Classification of digitized old maps

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00025615%3A_____%2F18%3AN0000021" target="_blank" >RIV/00025615:_____/18:N0000021 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/67985556:_____/18:00506953

Výsledek na webu

<a href="https://www.taylorfrancis.com/books/e/9780429505645/chapters/10.1201/9780429505645-32" target="_blank" >https://www.taylorfrancis.com/books/e/9780429505645/chapters/10.1201/9780429505645-32</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1201/9780429505645" target="_blank" >10.1201/9780429505645</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Classification of digitized old maps

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Classification of digitized old maps

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10508 - Physical geography

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Advances and Trends in Geodesy, Cartography and Geoinformatics

ISBN

978-0-429-50564-5

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

197-202

Název nakladatele

Taylor & Francis Group, London, UK

Místo vydání

Leiden, The Netherlands

Místo konání akce

DEMÄNOVSKÁ DOLINA, LOW TATRAS, SLOVAKIA

Datum konání akce

10. 10. 2017

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

000437494400032