Earticle

초록

영어

Histogram thresholding is one of the most popular image segmentation techniques. Variance-based thresholding is a famous method in which. In this paper, a new method based the framework of two-dimensional gray level histogram and class variance criterion is proposed. The methodology for image segmentation using two-dimensional histogram and variance criterion is elaborated firstly. Then the algorithm of the presented scheme is realized through recursion. Finally, the proposed method is tested on synthetic and real-world images. Experimental results show that the proposed method is better to overcome the shortcomings of the conventional variance-based methods, and the effectiveness of the proposed method is demonstrated by the experiments.

목차

Abstract
 1. Introduction
 2. Review of Class Variance Criterion for Image Thresholding
 3. The Proposed Method
  3.1. Thresholding Using Two-dimensional Histogram and Class Variance Criterion
  3.2. The Implementation of Algorithm of the Proposed Method
 4. Experimental Results and Analysis
  4.1. Performance Evaluation
  4.2. Real-world Images
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Fangyan Nie [ College of Computer Science and Technology Hunan University of Arts and Science, Changde 415000, China ]
• Pingfeng Zhang [ 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