Image-mapped data clustering: An efficient technique for clustering large data sets

Abstract

In this paper, we devise a novel algorithm for large data set clustering. Our algorithm utilizes efficient image processing techniques to cluster the data set after mapping its points into a binary image map. To this end, the algorithm avoids exhaustive search by using the mapped image, which contain the critical boundary information needed to detect clusters. Compared to available data clustering techniques, the proposed algorithm produces similar quality results and outperforms them in execution time and storage requirements.