Asphalted Road Temperature Variations Due to Wind Turbine Cast Shadows

The contribution of this paper is a technique that in certain circumstances allows one to avoid the removal of dynamic shadows in the visible spectrum making use of images in the infrared spectrum. This technique emerged from a real problem concerning the autonomous navigation of a vehicle in a wind farm. In this environment, the dynamic shadows cast by the wind turbines' blades make it necessary to include a shadows removal stage in the preprocessing of the visible spectrum images in order to avoid the shadows being misclassified as obstacles. In the thermal images, dynamic shadows completely disappear, something that does not always occur in the visible spectrum, even when the preprocessing is executed. Thus, a fusion on thermal and visible bands is performed.

[1]  Sumit Ghosh,et al.  A Study of Synthetic Creativity: Behavior Modeling and Simulation of an Ant Colony , 2000, IEEE Intell. Syst..

[2]  Luis Magdalena,et al.  A Color Vision-Based Lane Tracking System for Autonomous Driving on Unmarked Roads , 2004, Auton. Robots.

[3]  Thomas Stützle,et al.  The Ant Colony Optimization Metaheuristic: Algorithms, Applications, and Advances , 2003 .

[4]  Massimo Bertozzi,et al.  Vision-based intelligent vehicles: State of the art and perspectives , 2000, Robotics Auton. Syst..

[5]  Massimo Bertozzi,et al.  GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection , 1998, IEEE Trans. Image Process..

[6]  Charles E. Thorpe,et al.  UNSCARF-a color vision system for the detection of unstructured roads , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[7]  A. Broggi,et al.  Pedestrian Detection in Far Infrared Images based on the use of Probabilistic Templates , 2007, 2007 IEEE Intelligent Vehicles Symposium.

[8]  Manuel López-Ibáñez,et al.  Ant colony optimization , 2010, GECCO '10.

[9]  J. M. Moore,et al.  Cloud-shadow suppression technique for enhancement of Airborne Thematic Mapper imagery , 1993 .

[10]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[11]  Sebastian Thrun,et al.  Self-supervised Monocular Road Detection in Desert Terrain , 2006, Robotics: Science and Systems.

[12]  Alberto Broggi Robust real-time lane and road detection in critical shadow conditions , 1995, Proceedings of International Symposium on Computer Vision - ISCV.

[13]  J. Deneubourg,et al.  Probabilistic behaviour in ants: A strategy of errors? , 1983 .

[14]  Alberto Broggi,et al.  An agent based evolutionary approach to path detection for off-road vehicle guidance , 2006, Pattern Recognit. Lett..

[15]  Rafael Arnay,et al.  Applying an Ant Colony Optimization Algorithm to an Artificial Vision Problem in a Robotic Vehicle , 2008, DCAI.