Iron Meteorite Imaging System – Scanner
Institution
Arizona State University (Tempe Campus)
Class
Titanium Class (2017-2018)
Student Team
Malik Abduljabbar, Computer Systems Engineering
Noor Aboud, Computer Systems Engineering
Tim Brennan, Engineering Management
Robert Logan, Computer Systems Engineering
Kiran Suresh, Computer Systems Engineering
Rachael Tjahjo, Computer Systems Engineering
Xunkai Wang, Industrial Design
Scientific & Technical Guidance
Dr. Laurence Garvie, Research Professor, ASU Center for Meteorite Studies
Dr. Tim McCoy, Curator-in-Charge, US National Meteorite Collection, Smithsonian National Museum of Natural History
Academic Guidance
Prof. Dean Bacalzo, Assistant Professor, ASU Design School
Dr. Daniel McCarville, Professor of Practice, ASU Computing, Informatics, and Decision Systems Engineering
Dr. Ryan Meuth, Lecturer, Computing, Informatics, and Decision Systems Engineering
Masudul Quraishi, Graduate Assistant, 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, this team designed and built a prototype imaging system based on a scanner to image meteorite samples so that each image has the exact same lighting and image quality.