GPU Implementation of a Region Based Algorithm for Large Images Segmentation

Image segmentation is one of the most challenging issues in image computing. In this work, we focus on region-based active contour techniques (snakes) as they seem to achieve a high level of robustness and fit with a large range of applications. Some algorithmic optimizations provide significant speedups, but even so, execution times are still non-neglectable with the continuing increase of image sizes. Moreover, these algorithms are not well suited for running on multi-core CPU´s. At the same time, recent developments of Graphical Processing Units (GPU) suggest that higher speedups could be obtained by use of their specific design. We have managed to adapt a specially efficient snake algorithm that fits recent Nvidia GPU architecture and takes advantage of its massive multi-threaded execution capabilities. The speedup obtained is most often around 7.