Road network extraction with new vectorization and pruning from high-resolution RS images
Jin, Hang, Feng, Yanming, & Li, Bofeng (2008) Road network extraction with new vectorization and pruning from high-resolution RS images. In Image and Vision Computing New Zealand, 2008. IVCNZ 2008. 23rd International Conference, IEEE , Lincoln University, Christchurch, New Zealand, pp. 1-6.
This is the latest version of this eprint.
With the increasing resolution of remote sensing images, road network can be displayed as continuous and homogeneity regions with a certain width rather than traditional thin lines. Therefore, road network extraction from large scale images refers to reliable road surface detection instead of road line extraction. In this paper, a novel automatic road network detection approach based on the combination of homogram segmentation and mathematical morphology is proposed, which includes three main steps: (i) the image is classified based on homogram segmentation to roughly identify the road network regions; (ii) the morphological opening and closing is employed to fill tiny holes and filter out small road branches; and (iii) the extracted road surface is further thinned by a thinning approach, pruned by a proposed method and finally simplified with Douglas-Peucker algorithm. Lastly, the results from some QuickBird images and aerial photos demonstrate the correctness and efficiency of the proposed process.
Citation countsare sourced monthly fromand 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 theindexing service can be viewed at the linked Google Scholar™ search.
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.
|Item Type:||Conference Paper|
|Keywords:||road detection, homogram, mathematical morphology, remote sensing image|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > GEOMATIC ENGINEERING (090900) > Photogrammetry and Remote Sensing (090905)|
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > GEOMATIC ENGINEERING (090900) > Geospatial Information Systems (090903)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2008 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:||08 Mar 2010 14:38|
|Last Modified:||29 Feb 2012 23:48|
Available Versions of this Item
- Road network extraction with new vectorization and pruning from high-resolution RS images. (deposited 29 Jan 2010 09:14)
- Road network extraction with new vectorization and pruning from high-resolution RS images. (deposited 08 Mar 2010 14:38)[Currently Displayed]
Repository Staff Only: item control page