Snake energy analysis and result validation for a mobile laser scanning data-based automated road edge extraction algorithm

Kumar, Pankaj; Lewis, Paul; McElhinney, Conor P.; Boguslawski, Pawel; McCarthy, Tim

Abstract

© 2008-2012 IEEE. 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.

• Journal Article Type: Article
• Acceptance Date: Apr 21, 2016
• Online Publication Date: May 19, 2016
• Publication Date: Feb 1, 2017
• Deposit Date: Apr 27, 2016
• Publicly Available Date: May 25, 2016
• Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
• Print ISSN: 1939-1404
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 10
• Issue: 2
• Pages: 763-773
• DOI: https://doi.org/10.1109/JSTARS.2016.2564984
• Keywords: road edges, mobile laser scanning, snake energy, validation approach, complex road, roads, feature extraction, data mining, laser radar, mobile communication, algorithm design and analysis, accidents
• Public URL: https://uwe-repository.worktribe.com/output/911936
• Publisher URL: http://dx.doi.org/10.1109/JSTARS.2016.2564984
• Additional Information: Additional Information : (c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
• Contract Date: Apr 27, 2016