MARKOV RANDOM FIELDS (MRF)-BASED TEXTURE SEGMENTATION 
FOR ROAD DETECTION 
Ralf Reulke a , Artur Lippok b 
‘‘Humboldt-University Berlin, Department of Computer Science, Computer Vision 
Unter den Linden 6, 10099 Berlin, Germany - reulke@informatik.hu-berlin.de 
b Hilbertstr. 22a, 12307 Berlin, Germany - lippok@gmx.de 
Commission III, WG III/5 
KEY WORDS: Mapping, Photogrammetry, Vision, Fusion, Identification, Monitoring, Real-time, Platforms 
ABSTRACT: 
Traffic observation from airplane platforms using digital cameras is a fairly new application of Video Image Detection Systems 
(VIDS). These systems are also particularly interesting for observations at major events or in catastrophe situations. Applied systems 
are small or medium-sized panchromatic cameras. In order to concentrate on road image processing algorithms were applied to 
distinguish between urban and surrounding vegetation areas. Therefore, texture-based segmentation seems to be an adequate 
approach, because of the panchromatic images. Attention is focused on MRF, which are examined concerning their use for texture- 
based extraction of street space in aerial photographs. 
KURZFASSUNG: 
Der Einsatz von digitalen Kameras für Verkehrsbeobachtungen von Flugzeugplattformen ist eine relativ neue Anwendung von 
Videodetektionssystemen (VIDS). Diese Systeme sind auch besonders interessant für Überwachungsaufgaben bei 
Großveranstaltungen oder in Katastrophensituationen. Die angewendeten Systeme sind kleine oder mittelgroße panchromatische 
Kameras. Bildverarbeitungsalgorithmen zur Unterscheidung von urbanen und umgebenen Vegetationsgebieten wurden angewendet, 
um die Extraktion von Fahrzeugen lediglich auf den Straßenbereich zu fokussieren. Aufgrund der panchromatischen Bilder erscheint 
die texturbasierte Segmentierung dafür der adäquate Ansatz. Besonderes Augenmerk gilt den MRF, die hinsichtlich ihrer Nutzung 
für texturbasierte Extraktion von Straßenraum in Luftbildern untersucht werden. 
1. INTRODUCTION 
Traffic observation from airplane platforms using digital 
cameras is a new application of Video Image Detection Systems 
(VIDS) as already used for regular traffic observations. 
Monitoring from airplane platforms is also particularly 
interesting for observations at major events or in catastrophe 
situations. An overview of current airborne and spacebome 
monitoring systems and related activities can be found in (Hinz 
et al., 2006). 
The investigations described here, are based on the ANTAR- 
system and the evaluation software “Traffic Finder” developed 
by the German Aerospace Center. The system provides real 
time extraction of traffic data. ANTAR includes a digital mega 
pixel camera and an inertial measurement unit. The acquired 
images are transmitted to the ground and analysed by the 
software to extract cars and their features (Ruhe et al, 2007). 
One essential feature of such a system is the immediate 
knowledge of extracted cars or derived traffic parameters of 
street sections, which can be annotated in digital street maps 
(e.g. made by NAVTEQ). To improve the effectiveness of 
image processing algorithms, irrelevant traffic areas are omitted. 
In the presented example the observation area is defined with 
help of digital street maps in combination with a digital 
elevation model. For that purpose the camera orientation is 
exactly determined. Unfortunately, the precision of roadway 
geometry is restricted because of navigation errors, limited map 
accuracy or map availability. Therefore, the area with occurring 
traffic shall be exactly determined using additional image 
processing algorithms. Utilized camera systems are small or 
medium-sized panchromatic cameras. Image processing is 
restricted to texture-based segmentation approaches due to the 
panchromatic images.. Thus multispectral and colour 
approaches are not applicable. 
Segmentation is a commonly used term for identifying 
differences between particularly interesting and uninteresting 
objects as well as distinguishing foreground from background 
content. In order to identify possibilities for acquisition of scene 
information by digital images an analysis of the principle 
features of these images is required. In this regard, textures are 
the only possibility to derive information from imagery, besides 
the grey or colour values and structural features. For this reason, 
texture analysis methods were used since the beginning of 
digital image processing. There are continuous suggestions for 
new algorithmic approaches to texture-based scene analyses. 
Thereby, also Laws-Energy, Fuzzy- and Fourier approaches are 
analyzed besides first and higher order statistics. 
Road detection is a prerequisite for traffic observation from 
airplane platforms. The paper discusses different approaches to 
texture-based feature extraction and segmentation. Standard 
algorithms are examined first. Caused by the complicated 
observation conditions these methods cannot be used 
successfully. 
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