  This work identifies the orientation of galaxies in the Galaxy zoo data set.
The images are first identified by the number of principal components required
to represent 99 percent of the variance of the image. K means clustering is
used to separate the galaxies on the basis of their central brightness along
with outlier separation. Spectral clustering is then used to separate
circularly symmetric galaxies and the remaining galaxies are identified
according to their orientation as flat , left and right on the basis of the
alignment of the main axis. It is also seen that spectral clustering fails to
make this classification when the galaxy images are noisy and works only when
applied on a smaller subset of the total number of images in the Galaxy zoo
data set. This method also fails in the presence of multiple galaxies in the
image, considering them as an individual entity.
