Earticle

초록

영어

With the advent of the Internet and low-price digital cameras, as well as powerful image editing software, the authenticity of digital images can no longer be taken for granted. Image noises are often introduced into the tampered region during image manipulation process. In this paper, we propose a detection method to locate image forgeries based on noise estimation on HSV color space and hybrid clustering method combined with unsupervised clustering and supervised clustering. A suspicious image is first converted into HSV color space and segmented into non-overlapping image blocks. Then the noise variance at each local image block is estimated as input of unsupervised clustering. Finally, a supervised clustering method based on SVM is used to further improve the detection accuracy. Our experimental results demonstrate that the proposed method can effectively expose tampered regions from tampered images.

목차

Abstract
 1. Introduction
 2. Related Work
 3. The Proposed Method
  3.1. Image Preprocessing
  3.2. Block Segmentation
  3.3. Image Noise Estimation
  3.4. Image Block Classification
 4. Experimental Results and Discussion
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Yongzhen Ke [ School of Computer Science and Software Engineering, Tianjin Polytechnic University, China ]
• Qiang Zhang [ School of Computer Science and Software Engineering, Tianjin Polytechnic University, China ]
• Weidong Min [ School of Computer Science and Software Engineering, Tianjin Polytechnic University, China ]
• Shuguang Zhang [ JiangSu Wisedu Information Technology Co., Ltd, Jiangsu, 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