Connected component labeling on a 2D grid using CUDA

Connected component labeling is an important but computationally expensive operation required in many fields of research. The goal in the present work is to label connected components on a 2D binary map. Two different iterative algorithms for doing this task are presented. The first algorithm (Row–Col Unify) is based upon the directional propagation labeling, whereas the second algorithm uses the Label Equivalence technique. The Row–Col Unify algorithm uses a local array of references and the reduction technique intrinsically. The usage of shared memory extensively makes the code efficient. The Label Equivalence algorithm is an extended version of the one presented by Hawick et al. (2010) [3]. At the end the comparison depending on the performances of both of the algorithms is presented.

Research highlights
► CUDA implementation of connected component labeling requires hardware optimisation.
► Optimised directional propagation labeling algorithm uses shared memory and reduction.
► Label Equivalence algorithm is simple, fast and extensible.