Earticle

초록

영어

In this paper, we propose a novel method for automatic object segmentation using Mean shift with Grid-mask for Grab Cut algorithm. The main idea of proposed method is a rapid and exact technique for extracting initial foreground information using Mean shift with Grid-mask then we make initial rectangle around estimated initial foreground. And then Grab Cut algorithm is applied to segment foreground form background based on initial rectangle provided by previous process. In order to evaluate our proposed method, we compare the proposed method with several competitive automatic methods on the MSRA database which has 1000 images with ground truth. The scheme successfully segments objects without prior knowledge with both higher precision and better recall than competitive methods.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Proposed Method
  3.1. Mean Shift Clustering with Grid Mask
  3.2. Rectangle Initialization
  3.3. Object Segmentation using GrabCut
 4. Experimental Result
 5. Conclusions
 References

키워드

저자

• Kang Han Oh [ School of Electronics & Computer Engineering, Chonnam National University ]
• Sooh Hyung Kim [ School of Electronics & Computer Engineering, Chonnam National University ]
• In Seop Na [ School of Electronics & Computer Engineering, Chonnam National University ] Corresponding author
• Gwang Bok Kim [ School of Electronics & Computer Engineering, Chonnam National University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Software Engineering and Its Applications

• 간기

  월간

• pISSN

  1738-9984

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605