Date of Award

Summer 2008

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Electrical & Computer Engineering

Program/Concentration

Electrical Engineering

Committee Director

Zia-ur Rahman

Committee Member

Vijayan K. Asari

Committee Member

Jiang Li

Call Number for Print

Special Collections LD4331.E55 T355 2008

Abstract

Fog and other such weather conditions hamper the visibility of runway surfaces and any obstacles present on the runway, creating a situation where a pilot may not be able to safely land the aircraft. Assisting the pilot to land the aircraft safely in such conditions is an active area of research. A new method is being investigated that combines non-linear image enhancement with classification of runway edges to detect objects on the runway. The image is segmented into runway and non-runway regions, and objects that are found in the runway regions are deemed to constitute potential hazards. For runway edge classification, long, continuous edges in the image stream are used. This thesis describes a new method for edge-detection that is robust to the imaging conditions under which the imagery is acquired. This edge-detection method extracts edges using a locally adaptive threshold for the detection. The proposed algorithm is evaluated qualitatively and quantitatively on different types of images, especially acquired under poor visibility conditions. Additionally the results of our new algorithm are compared with other, more conventional edge detectors.

Rights

In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).

DOI

10.25777/49fv-f194

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