Eldin, Neil N.2018-03-022018-03-02December 22014-12December 2http://hdl.handle.net/10657/2750Offshore pipelines are vital infrastructure systems for oil and gas transportation. Statistics around the globe confirm that third-party threats, such as vessel anchoring, fishing, and offshore construction, contribute the most to offshore pipeline damages and are the number one cause of death, injury, and pollution. This research studies satellite imagery and its application in automating vessel detection for the purpose of offshore pipeline protection. Current methods of relying on high-resolution satellite images lead to a high implementation cost and less efficient image processing. This paper proposes a method of utilizing lower resolution satellite images for vessel detection in offshore pipeline safety zones. It applies a combination of cascade classifier and color segmentation method as well as a unique “color-coding” scheme to achieve an accurate and efficient satellite image processing procedure. The proposed method was tested on 150 Google Earth satellite images with an average detection rate of 94% for large and medium vessels and an average false alarm rate of 19%.application/pdfengThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).Image processingOffshorePipelinesSafetyVessel detection2018-03-02Thesisborn digital