An important approach for image segmentation is clustering the pixels based on their spectral properties. In this paper, a newly developed point symmetry distance is used to propose a new cluster validity index named S-index (Symmetry distance based index) which can provide a measure of goodness of clustering on different partitions of a data set. We have used one genetic clustering algorithm for partitioning the data set. Results demonstrating the superiority of the S-index in appropriately determining the number of clusters as compared to two other recently proposed measures, namely the PS index and PBM index, are provided for automatically classifying different landcover regions in remote sensing imagery.