Earticle

초록

영어

This paper presents a novel image segmentation method that performs histogram thresholding based on the conception of Tsallis generalized divergence. Firstly, to fit the image segmentation task, the original formula of Tsallis divergence was simplified, and then the symmetrical version was constructed. After that, the criterion of divergence sum of the objective and background between original and thresholded image was set up based on the symmetrical version of the Tsallis divergence. The optimal threshold obtained by minimizing the criterion of divergence sum. Finally, the proposed method was tested on different gray level images, and the performance was evaluated using uniformity measure, shape measure, and CPU run time. Experimental results indicate the effectiveness of the proposed method.

목차

Abstract
 1. Introduction
 2. Thresholding Principle based on Tsallis Divergence
  2.1. Tsallis Divergence
  2.2. Image Thresholding
 3. Experimental Results and Performance Evaluation
  3.1. Experimental Results and Analysis
  3.2. Performance Evaluation
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Fangyan Nie [ College of Computer Science and Technology, Hunan University of Arts and Science, Changde 415000, China ]
• Xiaolin Wang [ College of Computer Science and Technology, Hunan University of Arts and Science, Changde 415000, China ]
• Shuanghui Yu [ College of Computer Science and Technology, Hunan University of Arts and Science, Changde 415000, China ]
• Zhifei Liao [ College of Computer Science and Technology, Hunan University of Arts and Science, Changde 415000, 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