Earticle

초록

영어

Seam carving is a kind of content aware image retargeting algorithm and can be applied to resize and deliberately remove objects from digital images. Based on the observation that after applying an additional seam carving operation, the similarity, the energy relative error, and the difference of seam distance of original image are quite different from those of the seam-carved image, we propose and develop a new method for detecting seam carving or seam insertion of natural images without knowledge of the original image. First, we apply an additional seam carving operation to the testing image, then calculate similarity, energy relative error, and difference of seam distance between the testing image and its seam carved version. Last, we extract 11 dimensional features to detect seam carving operation to train a support vector machine classifier for recognizing whether an image is an original or it has been modified using seam-carving. Our experimental results demonstrate that our proposed forensic method achieves not only better detection rate but also lower dimensional features compared with other existing seam carved detection methods.

목차

Abstract
 1. Introduction
 2. The Proposed Algorithm
  2.1. Overview of Seam Carving Process
  2.2. The Characteristics of Seam Carved Images
  2.3. The Proposed Algorithm
 3. Results and Discussion
  3.1. The Performance of Similarity Feature
  3.2. The Performance of Mixed Features
  3.3. Comparisons with Previous Works
 4. Conclusions
 References

키워드

저자

• Yongzhen Ke [ School of Computer Science and Software Engineering, Tianjin Polytechnic University, China ] Corresponding Author
• Qingqing Shan [ School of Computer Science and Software Engineering, Tianjin Polytechnic University, China ]
• Fan Qin [ Department of Logistics Management, Nankai University, China ]
• Weidong Min [ School of Information Engineering, Nanchang University, China ]
• Jing Guo [ School of Computer Science and Software Engineering, Tianjin Polytechnic University, 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