New Tools for the Classification and Filtering of Historical Maps

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F19%3A82254" target="_blank" >RIV/60460709:41330/19:82254 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.mdpi.com/2220-9964/8/10/455" target="_blank" >https://www.mdpi.com/2220-9964/8/10/455</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/ijgi8100455" target="_blank" >10.3390/ijgi8100455</a>

Jazyk výsledku

angličtina

Název v původním jazyce

New Tools for the Classification and Filtering of Historical Maps

Popis výsledku v původním jazyce

Historical maps constitute an essential information for investigating the ecological and landscape features of a region over time. The integration of heritage maps in GIS models requires their digitalization and classification. This paper presents a semi automatic procedure for the digitalization of heritage maps and the successive filtering of undesirable features such as text, symbols and boundary lines. The digitalization step is carried out using Object based Image Analysis OBIA in GRASS GIS and R, combining image segmentation and machine learning classification. The filtering step is performed by two GRASS GIS modules developed during this study and made available as GRASS GIS add ons. The first module evaluates the size of the filter window needed for the removal of text, symbols and lines the second module replaces the values of pixels of the category to be removed with values of the surrounding pixels. The procedure has been tested on three maps with different characteristics, the Historical

Název v anglickém jazyce

New Tools for the Classification and Filtering of Historical Maps

Popis výsledku anglicky

Historical maps constitute an essential information for investigating the ecological and landscape features of a region over time. The integration of heritage maps in GIS models requires their digitalization and classification. This paper presents a semi automatic procedure for the digitalization of heritage maps and the successive filtering of undesirable features such as text, symbols and boundary lines. The digitalization step is carried out using Object based Image Analysis OBIA in GRASS GIS and R, combining image segmentation and machine learning classification. The filtering step is performed by two GRASS GIS modules developed during this study and made available as GRASS GIS add ons. The first module evaluates the size of the filter window needed for the removal of text, symbols and lines the second module replaces the values of pixels of the category to be removed with values of the surrounding pixels. The procedure has been tested on three maps with different characteristics, the Historical

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10511 - Environmental sciences (social aspects to be 5.7)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název periodika

ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION

ISSN

2220-9964

e-ISSN

2220-9964

Svazek periodika

8

Číslo periodika v rámci svazku

10

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

24

Strana od-do

1-24

Kód UT WoS článku

000498398300030

EID výsledku v databázi Scopus

2-s2.0-85075503022