Configuration-Transition-Based Connected-Component Labeling

被引:46
|
作者
He, Lifeng [1 ,2 ]
Zhao, Xiao [1 ]
Chao, Yuyan [3 ,4 ]
Suzuki, Kenji [5 ]
机构
[1] Shaanxi Univ Sci & Technol, Coll Elect & Informat Engn, Artificial Intelligence Inst, Xian 710021, Peoples R China
[2] Aichi Prefectural Univ, Fac Informat Sci & Technol, Nagakute, Aichi 4801198, Japan
[3] Nagoya Sangyo Univ, Grad Sch Environm Management, Nagoya, Aichi 4888711, Japan
[4] Shaanxi Univ Sci & Technol, Coll Mech & Elect Engn, Xian 710021, Peoples R China
[5] Univ Chicago, Dept Radiol, Div Biol Sci, Chicago, IL 60637 USA
关键词
Pattern recognition; image analysis; connected component; labeling;
D O I
10.1109/TIP.2013.2289968
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes a new approach to label-equivalence-based two-scan connected-component labeling. We use two strategies to reduce repeated checking-pixel work for labeling. The first is that instead of scanning image lines one by one and processing pixels one by one as in most conventional two-scan labeling algorithms, we scan image lines alternate lines, and process pixels two by two. The second is that by considering the transition of the configuration of pixels in the mask, we utilize the information detected in processing the last two pixels as much as possible for processing the current two pixels. With our method, any pixel checked in the mask when processing the current two pixels will not be checked again when the next two pixels are processed; thus, the efficiency of labeling can be improved. Experimental results demonstrated that our method was more efficient than all conventional labeling algorithms.
引用
收藏
页码:943 / 951
页数:9
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