Earticle

초록

영어

Image segmentation is a fundamental and challenging problem in image processing and often a vital step for high level analysis. Due to the active contour model (ACM) need to choose the initial contour for the following evolution, it limited the utilities of this kind of segmentation to a large extent. For the purpose of avoiding the processing of human choosing initial contour, in this paper, we proposed an automatic initial contour choosing algorithm of the input image information. Based on the chosen initial contour, the iterative efficient and the accuracy of segmentation have been improved when the initial contour is incorporated into the local based segmentation framework. Extensive experiments on synthetic and real images are provided to evaluate our method, showing significant improvements on the segmentation accuracy and stability, comparing to the human chosen initial contour, such as LBF and LGIF.

목차

Abstract
 1. Introduction
 2. The Review and Discussion of the Related Works
 3. The Proposed Model
  3.1. The Criteria of Initial Contour Choosing
  3.2. The Choosing Algorithm of the Initial Contour
 4. Implementation and Experimental Results
  4.1. The Comparison Different Initial Contour
  4.2. The Comparison of the Evolution Efficient
  4.3. The Experiments with Different Kinds of Images
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Caibo [ Southwest University of Science & Technology, Mianyang Sichuan 621010, China, China Academy of Engineering Physics, Mianyang, Sichuan 621000, China ]
• Zhigui Liu [ Southwest University of Science & Technology, Mianyang Sichuan 621010, China, China Academy of Engineering Physics, Mianyang, Sichuan 621000, China ]
• Junbo Wang [ Southwest University of Science & Technology, Mianyang Sichuan 621010, China, China Academy of Engineering Physics, Mianyang, Sichuan 621000, China ]
• Yuyu Zhu [ Southwest University of Science & Technology, Mianyang Sichuan 621010, China ]

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