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Two Efficient Label-Equivalence-Based Connected-Component Labeling Algorithms for 3-D Binary Images
DOI:10.1109/TIP.2011.2114352.png)
摘要
En 中文
Whenever one wants to distinguish, recognize, and/or measure objects (connected components) in binary images, labeling is required. This paper presents two efficient label-equivalence-based connected-component labeling algorithms for 3-D binary images. One is voxel based and the other is run based. For the voxel-based one, we present an efficient method of deciding the order for checking voxels in the mask. For the run-based one, instead of assigning each foreground voxel, we assign each run a provisional label. Moreover, we use run data to label foreground voxels without scanning any background voxel in the second scan. Experimental results have demonstrated that our voxel-based algorithm is efficient for 3-D binary images with complicated connected components, that our run-based one is efficient for those with simple connected components, and that both are much more efficient than conventional 3-D labeling algorithms.
Keyword:
Connected component
label equivalence
labeling algorithm
run
3-D binary image
期刊
IF:
13.7
论文数:
1.0W
被引数:
8.4W
机构
引用论文
Mixture of expert 3D massive-training ANNs for reduction of multiple types of false positives in CAD for detection of polyps in CT colonography
MEDICAL PHYSICS
IF3.2

