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Automatic Individual Detection and Separation of Multiple Overlapped Nematode Worms Using Skeleton Analysis

  • Nikzad Babaii Rizvandi
  • Aleksandra Pižurica
  • Wilfried Philips
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5112)

Abstract

We present a new method for detection and separation of individual nematode worms in a still image. After pre-processing stage, which includes image binarization, filling the small holes, obtaining the skeleton of the new image and pruning the extra branches of skeleton, we split a skeleton into several branches by eliminating the connection pixels (pixels with more than 2 neighbors). Then we compute angles of all branches and compare the angles of the neighboring branches. The neighbor branches with angle differences less than a threshold are connected. Our method has been applied to a database of 54 overlap worms and results in 82% accuracy as automatic and 89% as semi-automatic with some limited user interaction.

Keywords

Overlap worms Worm detection Skeleton angle analysis Image processing Computer vision 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Nikzad Babaii Rizvandi
    • 1
  • Aleksandra Pižurica
    • 1
  • Wilfried Philips
    • 1
  1. 1.Image Processing and Interpretation Group (IPI), Department of Telecommunications and Information Processing (TELIN)Ghent UniversityGentBelgium

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