The aim of our research is to combine the conventional clustering algorithms based on rough sets and fuzzy sets with metaheuristics like firefly algorithm and fuzzy firefly algorithm. Image segmentation is carried out using the resultant hybrid clustering algorithms. The performance of the proposed algorithms is compared with numerous contemporary clustering algorithms and their firefly fused counter-parts. We further bolster the performance of our proposed algorithm my using Gaussian kernel in place of the traditional Euclidean distance measure. We test the performance of our algorithms using two performance indices, namely DB (Davis Bouldin) indexand Dunn index. Our experimental results highlight the advantages of using metaheuristics and kernels over the existing clustering algorithms. © 2018, Springer Nature Singapore Pte Ltd.