Robust Grid Detection in Historical Map Images

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F22%3A43966586" target="_blank" >RIV/49777513:23520/22:43966586 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/9897721" target="_blank" >https://ieeexplore.ieee.org/document/9897721</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICIP46576.2022.9897721" target="_blank" >10.1109/ICIP46576.2022.9897721</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Robust Grid Detection in Historical Map Images

Popis výsledku v původním jazyce

This paper presents a novel method for grid detection in historical maps. The approach is based on Hough transform accompanied with a sophisticated post-processing. They are applied to detect the grid that consists of graticule lines. It works without any training and does not require any annotated data. The proposed approach is very efficient in detecting the rectangular grid and the intersection points as shown in the international &quot;MapSeg&quot; segmentation competition, where it won the Task 3 with a significant margin. The robustness of the proposed method has been demonstrated by evaluating on another dataset composed of significantly different cadastral map images with excellent results.

Název v anglickém jazyce

Robust Grid Detection in Historical Map Images

Popis výsledku anglicky

This paper presents a novel method for grid detection in historical maps. The approach is based on Hough transform accompanied with a sophisticated post-processing. They are applied to detect the grid that consists of graticule lines. It works without any training and does not require any annotated data. The proposed approach is very efficient in detecting the rectangular grid and the intersection points as shown in the international &quot;MapSeg&quot; segmentation competition, where it won the Task 3 with a significant margin. The robustness of the proposed method has been demonstrated by evaluating on another dataset composed of significantly different cadastral map images with excellent results.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název statě ve sborníku

2022 IEEE International Conference on Image Processing (ICIP)

ISBN

978-1-66549-620-9

ISSN

1522-4880

e-ISSN

2381-8549

Počet stran výsledku

5

Strana od-do

1931-1935

Název nakladatele

IEEE

Místo vydání

New York

Místo konání akce

Bordeaux

Datum konání akce

16. 10. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001058109502009