Introduction to spectral clustering

Spectral clustering methods are based on graph and matrix theories. Their principle is simple: given some data inputs, build similarity matrix, analyse the spectrum of its Laplacian matrix, and often get a perfect clustering from the eigenvectors analysis. This paper presents an introduction to spectral clustering methods and some applications in signal and image segmentation.