Earticle

초록

영어

The image segmentation result based on level set typically depends on the appropriate manual initial contour. In this paper, we introduce an autonomous approach for deciding the initial level set contour to be close to the actual boundary as far as possible, and the decided initial contour can be directly evolved by various level set methods. Such an improvement can speed up the evolution and lead to a more robust segmentation result. Then, we consider the statistical information of three distinct regions to construct a new level set model, including contour, contour inside and outside. Combining the two steps above is helpful to obtain a pretty ideal segmentation effect. Some remarkable results and shorter execution time for some difficult segmentation tasks shown in this paper demonstrate the potential of our innovative approach.

목차

Abstract
 1. Introduction
 2. The Proposed Method
  2.1. An Autonomous Approach for Deciding Initial Contour
  2.2. Level Set Evolution Model
  2.3. Implement
 3. Experiment Results
 4. Conclusion
 References

키워드

저자

• Xiaowei He [ College of Mathematics, Physics and Information Engineering, Zhejiang Normal University ]
• Zhuan Song [ College of Mathematics, Physics and Information Engineering, Zhejiang Normal University ]
• Junli Fan [ College of Mathematics, Physics and Information Engineering, Zhejiang Normal University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605