Lattice Boltzmann Anisotropic Diffusion Model Based Image Segmentation

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 107)

Abstract

This chapter introduces a new method of image segmentation based on Lattice Boltzmann Anisotropic Diffusion Model (LBADM). Anisotropic diffusion model is build by the membrane media. Active contour model is simulated by thermal diffusion equation, and the heat field is established. Then, by the LBADM it can be obtain the edge of object segmentation. The experiment and discussion is showed that our algorithm can accurately solve the convection–diffusion equation. It can obtain closed curves and deal with topology changes well. Contrasting with the level set method and narrowband level set method for computing speed,the result of the experiment is confirmed that the algorithm greatly reduces the computation of segmentation.

Keywords

Image segmentation Cellular automata Lattice Boltzmann model Anisotropic diffusion Membrane media 

Notes

Acknowledgments

The authors appreciate the support provided by Scientific Research Foundation for Young Teacher Project of Suzhou Vocational University.

References

  1. 1.
    Gastaud M, Barlaud M, Aubert G (2004) Combining shape prior and statistical features for active contour segmentation[C]. IEEE Trans Circuits Sys Video Technol 14(5):726–734 Special session on audio and video analysis for interactive multimedia servicesCrossRefGoogle Scholar
  2. 2.
    Parker BJ, Feng DG (2005) Graph-based Mumford-Shah segmentation of dynamic PET with application to input function estimation [C]. IEEE Trans Nucl Sci 52(1):79–89CrossRefGoogle Scholar
  3. 3.
    Mitiche A, Sekkati H (2006) Optical flow 3D segmentation and interpretation: a variational method with active curve evolution and level sets [C]. IEEE Trans Pattern Anal Mach Intell 28(11):1818–1829CrossRefGoogle Scholar
  4. 4.
    Yuan WF, Tan KH (2007) An evacuation model using cellular automata[J]. Phys a Stat Mech Appl 384(2):549–566CrossRefGoogle Scholar
  5. 5.
    Yue H, Hao H, Chen X, Shao C (2007) Simulation of pedestrian flow on square lattice based on cellular automata model [J]. Phys A 384(2):567–588CrossRefGoogle Scholar
  6. 6.
    Walus K, Budiman RA, Jullien GA (2004) Split current quantum-dot cellular automata-modeling and simulation [C]. IEEE Trans Nanotechnol 3(2):249–255CrossRefGoogle Scholar
  7. 7.
    Xiao X, Shao SH, Ding YS, Huang HD, Chen XJ, Chou KC (2005) An application of gene comparative image for predicting the effect on replication ratio by HBV virus gene missense mutation [J]. J Theor Biol 235(4):555–565CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Department of Mechanic-Electronic EngineeringSuzhou Vocational UniversitySuzhouChina
  2. 2.School of Electrical and Information EngineeringJiangsu UniversityZhenjiangChina
  3. 3.Department of Computer EngineeringSuzhou Vocational UniversitySuzhouChina

Personalised recommendations