Towards Night Fog Detection
through use of
In-Vehicle Multipurpose Cameras
Romain Gallen
Aurélien Cord
Nicolas Hautière
Didier Aubert
Atmospheric Characterization with
in-vehicle Multipurpose Cameras
• Triple goal
[Hautiere06]
– Driving assistance systems
(lighting, wipers)
– Fiabilize other ADAS based
on cameras
– Functionality used as input
in intelligent speed
adaptation systems
• Previous works on :
– Rain detection
– Day fog detection
• Almost nothing about
Night fog
[Cord11]
A. Cord and D. Aubert, Towards Rain Detection through Use of In-Vehicle Multipurpose Cameras, IV’2011 (Poster session on Wednesday)
N. Hautière, J.-P. Tarel, J. Lavenant, and D. Aubert, Automatic fog detection and estimation of visibility distance through use of an onboard
camera, Machine Vision and Applications, vol. 17, no. 1, pp. 8–20, 2006.
2/11
Embedded Night Fog Detection
3/11
• Two distinct phenomenons that are not observable at the
same time (due to the classical camera settings) :
Road is lit by car own
lighting system
Multiple light sources
in the environment
R. Gallen, A. Cord, N. Hautière et D. Aubert, Procédé et dispositif de détection de brouillard, la nuit, Brevet Français n°1057802, Sept. 2010.
Back Scattered Veil Detection (1/5)
• Perceptible back scattered veil
• Previous works
[Leleve06]
[Kawasaki08]
J. Leleve, A. Bensrhair, , and J. Rebut, Method for detecting night fog and system implementing said method, Patent EP1 715 456, 10-2006.
N. Kawasaki, T. Miyahara, and Y. Tamatsu, Visibility condition determining device for vehicle, Patent 20 080 007 429, 01-2008.
4/11
Back Scattered Veil Detection (2/5)
• Experiments
• conducted in a fog
chamber at the LRPC,
Clermont-Ferrand, France
• 30 m deep, 2.7 m high
• Monitored Fog
• Software simulation
• Semi Monte Carlo ray
tracing
• Photorealistic scenes
• PROF-LCPC Software
5/11
6/11
Back scattered veil detection (3/5)
• Experiments
Image of in-vehicle camera
• Correlation
between real
images and
synthetic images
• Software simulation
Synthetic image
Correlation mask
Back Scattered Veil Detection (4/5)
7/11
Zero mean Normalized Sum of
Squared Differences Correlation
Meteorological Visibility
Back Scattered Veil Detection (5/5)
• Conclusion :
•Detection and characterization of night fog.
•Simple, adaptable, real time.
•Possibility to use a mean image
Raw image
Mean image
•How to manage in presence of light
sources in the environment ?
7/11
Detection of halos around light sources (1/3)
• Hypothesis :
– halos are present around
light sources
– intensity decrease as the
distance from the source
increases
– Sources unknown
– Automatic camera
settings
8/11
Detection of halos around light sources (1/3)
Algorithm for halo detection around light sources
Features analysed :
- Surface
- Gravity center
- Compacity (surface/perimeter)
- Elongation
8/11
Detection of halos around light sources (1/3)
Regions that appear at intermediate thresholds
are not added to the tree
8/11
Detection of halos around light sources (1/3)
8/11
Detection of halos around light sources (1/3)
Selection is made according to size, shape and lenght of branch criterions
8/11
Detection of halos around light sources (1/3)
Selection of interesting light sources
8/11
Detection of halos around light sources (2/3)
• Extraction of
the intensity
profile of light
sources
• The slope of
the profile is
relevant
regarding the
presence of
fog
9/11
Detection of halos around light sources (3/3)
• Detection
based on a
single frame
~ 98% of good
detection
results
• Fiabilized by
a detection
based on
consecutive
frames
10/11
Conclusion
• Method allowing for fog detection with a dual algorithm
• with standard camera
• using automatic exposure settings
• Real time implemented and tested algorithms
• Preserves the usual working state of other camera based
ADAS
• May be combined in order to improve
• Driver/car orientated ADAS (adaptive lighting
systems, future vision enhancement systems in fog)
• Safety orientated ADAS (Preemptive driver
information, Intelligent Speed Adaptation in fog)
• System orientated ADAS (detection of working
state, improvement of camera based ADAS
through image restoration)
11/11