Poster Presentation

Pattern Recognition Algorithms for Searching Merging Galaxies

Tse-Lin Lee (IANCU) and Chorng-Yuan Hwang (IANCU)

We present a pattern recognition method for rapidly searching possible merging galaxies from large astronomical surveys. Galaxy mergers usually have complex structures and might exhibit irregular shapes. Therefore, we develop algorithms to identify abnormal patterns appearing in images as merger candidates for visual verification. We apply our algorithms on real survey images selected from the Red Sequence Cluster Survey 2 to evaluate the efficiency and applicability. We also run a test on a set of visual identified merging galaxies that were provided by the Galaxy Zoo project for comparison. The results show that our approach can efficiently cut down the time and manpower consumption on searching for merging galaxies in large astronomical surveys.