关键词: GPU加速, 连通域标记, 并行化, 统一计算设备架构, 8邻域

Abstract: In combination of NVIDIA's Graphics Processing Unit (GPU) parallel architecture and hardware features under Compute Unified Device Architecture (CUDA) architecture, a new parallel labeling algorithm of connected domain was proposed for binary images. It effectively located the connected domain of the binary image and recorded its size at high speed, and significantly reduced the marking time. It recognized the connected domain through searching the minimum labeled pixel value in neighborhood. Because the processing sequence of each pixel is not in particular order and independent from each other, it can be dealt in parallel. The calculation efficiency of the algorithm is independent of the shapes and the quantity of the connected regions, and the algorithm has good robustness. The experimental results show that the algorithm fully plays the parallel processing capability of GPU, and can get a more than 300 times speedup than general algorithm based on CPU and 17 times speedup than OpenCV function (CPU) in processing high-resolution images and multi-connected-domain images.

Key words: GPU acceleration, connected-domain labeling, parallelization, Compute Unified Device Architecture (CUDA), 8-neighborhood