Earticle

초록

영어

Measuring image similarity is important for a number of image processing applications. The goal of research in objective image similarity assessment is to develop quantitative measures that can automatically predict perceived image similarity. In this paper, we propose a new objective approach of measuring image similarity based on shape context. We take the geometric structures of objects into account during measuring the image similarity by virtue of shape context which is a robust and compact, yet highly discriminative descriptor. Firstly we find visual salient regions of images by virtue of a regional contrast based saliency extraction algorithm and employ shape context to describe the shape of visual salient region. Then we detect shape deformations of visual salient regions between two images through estimating shape context distances, and accordingly compute the image similarity values. Real data have been used to test the proposed approach and very good results have been achieved, validating it.

목차

Abstract
 1. Introduction
 2. Flowchart of the Proposed Approach
 3. Detecting Visual Salient Regions
 4. Computing Shape Context Distance
  4.1. Edge Detection for Shape Context
  4.2. Shape Context
  4.3. Measuring Shape Distance
 5. Measuring Image Similarity Based on Shape Context
 6. Experimental Results
 7. Conclusion
 Acknowledgements
 References

키워드

저자

• Canlin Li [ School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou 450000, China ]
• Shenyi Qian [ School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou 450000, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605