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Spatial-Related Traffic Sign Inspection for Inventory Purposes Using Mobile
Laser Scanning Data
Abstract:
This paper presents a spatial-related traffic sign inspection process for sign type,
position, and placement using mobile laser scanning (MLS) data acquired by a
RIEGL VMX-450 system and presents its potential for traffic sign inventory
applications. First, the paper describes an algorithm for traffic sign detection in
complicated road scenes based on the retroreflectivity properties of traffic signs
in MLS point clouds. Then, a point cloud-to-image registration process is proposed
to project the traffic sign point clouds onto a 2-D image plane. Third, based on the
extracted traffic sign points, we propose a traffic sign position and placement
inspection process by creating geospatial relations between the traffic signs and
road environment. For further inventory applications, we acquire several spatial-
related inventory measurements. Finally, a traffic sign recognition process is
conducted to assign sign type. With the acquired sign type, position, and
placement data, a spatial-associated sign network is built. Experimental results
indicate satisfactory performance of the proposed detection, recognition,
position, and placement inspection algorithms. The experimental results also
prove the potential of MLS data for automatic traffic sign inventory applications.

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Spatial related traffic sign inspection for inventory purposes using mobile laser scanning data

  • 1. Spatial-Related Traffic Sign Inspection for Inventory Purposes Using Mobile Laser Scanning Data Abstract: This paper presents a spatial-related traffic sign inspection process for sign type, position, and placement using mobile laser scanning (MLS) data acquired by a RIEGL VMX-450 system and presents its potential for traffic sign inventory applications. First, the paper describes an algorithm for traffic sign detection in complicated road scenes based on the retroreflectivity properties of traffic signs in MLS point clouds. Then, a point cloud-to-image registration process is proposed to project the traffic sign point clouds onto a 2-D image plane. Third, based on the extracted traffic sign points, we propose a traffic sign position and placement inspection process by creating geospatial relations between the traffic signs and road environment. For further inventory applications, we acquire several spatial- related inventory measurements. Finally, a traffic sign recognition process is conducted to assign sign type. With the acquired sign type, position, and placement data, a spatial-associated sign network is built. Experimental results indicate satisfactory performance of the proposed detection, recognition, position, and placement inspection algorithms. The experimental results also prove the potential of MLS data for automatic traffic sign inventory applications.