We describe a system for the automatic quantification of structure in spiral
galaxies. This enables translation of sky survey images into data needed to
help address fundamental astrophysical questions such as the origin of spiral
structure---a phenomenon that has eluded theoretical description despite 150
years of study (Sellwood 2010). The difficulty of automated measurement is
underscored by the fact that, to date, only manual efforts (such as the citizen
science project Galaxy Zoo) have been able to extract information about large
samples of spiral galaxies. An automated approach will be needed to eliminate
measurement subjectivity and handle the otherwise-overwhelming image quantities
(up to billions of images) from near-future surveys. Our approach automatically
describes spiral galaxy structure as a set of arcs, precisely describing spiral
arm segment arrangement while retaining the flexibility needed to accommodate
the observed wide variety of spiral galaxy structure. The largest existing
quantitative measurements were manually-guided and encompassed fewer than 100
galaxies, while we have already applied our method to more than 29,000
galaxies. Our output matches previous information, both quantitatively over
small existing samples, and qualitatively against human classifications from
Galaxy Zoo.Comment: 9 pages;4 figures; 2 tables; accepted to CVPR (Computer Vision and
Pattern Recognition), June 2012, Providence, Rhode Island, June 16-21, 201