3D Block-Based Medial Axis Transform and Chessboard Distance Transform on the CREW PRAM

Authors:
Shih-Ying Lin;Shi-Jinn Horng;Tzong-Wann Kao;Chin-Shyurng Fahn;Pingzhi Fan;Cheng-Ling Lee;Anu Bourgeois
Affiliations:
Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan;Institute of Mobile Communications, Southwest Jiaotong University, Chengdu, 610031 and Department of Computer Science and Information Engineering, National Taiwan University of Science and Technol ...;Department of Electronic Engineering, Technology and Science Institute of Northern Taiwan, Taipei, Taiwan;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan;Institute of Mobile Communications, Southwest Jiaotong University, Chengdu, 610031;Department of Electro-Optical Engineering, National United University, Miaoli, Taiwan;Department of Computer Science, Georgia State University, Atlanta, GA 30302-4110
Venue:
ICA3PP '08 Proceedings of the 8th international conference on Algorithms and Architectures for Parallel Processing
Year:
2008

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Abstract

Traditionally, the block-based medial axis transform (BB-MAT) and the chessboard distance transform (CDT) were usually viewed as two completely different image computation problems, especially for three dimensional (3D) space. We achieve the computation of the 3D CDT problem by implementing the 3D BB-MAT algorithm first. For a 3D binary image of size N3, our parallel algorithm can be run in O(logN) time using N3processors on the concurrent read exclusive write (CREW) parallel random access machine (PRAM) model to solve both 3D BB-MAT and 3D CDT problems, respectively. In addition, we have implemented a message passing interface (MPI) program on an AMD Opteron Model 270 cluster system to verify the proposed parallel algorithm, since the PRAM model is not available in the real world. The experimental results show that the speedup is saturated when the number of processors used is more than four, regardless of the problem size.