ aléatoire de Markov
[Termes IGN] classification bayesienne
[Termes IGN] distribution de Gibbs
[Termes IGN] image aérienne
[Termes IGN] optimisation (mathématiques)
[Termes IGN] reconnaissance d'objets
[Termes IGN] reconnaissance de formes
[Termes IGN] segmentation d'image
[Termes IGN] théorème de Bayes
[Termes IGN] voisinage (relation topologique)Index. décimale : 35.20 Traitement d'image Résumé : (Auteur)This thesis solves the problem of interpretation of digital images by Markov random fields in connec-tion with Bayesian statistics. The interpretation requires the description of the objects expected in an image and of the objects existing in the image. The appearence of objects in images is ambiguous, so that context relations between neighbouring objects have to be included. Object recognition requires the labeling of segmented image primitives. By this process uncertainties appear which have to be considered by the object description as well as by the labeling.
A mathematical, stochastic method is used, which is theoretically founded and domain independent. Based on Markov random fields a relational description is created for the expected and the existing objects. The relations between neighbouring objects are represented by potentials of cliques of the Gibbs distributions of the Markov random fields. This creates a context dependency based on the local neighbourhood. The flexibility of Bayesian statistics allows the introduction of prior informa-tion of the unknown object labels, which consists of the frequencies of the occurrence of objects and their necessary neighbourhood relations. The labeling problem is solved by maximizing the posteriori density which follows from the Bayes' theorem. Deterministic and stochastic optimization algorithms are compared.
The interpretation model not only contains features of the objects and relations {o their neighbours, indirect neighbourhood objects and three pairwise neighbouring objects are also included. An inter--pretation is therefore possible with a more detailed consideration of object relations. A semantic model of concrete objects and their context relations in aerial images is constructed. If there are no images of the same domain, elements in the object model will be determined by heuristic arguments.
The approach has been tested on a generated and a real image. The ideal circumstances of the synthe-tic image are used, to investigate influences of variations of the image model and of the optimization algorithms. Finally a segmented image with three color channels is interpreted.Numéro de notice : 28045 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=63392 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 28045-01 35.20 Livre Centre de documentation Télédétection Disponible 28045-02 35.20 Livre Centre de documentation Télédétection Disponible PermalinkPermalinkPermalinkPermalinkMeasurement, characterization and classification for automated line feature generalization / Corinne Plazanet (1995)
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PermalinkMesure de qualité d'interprétation d'images SPOT pour l'occupation du sol / Hervé Le Men in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 137 (Janvier 1995)
PermalinkPermalinkPermalinkModellierung stochastisch korrelierter Signalanteile in geodätischen Beobachtungen, angewendet insbesondere auf die Bestimmung des Schwerefeldes aus der Kombination von kinematischen und dynamischen Messungen / K. Neumayer (1995)
PermalinkMultiple paradigms for automating map generalization: geometry, topology, hierarchical partioning and local triangulation / Anne Ruas (1995)
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