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The graph isomorphism problem is a main problem which has numerousapplications in different fields. Thus, finding an efficient and easy toimplement method to discriminate non-isomorphic graphs is valuable. In thispaper, a new method is introduced which is very simple and easy to implement,but very efficient in discriminating non-isomorphic graphs, in practice. Thismethod does not need any heuristic attempt and based on the eigenvalues of anew matrix representation for graphs. It, almost always, separatesnon-isomorphic $n$-vertex graphs in time $O(n^3)$ and in worst cases such asstrongly regular graphs, in time $O(n^4)$. Here, we show that this method,successfully, characterizes the isomorphism classes of studied instances ofstrongly regular graphs (up to 64 vertices). Strongly regular graphs arebelieved to be hard cases of the graph isomorphism problem.

Discrimination of Graph Isomorphism Classes by Continuous Spectrum and Split Technique