Earticle

초록

영어

Saliency detection is an important research topic in computer vision. The traditional methods compute image saliency map, then salient segmentation is based on the corresponding saliency map. Unfortunately, overall performance of this method is poor due to the reason of losing some fine details and spatial information within image. This paper presents a new framework to overcome the drawback, named FDSRDS(Framework for Directly Salient Region Detection and Segmentation based on graph methods). Under FDSRSD, firstly, we get the foreground image by segmenting the original image via our extended grabcut algorithm. Mostly, the saliency region is within the foreground part. Secondly, we segment the foreground image into regions by means of graph based segmentation and nearest neighbor graph . Thirdly, we use relative weber's luminance rules to calculate every region’s luminance. Finally, we get the maximum luminance region which is the saliency region. Under FDSRSD framework, algorithms we proposed capture fine details and spatial relationships in saliency computation. We demonstrate impressive results by evaluating our method with other five state-of-the-art methods on the publicly available data set.

목차

Abstract
 1. Introduction
 2. Related Work
 3. The FDSRDS Framework
  3.1. Direct Segmentation by Extended Grabcut
  3.2. Grouping Intermediate Image into Regions by Graph Segmentation Based on Nearest Neighbor Graph
  3.3. Eliminating Surplus Regions by Region Luminance Contrast Construction by Weber's Luminance Rules
 4. Experimental Comparisons
  4.1. Experimental Setup
  4.2. Results
 5. Discussions and Conclusions
  5.1. Results
  5.2. Conclusions and Future Works
 Acknowledgements
 References

키워드

저자

• Lin Li [ University of Electronic Science and Technology of China, Chengdu 611731, China, Sichuan TOP IT Vocational Institute ]
• Yue Wu [ University of Electronic Science and Technology of China, Chengdu 611731, China ]
• Mao Ye [ University of Electronic Science and Technology of China, Chengdu 611731, 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