A Novel Method for Improving the Voxel-Pattern-Based Euler Number Computing Algorithm of 3D Binary Images

Bin Yao, Dianzhi Han, Shiying Kang, Yuyan Chao, Lifeng He

Abstract: As an important topological property of a 3D binary image, the Euler number can be calculated by counting certain 2  ×  2  ×  2 voxel patterns in the image. This paper presents a novel method for improving the voxel-pattern-based Euler number computing algorithm of 3D binary images. In the proposed method, by changing the accessing order of voxels in 2 ×  2 × 2 voxel patterns and combining the voxel patterns which provide the same Euler number increments for the given image, the average numbers of voxels to be accessed for processing a 2 × 2 × 2 voxel pattern can be decreased from 8 to 4.25, which will lead to an efficient processing. Experimental results demonstrated that the proposed method is much more efficient than the conventional voxel-pattern-based Euler number computing algorithm.