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Classification of digitized old maps
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SYSNO ASEP 0506953 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Classification of digitized old maps Author(s) Talich, M. (CZ)
Böhm, O. (CZ)
Soukup, Lubomír (UTIA-B) RID, ORCIDSource Title Advances and Trends in Geodesy, Cartography and Geoinformatics. - Leiden : Taylor & Francis Group, London, UK, 2018 / Molcikova S. ; Hurcikova V. ; Zeliznakova V. ; Blistan P. - ISBN 978-0-429-50564-5 Pages s. 197-202 Number of pages 6 s. Publication form Print - P Action 10th International Scientific and Professional Conference on Geodesy, Cartography and Geoinformatics, 2017 Event date 10.10.2017 - 13.10.2017 VEvent location Demanovska Dolina Country SK - Slovakia Event type EUR Language eng - English Country NL - Netherlands Keywords old maps ; classification of digital images ; Bayesian classification ; web application ; web map services Subject RIV DE - Earth Magnetism, Geodesy, Geography OECD category Physical geography Institutional support UTIA-B - RVO:67985556 UT WOS 000437494400032 EID SCOPUS 85061303226 DOI 10.1201/9780429505645 Annotation Because of their importance as historical sources, old maps are steadily becoming more interesting to researchers and public users. However, the users are no longer satisfied only by simple digitization and on-line publication. Users primarily require advanced web tools for more sophisticated work with old maps. This paper is concerned with classification of digitized old maps in form of raster images. An automatic classification of digital maps is useful tools. This process allows to automatically de-tect areas with common characteristic, i.e. forests, water surfaces, buildings etc. Technically it is a problem of assigning the image's pixels to one of several classes defined in advance. If the map is georeferenced the classified image can be used to determine the surface areas of the clas-sified regions, or otherwise evaluate their position. Unfortunately quite substantial difficulties can be expected when attempting to apply these tools. The main cause of these difficulties is varied quality of digitized maps resulting from damage caused to the original maps by time or storage conditions and from varying scanning procedures. Even individual maps from the same map series can differ quite a lot. The review of the main classification methods with special emphasis on the Bayesian meth-ods of classification is given. An example of this classification and its use is also given. Web application of raster image classification is introduced as well. The web application can classify both individual images and raster data provided via Web Map Services (WMS) with respect to OGC standards (Open Geospatial Consortium). After gathering the data, classification is applied to distinguish separate regions in the image. User can choose between several classification methods and adjust pertinent parameters. Furthermore, several subsequent basic analytical tools are offered. The classification results and registration parameters can be saved for further use. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2020
Number of the records: 1