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Extension of the virtual electric field model using bilateral-like filter for active contours

  • Shoujun Zhou
  • Yao Lu
  • Nana Li
  • Yuanquan WangEmail author
Original Paper
  • 31 Downloads

Abstract

The gradient vector flow (GVF) model has been proven as an effective external force for active-contour-based image segmentation. However, it suffers from high computation cost since there are two PDEs to be solved in an iterative manner. As a remedy, the virtual electric field (VEF) model is proposed, which can be implemented in real time using the fast Fourier transform. However, the VEF model cannot preserve weak edges since it employs linear kernels. In this work, we extend the VEF model by using bilateral-like filters, and a fast algorithm is also employed for the proposed model. The proposed model is referred to as bilateral-filter-based VEF (BVEF) model. Experimental results on synthetic and real images demonstrate that the BVEF snake possesses some desired properties of the GVF, CNGGVF and VEF snakes such as large capture range and concavity convergence, and the BVEF model can be implemented in near real time, and its computation cost is comparable to that of the VEF model and much shorter than that of the GVF and CNGGVF models; it also can preserve weak edges, thanks to the bilateral-like nonlinear kernels.

Keywords

Active contour Gradient vector flow Virtual electric field And bilateral filter 

Notes

Acknowledgements

This work was supported by the National Science Foundation of China (No. 61471349), the Basic Discipline Layout Project of Shenzhen City (No. JCYJ20150731154850923), Shenzhen Engineering Laboratory for Key Technologies on Intervention Diagnosis and Treatment Integration, the Key program from NSF of Hebei Province (No. F2016202144), the general program from NSF of Tianjin (No. 16JCYBJC15600) and the youth fund from the Department of Education of Hebei Province (No. QN2016217).

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Research Center for Medical Robotics and Minimally Invasive Surgical Device, Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhenChina
  2. 2.School of Artificial IntelligenceHebei University of TechnologyTianjinChina
  3. 3.School of Data and Computer ScienceSun Yat-Sen UniversityGuangzhouChina

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