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Automated Pipeline Corrosion Assessment

Current industry practice for monitoring internal pipeline corrosion is to visually compare the most recent radiographic image of a pipeline to previous radiographic images from the same location. To improve the inspection quality and efficiency, this project aims to create an application that automates the detection and assessment of internal pipeline corrosion. Through image processing techniques, the final application automates the existing inspection process.

Team Members: 

Enrique Callado

Kendal Clovis

Aaron Li

Nick Pacheco