Full text: Proceedings International Workshop on Mobile Mapping Technology

AUTOMATIC MEASUREMENT OF ROAD WIDTHS IN COLOUR STEREO SEQUENCES ACQUIRED BY A MOBILE 
MAPPING SYSTEM 
Krzysztof Gajdamowicz 
Inst, of Geodesy and Photogrammetry 
Royal Institute of Technology 
Sweden 
krzygajd@geomatics.kth.se 
Commission II, Working Group 1 
KEY WORDS: road inventory, automatic colour image analysis, colour based segmentation 
ABSTRACT 
In 1995, the Department of Geodesy and Photogrammetry together with the Swedish National Road Administration (SNRA) and the 
Swedish National Board for Industrial and Technical Development (in Swedish: NUTEK) set up a project for the development of 
methods for automatic analysis of the data acquired by Mobile Mapping Systems (MMS). Such methods are planned to be used for fast 
and cost effective data collection for the National Road Data Base (NRDB). 
Colour stereo sequences recorded by MMS are georeferenced and analysed in a post-process to obtain geometric and semantic 
information about roads and objects in their surrounding. This paper presents methods for automatic measurement of road widths from 
colour stereo georeferenced images. It also presents an evaluation of the automatic method for road width measurement in comparison 
with semi-automated. Additionally, this paper discusses the advantages and limitations of the method. Finally, recommendations and 
improvements of the method are presented. 
The automatic measurement of road widths is based on step-wise processing of colour georeferenced stereo sequences. It employs colour 
based segmentation for localisation of the road, image filtering for extraction of road boundaries, image matching for 3D positioning of 
road boundaries and computation of 3D vector between the road boundaries to determine the width of the road. The final results are 
revised and checked for gross errors. If any outliers are found, the measurements are repeated by semi-automatic stereo measurement, 
where for a manually selected point in one stereo image the corresponding point is found by feature based matching in colour space. 
After the matching procedure is completed, the road width is computed in the global co-ordinate frame. 
1 INTRODUCTION 
Inventory of roads and maintenance of the road data is a primary 
task for the Swedish National Road Administration (SNRA). 
Information about the road and road environment needs to be 
acquired and frequently updated. Main attributes in the Road 
Data Bank (RDB) are the nodal points, i.e. road junctions, and 
the distance between them. The position information and the 
attributes of the inventory objects like kerbs, manholes, road 
signs, road widths, etc. are georeferenced using distance from 
road junctions. 
Presently, measurements of the road widths are performed in a 
traditional way using survey tape. Such measurements are time 
consuming and often require interference in a traffic flow. In case 
of very trafficked roads measurement of the road widths requires 
an alternative method. 
One of then! is aerial photogrammetry. Up to now several 
algorithms for automatic road extraction from aerial photographs 
were presented, e.g. Mayer et al. (1998). Unfortunately, these 
methods still require more research and optimisation in order to 
be robust. Moreover, aerial photogrammetry is an expensive 
method that has low repeatability, therefore it is not well suited 
for the purpose of road width measurement. 
The other way to acquire road widths is to use Mobile Mapping 
System (MMS) and digital photogrammetry. MMS like On-Sight 
developed by Transmap Corp. is a system, which integrates GPS, 
INS, odometer and colour digital cameras on a van. Such a 
system allows acquiring stereo georeferenced images of the 
roads while driving with speed up to 80 km/h. Road widths are 
measured in a post-process using georeferenced images and 
stereo photogrammetrical methods. Monotonous image point 
measurement procedure requires automation. Habib (1994) 
described in his thesis an algorithm for automatic extraction and 
matching of the road edges (painted lines) using MMS 
georeferenced images and data association technique. Tao (1996) 
presented an integrated approach to reconstruct centrelines using 
stereo image sequences and MMS trajectory calculated from 
GPS/INS data. Gajdamowicz (1998) presented a semi-automatic 
approach for point and vector measurement and an automatic 
approach for road sign inventory. 
The primary goal of this paper is to present an approach to 
measure road widths automatically. The secondary goal of this 
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