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

Amin Dharamsi

Call Number for Print

Special Collections LD4331.E55 R43 2008

Abstract

Aircrafts of the future now face the challenge of growing demand for safety which will require a more significant level of pilot assistance than is available today. During an approach to the airport runway, an algorithm that continuously segments the runway from the rest of the background with very little human intervention is very useful for both enhancing the landing safety and reducing the pilot's work load. This thesis presents a novel method for segmenting airport runways on a clear day and in poor visibility conditions using the color space components. In this thesis, collages were formed for both runway (foreground) and non-runway (background) image classes that were collected for the clear case, and additional samples were collected for the poor visibility case to generate a histogram and statistics. The histogram gray level thresholds extracted from each color space component for the foreground and background classes were used to obtain threshold values for runway segmentation. The segmentation was further refined based on the ratios of the components of the color space. Finally, Multi-Scale Retinex (MSR) was performed on runway images under poor visibility conditions. The MSR provides improved contrast and color constancy that is needed to enhance images with poor visibility, by performing non-linear spatial/spectral transforms. After enhancement, the procedure was repeated with a different histogram-threshold and ratio values for all color spaces resulting in a well segmented runway.

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DOI

10.25776/z7vs-7j41

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