To match point-sets reliably, an algorithm for point pattern matching based on spectral graph theory and the analysis of geometric consistency is presented. The cost of spectral correspondences between the matched point-sets is obtained by means of eigenvectors of Laplacian matrix. An object function with hybrid form is defined by incorporating geometric consistency represented by neighborhood relationship. The given object function is solved by utilizing iterative relaxation method. Comparative experiments applied to synthetic data and real-world images demonstrate the proposed method possesses better precision and time performance.