We have created a method for the efficient and automatic extraction of structure from images of spiral galaxies. In particular, we can isolate ”spiral arm segments” by clustering pixels together based on arm segment membership. We can then automatically and objectively extract specific properties of spiral arm segments such as total luminosity, pitch angle (aka winding tightness), and length. This allows us to extract more global properties such as average pitch angle of the arms in a galaxy, winding direction, and existence of bars and rings. As far as we are aware this is a first. Comparisons with the Galaxy Zoo project (human-based classifications) indicate that we agree with humans on the winding direction of the arms at about the same level as humans agree with each other (more than 95the time). The information that we extract may allow us to answer such interesting questions as how structure evolves with the age of the universe, how structure depends on the local environment in which a galaxy resides, and how its structure changes as a function of the wavelength in which it is observed. The project has already garnered much interest and collaborations with astronomers.