Spectral Partitioning and its Application to Image Segmentation

The properties of graphs can be studied via the algebraic characteristics of its adjacency or Laplacian matrix. The second eigenvector of the graph Laplacian is one very useful tool which provides information as to how to partition a graph. In this thesis, we study spectral clustering and how to apply it in solving the image segmentation problem in computer vision.