본문 바로가기
  • Home

A Comparative Study on Methods for Identifying Partially Changed Objects to Detect Deleted Objects in Partial Maps

  • Journal of Software Assessment and Valuation
  • Abbr : JSAV
  • 2023, 19(3), pp.55-63
  • DOI : 10.29056/jsav.2023.09.06
  • Publisher : Korea Software Assessment and Valuation Society
  • Research Area : Engineering > Computer Science
  • Received : September 12, 2023
  • Accepted : September 20, 2023
  • Published : September 30, 2023

KIM KWANG SOO 1 Kim, Bong Wan 2

1한국전자통신연구원
2한국전자통신연구소

Accredited

ABSTRACT

In order to prevent safety accidents in urban underground spaces, an integrated underground space map is being generated. To shorten the update time of the map, a changed object detection and extraction technology is applied, which selects only updated objects from newly input maps. Updated objects are classified into a new object, a deleted object, and an attribute changed object. However, when a partial map including only buried facilities that are targets of excavation work is input, a problem of not finding a deleted object occurs. In this paper, we discussed three methods to find deleted objects in the partial map. In order to detect the deleted object, it must be determined whether an updated object exists in which only part of the original objects has been changed. DE-9IM, Relate function, and Intersection function were used to extract partially changed objects, and the performances of these methods were compared by using linear objects. All three methods determined objects including overlapping shapes as the same object without errors, and the Relate function showed the fastest performance.

Citation status

* References for papers published after 2022 are currently being built.