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ISPRS Int. J. Geo-Inf. 2016, 5(7), 125; doi:10.3390/ijgi5070125

Recognition and Reconstruction of Zebra Crossings on Roads from Mobile Laser Scanning Data

1,2,3
,
1,4,* , 1,3,* and 1
1
School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China
2
Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China
3
The Key Laboratory for Geographical Information System, Ministry of Education, Wuhan 430079, China
4
Power China Zhongnan Engineering Corporation Limited, Changsha 410014, China
*
Authors to whom correspondence should be addressed.
Academic Editor: Wolfgang Kainz
Received: 16 May 2016 / Revised: 3 July 2016 / Accepted: 8 July 2016 / Published: 19 July 2016
View Full-Text   |   Download PDF [6643 KB, uploaded 19 July 2016]   |  

Abstract

Zebra crossings provide guidance and warning to pedestrians and drivers, thereby playing an important role in traffic safety management. Most previous studies have focused on detecting zebra stripes but have not provided full information about the areas, which is critical to both driver assistance systems and guide systems for blind individuals. This paper presents a stepwise procedure for recognizing and reconstructing zebra crossings using mobile laser scanning data. First, we propose adaptive thresholding based on road surface partitioning to reduce the impact of intensity unevenness and improve the accuracy of road marking extraction. Then, dispersion degree filtering is used to reduce the noise. Finally, zebra stripes are recognized according to the rectangular feature and fixed size, which is followed by area reconstruction according to arrangement patterns. We test our method on three datasets captured by an Optech Lynx mobile mapping system. The total recognition rate of 90.91% demonstrates the effectiveness of the method. View Full-Text
Keywords: mobile laser scanning data; zebra crossings; adaptive thresholding; principle component analysis mobile laser scanning data; zebra crossings; adaptive thresholding; principle component analysis
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Li, L.; Zhang, D.; Ying, S.; Li, Y. Recognition and Reconstruction of Zebra Crossings on Roads from Mobile Laser Scanning Data. ISPRS Int. J. Geo-Inf. 2016, 5, 125.

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