1. Road Manhole Cover Delineation Using Mobile Laser Scanning Point Cloud Data
- Author
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Dilong Li, Cheng Wang, Jonathan Li, Yongtao Yu, Haiyan Guan, and Chunhua Jin
- Subjects
Computer science ,business.industry ,Feature extraction ,0211 other engineering and technologies ,Point cloud ,02 engineering and technology ,Image segmentation ,Geotechnical Engineering and Engineering Geology ,Kernel (image processing) ,Road surface ,Georeference ,Computer vision ,Artificial intelligence ,Electrical and Electronic Engineering ,business ,Classifier (UML) ,021101 geological & geomatics engineering - Abstract
Periodical road manhole cover measurement is extremely important to ensure road safety and reduce traffic disasters. This letter proposes an effective method for delineating road manhole covers from mobile laser scanning point cloud data. To improve processing efficiency, first, road surface points are segmented and rasterized into georeferenced intensity images. Then, object-oriented patches are generated through superpixel segmentation and further fed to a convolutional capsule network classifier for manhole cover detection. Finally, manhole covers are accurately delineated through a marked point process of disks. Quantitative evaluations on three data sets show that an average completeness, correctness, quality, and ${F} _{1}$ -measure of 0.965, 0.961, 0.929, and 0.963, respectively, are obtained. Comparative studies with three existing methods confirm that the proposed method performs superiorly in delineating manhole covers of varying conditions and on complex road surface environments.
- Published
- 2020
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