Computer vision for corrosion detection

People

Principal investigator

Research areas

Description

Engineered products from cars, planes, bridges and buildings, are comprised of materials that have been crafted by humans. Inotherwords, we put a heck of a lot of energy into metal production, only to have nature want the energy back, and causing metals to corrode. Corrosion costs the world over a trillion dollars a year (and rising), which is more than the whole GDP of Australia. In order to better protect against the impact of corrosion, and to also revolutionise its detection, computer vision can play an important role. In this project, the use of IBM WatsonTM for corrosion detection (from images) will be explored.

Goals

To produce a classifier and detector that will allow the community to further advance its utilisation of computer vision for good.

Requirements

Ability to code (even if very elementary skills) would be beneficial.

An interest to learn Python.

Passion for data science.

Keywords

computer vision, machine learning, AI, data science, corrosion, fun, rust

Updated:  1 June 2019/Responsible Officer:  Dean, CECS/Page Contact:  CECS Marketing