A Survey On Outdoor
Water Hazard Detection
Mohammad Iqbal
Olivier Morel
Fabrice Meriaudeau
Agenda
Introduction : Location, Motivation, Water
Appearance, A Variety outdoor Water Hazard
Scene.
Water detection method...
Location
Gunadarma University, Indonesia
Simple Information :
25.000 students and 1000 lecturers
9 campus locations
12 bac...
Location
Université de Bourgogne, France
Simple Information :
27,000 students divided into six
city, Dijon, Auxerre, Chalo...
Motivation
Autonomous off-road navigation is a highly
complicated task for a robot owing to the
different kinds of obstacl...
Water Appearance
Ambient light (day versus night operation)
Scene elements reflected by the surface (sky,
vegetation or bu...
A Variety outdoor
Water Hazard Scene
brighter intensities where the sky
is reflected, darker intensities
where the water i...
Water Detection Method
Color Imagery
Short Wave Infra red (SWIR) Imagery
Thermal Infra red Imagery
Laser Range Finder
Mult...
Color Imagery
Color classification for rippled water
Result :
Color classification for still water
Image Processing : Satu...
Color Imagery
During the day, colour image classification can be
used to recognize water by its reflection of the sky; in
...
Short Wave Infra Red
(SWIR) Imagery
Basic Principal : Analysing image of it deepness Infra red Sensor
As the absorption co...
Short Wave Infra Red
(SWIR) Imagery
Fact from SWIR : Snow and ice have very strong absorption beyond about 1.4
μm therefor...
Thermal Infra red Imagery
Water Appearance from operating
time detection (day or night)
The water bodies tend to be cooler...
Thermal Infra red Imagery
We can use thermal images of water
measures only on the very top layer
of the water surface beca...
Laser Range Finder
A LADAR system works by firing photons
(lasers) at a given object or area, it then
measures the time of...
Laser Range Finder
LADAR has been concluded for detecting water body within short
ranges of shallow water bodies. The visi...
Multi feature based
A lot of scene of water body in outdoor
environment, bring the idea to researchers
to combine various ...
Multi feature based
The multi-cue approach allows each detector to
target different water characteristics.
A certain amoun...
Polarization Imaging based
This technique based on the physical principle
that the light reflected from water surface is p...
Polarization Imaging based
Extraction of polarization imaging information result :
(Binxie, 2007) Degree of Polarization
P...
Classification Scheme
of method water detection
Presentation ICTS 2009
Upcoming SlideShare
Loading in …5
×

Presentation ICTS 2009

505 views

Published on

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
505
On SlideShare
0
From Embeds
0
Number of Embeds
4
Actions
Shares
0
Downloads
8
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Presentation ICTS 2009

  1. 1. A Survey On Outdoor Water Hazard Detection Mohammad Iqbal Olivier Morel Fabrice Meriaudeau
  2. 2. Agenda Introduction : Location, Motivation, Water Appearance, A Variety outdoor Water Hazard Scene. Water detection method : Color Imagery, Short Wave Infra red (SWIR) Imagery, Thermal Infra red Imagery, Laser Range Finder, Multi feature based and Polarization Imaging based Classification Scheme of method water detection
  3. 3. Location Gunadarma University, Indonesia Simple Information : 25.000 students and 1000 lecturers 9 campus locations 12 bachelor , 6 master and 2 PhD programs internal news, radio and TV station Each department of each faculty at Gunadarma University has laboratories that have divisions: Basic, Intermediate and Advance Laboratories. The laboratories are facilities for students as supporting requirment for some subjects that the students receive during the class. www.gunadarma.ac.id
  4. 4. Location Université de Bourgogne, France Simple Information : 27,000 students divided into six city, Dijon, Auxerre, Chalon-sur- Saône, Le Creusot, Mâcon and Nevers. The Humanities and Sciences are well represented on the main campus along with Medicine and Literature in separate buildings. The IUT (Institute of technology) is also on the campus, providing specialist higher level diplomas in Business, Biology, Communications and Computer Science. Lab LE2I IUT (Institut Universitaire de Technologie), Le Creusot webcreusot.u-bourgogne.fr 12, Rue Fonderie 71200 Creusot (Le), France +33 3 85 73 10 00
  5. 5. Motivation Autonomous off-road navigation is a highly complicated task for a robot owing to the different kinds of obstacles it can encounter. Water hazards such as puddles and ponds are very common in the outdoor environment and are hard to detect even with ranging devices such as LADAR as the signal does not get reflected back to the sensor.
  6. 6. Water Appearance Ambient light (day versus night operation) Scene elements reflected by the surface (sky, vegetation or buildings) Width of surface water (a pond versus a lake) Water depth Water turbidity and presence or absence of ripples on the surface or shadow
  7. 7. A Variety outdoor Water Hazard Scene brighter intensities where the sky is reflected, darker intensities where the water is in shadow, and reflections of ground cover that are close and far away. changes in illumination along the body of water and are not clearly distinguished from the surrounding terrain. Image from the DARPA 2004 Grand Challenge media galle Image from Matthies, BelluttaImage from Matthies, Bellutta Big Challenge on Water Detection to formulate a single feature capable of characterizing water under the different scenarios
  8. 8. Water Detection Method Color Imagery Short Wave Infra red (SWIR) Imagery Thermal Infra red Imagery Laser Range Finder Multi feature based Polarization Imaging based
  9. 9. Color Imagery Color classification for rippled water Result : Color classification for still water Image Processing : Saturasi (left), brighness (right) Source : Evaluate the brightness [I = (R+G+B)/3] and color saturation [1- min(R,G,B)/I] of the terrain, water, and sky If [S=0] or [S ≤ 0.27 and B ≥ 0.73] or [sky and S ≤ 0.1 and B > Bmin(S)] or [sky and S ≤ 0.3 and B > Bmin(S) and 240<H<285] The thresholding criteria derived for labeling a pixel a water cue from color S = Saturation, B=Brightness, H=Hue
  10. 10. Color Imagery During the day, colour image classification can be used to recognize water by its reflection of the sky; in off-road, open terrain, this is a fairly reliable, easy-to- compute signature. On the other hand, when still water reflects other aspects of the terrain, such as trees, hills, or buildings, it may be particularly difficult. This method usually combine with texture detection of water. texture quantifies grayscale intensity differences (contrast), a defined area over which differences occur, and directionality, or lack of it (Haralick, 1973). For this water cue, water regions having low texture.
  11. 11. Short Wave Infra Red (SWIR) Imagery Basic Principal : Analysing image of it deepness Infra red Sensor As the absorption coefficient of pure water in the near infrared wavelengths is higher than that in the visible range, water bodies of any appreciable depth will appear very dark in the near infrared imagery. Ability of SWIR cameras with wavelength sensitivity from nearly 0.9 to 1.7 μm
  12. 12. Short Wave Infra Red (SWIR) Imagery Fact from SWIR : Snow and ice have very strong absorption beyond about 1.4 μm therefore the wavelength region around 1.5 μm to 1.6 μm may be useful for recognizing water, snow and ice. Result : The water is very dark at the bottom of the image where it reflects the sky; the angle of incidence at that point is at least 80 degrees. Beyond that, strong reflections of clouds and trees are evident on the water surface. Note that the vegetation all around the reservoir is highly reflective at these wavelengths. SWIR is capable of detecting water at moderate angles of incidence and has the potential to discriminate snow and ice from other terrain materials. But the performance of this technique degrades in regions of water strongly reflecting vegetation or the clouds.
  13. 13. Thermal Infra red Imagery Water Appearance from operating time detection (day or night) The water bodies tend to be cooler than surrounding terrain during the day and warmer at night. The size of water body will be affected to the temperature distribution and smaller bodies equalize temperature quickly while there is significant contrast for larger bodies of water. Moreover, water has a higher emissivity than other terrain materials and hence, improves the contrast during night. Ability of Thermal Camera (Mid-wave IR - MWIR) with wavelength sensitivity from nearly 3.5 to 20 μm Water bodies have a thermal region distribution region around 3 to 5 μm and other gases in the atmosphere restricts aerial systems 8 to 15 μm.
  14. 14. Thermal Infra red Imagery We can use thermal images of water measures only on the very top layer of the water surface because those wavelengths are attenuated/absorbed very rapidly. In the water content, this is will makes confusing results sometimes, unless you know for certain what covers the area you are looking at or have very precise control of the wavelengths sensed by the instrument (which makes in expensive). Most thermal imaging systems have strict technical parameters, for example, detector materials must be kept extremely cold during use (because the emitted radiation being sensed is very weak) Result Water Detection with Thermal IR taken at 3 pm (left) & 4 am (right)
  15. 15. Laser Range Finder A LADAR system works by firing photons (lasers) at a given object or area, it then measures the time of flight of photons (time to reflect back), this enables a CCD style setup to encode each photon as a pixel and produce a 3D image of the object or area. The water bodies can return signals for robot mounted LADAR ranging systems owing to the specular reflection at the air water interface. It has been suggested that some of the LADAR energy penetrates the interface and could even produce a range measurement of the bottom of the water body depending on the angle of incidence LADAR System
  16. 16. Laser Range Finder LADAR has been concluded for detecting water body within short ranges of shallow water bodies. The visible and near infrared LADAR may provide a return value and could be used in detection and depth measurements. Scene elements within certain range (between 6.5 and 11 metres), provide return values could be used to characterise water. Beyond this limit, no return signal is obtained from any object and hence, it is mean not possible to detect water hazards. For detecting the presence of water body, LADAR system need careful installation, depend on time operation (day or night), and the precision angles of incident laser beam to water bodies object.
  17. 17. Multi feature based A lot of scene of water body in outdoor environment, bring the idea to researchers to combine various techniques to detect the water. The technique employs brightness, texture and range reflection features that are fused to detect water hazards. [9] The brightness and texture cues Extracted by common image segmentation methods such as region growing and clustering. Find a parameter the 3D Information Use an NCC (normalized cross correlation criteria) based stereo matching method. Features are fused to detect the water regions in the scene Brightness textures
  18. 18. Multi feature based The multi-cue approach allows each detector to target different water characteristics. A certain amount of false detections from each detector is tolerated by applying fusion rules that are, in part, designed to eliminate false detections. Generally, this technique have a better results than any technique based on a single feature. But, to apply this approach we need found many task to formulating a robust fusing scheme capable of accommodating the different factors influencing the appearance of a water body. This is will increase a computational overhead, hence it will complicate their use in real time applications.
  19. 19. Polarization Imaging based This technique based on the physical principle that the light reflected from water surface is partial linearly polarized and the polarization phases of them are more similar than those from the scenes around. Water hazards can be detected by comparison of polarization degree and similarity of the polarization phases. Two step : I0, I45 and I90 is a representation of intensity image measurements that are taken at 0, 45 and 90 degrees of polarizer lens. 1. Extraction of polarization imaging information
  20. 20. Polarization Imaging based Extraction of polarization imaging information result : (Binxie, 2007) Degree of Polarization Phase of Polarization 2. Segmentation polarization image Degree of Polarization Phase of Polarization self-adaptive threshold segmentation algorithm and a morphology filtering technique to label water region
  21. 21. Classification Scheme of method water detection

×