QUT ePrints

Enhancing digital road map with lane details extracted from large-scale stereo aerial imagery using object-oriented image analysis

Jin, Hang, Li, Zhengrong, & Feng, Yanming (2009) Enhancing digital road map with lane details extracted from large-scale stereo aerial imagery using object-oriented image analysis. In Proceedings of Surveying and Spatial Sciences Institute Biennial International Conference, Adelaide Convention Centre, Adelaide, South Australia.

View at publisher

Abstract

Precise, up-to-date and increasingly detailed road maps are crucial for various advanced road applications, such as lane-level vehicle navigation, and advanced driver assistant systems. With the very high resolution (VHR) imagery from digital airborne sources, it will greatly facilitate the data acquisition, data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lane information from aerial images with employment of the object-oriented image analysis method. Our proposed algorithm starts with constructing the DSM and true orthophotos from the stereo images. The road lane details are detected using an object-oriented rule based image classification approach. Due to the affection of other objects with similar spectral and geometrical attributes, the extracted road lanes are filtered with the road surface obtained by a progressive two-class decision classifier. The generated road network is evaluated using the datasets provided by Queensland department of Main Roads. The evaluation shows completeness values that range between 76% and 98% and correctness values that range between 82% and 97%.

Impact and interest:

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:

311 since deposited on 28 Jan 2010
76 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.

ID Code: 30111
Item Type: Conference Paper
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 2009 [please consult the authors]
Deposited On: 29 Jan 2010 07:14
Last Modified: 10 Jun 2010 00:20

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page