Meteorite Image Analysis – Team 2
Institution
Arizona State University (Tempe Campus)
Class
Titanium Class (2017 – 2018)
Student Team
Mark Erece, Computer Science
Rameal Nabeeh, Computer Science
Ashwin Nair, Computer Science
Waris Phupaibul, Computer Science
Daniel Schwegel, Computer Science
Academic Guidance
Yitao Chen, Graduate Research Associate, Computing, Informatics, and Decision Systems Engineering
Dr. Ming Zhao, Associate Professor, Computing, Informatics, and Decision Systems Engineering
Project Description
To prepare for scientific investigations at Psyche, meteorite experts from ASU and the Smithsonian Institution seek an imaging system to help determine the bulk chemical compositions of iron meteorites from their optical images. Meteorite experts use their knowledge to recognize the inclusions in meteorites based primarily on color, texture, and reflectivity. A major challenge of this project is to translate this human knowledge to an automated recognition system the can replicate the human expertise. To work towards this goal, students created software to conduct planimetric analysis of images of iron meteorite samples to help determine their bulk chemical compositions. An additional challenge to this project was how to process and store large numbers of very large image files.