Kumar, Pankaj and Lewis, Paul and McElhinney, Conor P. and Boguslawski, Pawel and McCarthy, Tim (2016) Snake energy analysis and results validation for a mobile laser scanning data based automated road edge extraction algorithm. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10 (2). pp. 763-773. ISSN 1939-1404

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Abstract

The negative impact of road accidents cannot be ignored in terms of the very sizeable social and economic loss. Road infrastructure has been identified as one of the main causes of the road accidents. They are required to be recorded, located, measured, and classified in order to schedule maintenance and identify the possible risk elements of the road. Toward this, an accurate knowledge of the road edges increases the reliability and precision of extracting other road features. We have developed an automated algorithm for extracting road edges from mobile laser scanning (MLS) data based on the parametric active contour or snake model. The algorithm involves several internal and external energy parameters that need to be analyzed in order to find their optimal values. In this paper, we present a detailed analysis of the snake energy parameters involved in our road edge extraction algorithm. Their optimal values enable us to automate the process of extracting edges from MLS data for tested road sections. We present a modified external energy in our algorithm and demonstrate its utility for extracting road edges from low and nonuniform point density datasets. A novel validation approach is presented, which provides a qualitative assessment of the extracted road edges based on direct comparisons with reference road edges. This approach provides an alternative to traditional road edge validation methodologies that are based on creating buffer zones around reference road edges and then computing quality measure values for the extracted edges. We tested our road edge extraction algorithm on datasets that were acquired using multiple MLS systems along various complex road sections. The successful extraction of road edges from these datasets validates the robustness of our algorithm for use in complex route corridor environments.

Item Type:	Article
Additional Information:	Research presented in this paper was initially funded by the Irish Research Council Enterprise Partnership scheme and Strategic Research Cluster grants (07/SRC/I1168 & 13/IF/I2782) of Science Foundation Ireland under the National Development Plan. The research is continued at Universiti Teknologi Malaysia. The authors gratefully acknowledge this support. The authors also acknowledge the 3D Laser Mapping company for providing the Streetmapper mobile laser scanning data.
Keywords:	Complex road; mobile laser scanning (MLS); road edges; snake energy; validation approach;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
Item ID:	9258
Identification Number:	https://doi.org/10.1109/JSTARS.2016.2564984
Depositing User:	Tim McCarthy
Date Deposited:	19 Feb 2018 15:45
Journal or Publication Title:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publisher:	IEEE
Refereed:	Yes
Funders:	Irish Research Council Enterprise Partnership, Science Foundation Ireland (SFI)
URI:	http://ieeexplore.ieee.org
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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