TY - JOUR

T1 - A "group marching cube" (GMC) algorithm for speeding up the marching cube algorithm

AU - Chen, Lih Shyang

AU - Lay, Young Jinn

AU - Huang, Je Bin

AU - Chen, Yan De

AU - Chang, Ku Yaw

AU - Chen, Shao Jer

N1 - Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.

PY - 2011/6

Y1 - 2011/6

N2 - Although theMarching Cube (MC) algorithm is very popular for displaying images of voxel-based objects, its slow surface extraction process is usually considered to be one of its major disadvantages. It was pointed out that for the original MC algorithm, we can limit vertex calculations to once per vertex to speed up the surface extraction process, however, it did not mention how this process could be done efficiently. Neither was the reuse of these MC vertices looked into seriously in the literature. In this paper, we propose a "Group Marching Cube" (GMC) algorithm, to reduce the time needed for the vertex identification process, which is part of the surface extraction process. Since most of the triangle-vertices of an isosurface are shared by many MC triangles, the vertex identification process can avoid the duplication of the vertices in the vertex array of the resultant triangle data. The MC algorithm is usually done through a hash table mechanism proposed in the literature and used by many software systems. Our proposed GMC algorithm considers a group of voxels simultaneously for the application of the MC algorithm to explore interesting features of the original MC algorithm that have not been discussed in the literature. Based on our experiments, for an object with more than 1 million vertices, the GMC algorithm is 3 to more than 10 times faster than the algorithm using a hash table. Another significant advantage of GMC is its compatibility with other algorithms that accelerate theMC algorithm. Together, the overall performance of the originalMC algorithm is promoted even further.

AB - Although theMarching Cube (MC) algorithm is very popular for displaying images of voxel-based objects, its slow surface extraction process is usually considered to be one of its major disadvantages. It was pointed out that for the original MC algorithm, we can limit vertex calculations to once per vertex to speed up the surface extraction process, however, it did not mention how this process could be done efficiently. Neither was the reuse of these MC vertices looked into seriously in the literature. In this paper, we propose a "Group Marching Cube" (GMC) algorithm, to reduce the time needed for the vertex identification process, which is part of the surface extraction process. Since most of the triangle-vertices of an isosurface are shared by many MC triangles, the vertex identification process can avoid the duplication of the vertices in the vertex array of the resultant triangle data. The MC algorithm is usually done through a hash table mechanism proposed in the literature and used by many software systems. Our proposed GMC algorithm considers a group of voxels simultaneously for the application of the MC algorithm to explore interesting features of the original MC algorithm that have not been discussed in the literature. Based on our experiments, for an object with more than 1 million vertices, the GMC algorithm is 3 to more than 10 times faster than the algorithm using a hash table. Another significant advantage of GMC is its compatibility with other algorithms that accelerate theMC algorithm. Together, the overall performance of the originalMC algorithm is promoted even further.

UR - http://www.scopus.com/inward/record.url?scp=79957943936&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79957943936&partnerID=8YFLogxK

U2 - 10.1587/transinf.E94.D.1289

DO - 10.1587/transinf.E94.D.1289

M3 - Article

AN - SCOPUS:79957943936

VL - E94-D

SP - 1289

EP - 1298

JO - IEICE Transactions on Information and Systems

JF - IEICE Transactions on Information and Systems

SN - 0916-8532

IS - 6

ER -