QUT ePrints

Evaluating automatic road detection across a large aerial imagery collection

Guo, Xufeng, Dean, David B., Denman, Simon, Fookes, Clinton B., & Sridharan, Sridha (2011) Evaluating automatic road detection across a large aerial imagery collection. In Proceedings of the 2011 International Conference of Digital Image Computing: Techniques and Applications, IEEE, Sheraton Noosa Resort & Spa, Noosa, QLD, pp. 140-145.

[img] Accepted Version (PDF 4Mb)
Available under License Creative Commons Attribution Share Alike 3.0 Australia.
    [img] Presentation (PDF 3826Kb)
    Available under License Creative Commons Attribution Share Alike 3.0 Australia.

      View at publisher

      Abstract

      The automated extraction of roads from aerial imagery can be of value for tasks including mapping, surveillance and change detection. Unfortunately, there are no public databases or standard evaluation protocols for evaluating these techniques. Many techniques are further hindered by a reliance on manual initialisation, making large scale application of the techniques impractical. In this paper, we present a public database and evaluation protocol for the evaluation of road extraction algorithms, and propose an improved automatic seed finding technique to initialise road extraction, based on a combination of geometric and colour features.

      Citations:

      1 times in Scopus
      Search Google Scholar™

      Citation countsare sourced monthly from Scopus and Web of Science citation databases.

      These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science generally from 1980 onwards.

      Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

      Full-text downloads:

      62 since deposited on 13 Dec 2011
      40 in the past twelve months

      Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

      More statistics...
      ID Code: 47715
      Item Type: Conference Paper
      Keywords: Automatic Road Detection, Database
      ISBN: 9780769545882
      Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)
      Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
      Past > Institutes > Information Security Institute
      Past > Schools > School of Engineering Systems
      Copyright Owner: Copyright 2011 IEEE
      Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
      Deposited On: 14 Dec 2011 09:14
      Last Modified: 23 May 2013 14:53

      Export: EndNote | Dublin Core | BibTeX

      Repository Staff Only: item control page