Title :
GPU-Accelerated Parallel 3D Image Thinning
Author :
Bingfeng Hu ; Xuan Yang
Author_Institution :
Coll. of Comput. Sci. & Software Eng., Shenzhen Univ., Shenzhen, China
Abstract :
The skeletons of the objects in 3D images can be extracted by using 3D image thinning. The application of 3D image thinning for image analysis is hampered by its considerable computation time. By employing the graphics processing unit (GPU), which has tremendous powerful computing power at an incomparable performance-to-cost ratio, the calculation of 3D image thinning can be accelerated. In this paper, we proposed a parallel implementation approach on GPU for the 3D 12-subiteration image thinning algorithm, in which object voxels of 3D image are assigned to threads based on the characteristic of sparse 3D image data. The performance of our approach is analyzed with different image sizes, the ratio of object voxels and the number of thread grids on GPU. The performance of the traditional threads assignment strategy and new threads assignment strategy are compared to show that the proposed approach is more efficient.
Keywords :
graphics processing units; image thinning; parallel processing; 3D 12-subiteration image thinning algorithm; GPU-accelerated parallel 3D image thinning; graphics processing unit; image analysis; object skeleton extraction; object voxels; parallel implementation approach; performance-to-cost ratio; sparse 3D image data; thread grids; threads assignment strategy; Arrays; Graphics processing units; Instruction sets; Kernel; Parallel processing; Shape; Three-dimensional displays; 3D image thinning; GPU; Parallel algorithm;
Conference_Titel :
High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing (HPCC_EUC), 2013 IEEE 10th International Conference on
Conference_Location :
Zhangjiajie
DOI :
10.1109/HPCC.and.EUC.2013.30