NDLI: Real-time corridor recognition adaptable for shadow and illuminance variation

Content Provider	IEEE Xplore Digital Library
Author	Suzuki, H. Minami, M.
Copyright Year	2002
Abstract	In the fields of ITS and Robotics, recognition of a working environment using a vision system is critical for an autonomous vehicle such as a car controlled automatically and a mobile robot to guide it along corridor and to confirm its possible intelligence. Therefore it is necessary to equip a recognition system with some sensor, such as a CCD camera, which is generally thought to be useful for all kinds of vehicles, and can get environmental information at once. However, it is thought to be hard to use the CCD camera for visual feedback that requires to acquire the information in real-time, and moreover to be robust against lighting condition variations and existence of noises objects including a shadow. This research presents a corridor recognition method using unprocessed gray-scale image, termed here as a raw-image, and a genetic algorithm (GA), without any image information conversion, so as to perform the recognition process in real-time. Furthermore, to achieve robustness concerning lighting condition variations, we propose a model-matching method using a representative object model designated here as surface-strips model. The robustness of the method against noises in the environment, including lighting conditions variations and shadows, and the effectiveness of the method for real-time recognition have been verified using real corridor images.
Starting Page	61
Ending Page	66
File Size	576984
Page Count	6
File Format	PDF
ISBN	0780373898
DOI	10.1109/ITSC.2002.1041189
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-09-06
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mobile robots Noise robustness Image recognition Intelligent robots Robot vision systems Intelligent vehicles Intelligent sensors Charge coupled devices Charge-coupled image sensors Working environment noise
Content Type	Text
Resource Type	Article

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