A Novel Two-Scan Connected-Component Labeling Algorithm

  • Lifeng He
  • Yuyan Chao
  • Yun Yang
  • Sihui Li
  • Xiao Zhao
  • Kenji Suzuki
Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 229)

Abstract

This chapter proposes a novel two-scan labeling algorithm. In the first scan, all conventional two-scan labeling algorithms process image lines one by one, assigning each foreground pixel a provisional label, finding and resolving label equivalences between provisional labels. In comparison, our proposed method first scans image lines every four lines, assigns provisional labels to foreground pixels among each three lines, and finds and resolves label equivalences among those provisional labels. Then, it processes the leaving lines from top to bottom one by one, and for each line, assigns provisional labels to foreground pixels on the line, and finds and resolves label equivalences among the provisional labels and those assigned to the foreground pixels on the lines immediately above and below the current line. With our method, the average number of times for checking pixels for processing a foreground pixel will decrease; thus, the efficiency of labeling can be improved. Experimental results demonstrated that our method was more efficient than conventional label-equivalence-based labeling algorithms.

Keywords

Computer vision Connected component Fast algorithm Label equivalence Labeling Pattern recognition 

Notes

Acknowledgments

This work was supported in part by the Ministry of Education, Science, Sports and Culture, Japan, Grant-in-Aid for Scientific Research (C), 23500222, 2011.

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Lifeng He
    • 1
    • 2
  • Yuyan Chao
    • 3
  • Yun Yang
    • 1
  • Sihui Li
    • 1
  • Xiao Zhao
    • 1
  • Kenji Suzuki
    • 4
  1. 1.College of Electrical and Information EngineeringShaanxi University of Science and TechnologyXi’anChina
  2. 2.Faculty of Information Science and TechnologyAichi Profectural UniversityNagakuteJapan
  3. 3.Graduate School of Environment ManagementNagoya Sangyo UniversityOwariasahiJapan
  4. 4.Department of Radiology, Division of the Biological SciencesThe University of ChicagoChicagoUSA

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