A Hybrid Approach to Parallel Connected Component Labeling Using CUDA
Department of Information and Communication Engineering, Myongji University, Yongin, South Korea
International Journal of Signal Processing Systems, Vol. 1, No. 2, 2013
@article{soh2013hybrid,
title={A Hybrid Approach to Parallel Connected Component Labeling Using CUDA},
author={Soh, Youngsung and Ashraf, Hadi and Hae, Yongsuk and Kim, Intaek},
year={2013}
}
Connected component labeling (CCL) is a mandatory step in image segmentation where each object in an image is identified and uniquely labeled. Sequential CCL is a time-consuming operation and thus is often implemented within parallel processing framework to reduce execution time. Several parallel CCL methods have been proposed in the literature. Among them are NSZ label equivalence (NSZ-LE) method and modified 8 directional label selection (M8DLS) method. It was shown that M8DLS outperforms NSZ-LE and M8DLS is by far the best. In this paper we propose a new parallel CCL algorithm termed as HYBRID1 that hybridizes M8DLS and Kernel C method with some modification and show that it runs faster than M8DLS for various kinds of images.
December 4, 2013 by hgpu
