4.3 Article

An Image Watermarking Scheme Using Arnold Transform and Fuzzy Smooth Support Vector Machine

Journal

MATHEMATICAL PROBLEMS IN ENGINEERING
Volume 2015, Issue -, Pages -

Publisher

HINDAWI LTD
DOI: 10.1155/2015/931672

Keywords

-

Funding

  1. National Natural Science Foundation of China [61370169, 61402153, 61472042]
  2. Key Project of Science and Technology Department of Henan Province [142102210056]
  3. Science and Technology Research Key Project of Educational Department of Henan Province [13A520529, 12A520027]
  4. Education Fund for Youth Key Teachers of Henan Normal University

Ask authors/readers for more resources

With the development of information security, the traditional encryption algorithm for image has been far from ensuring the security of image in the transmission. This paper presents a new image watermarking scheme based on Arnold Transform (AT) and Fuzzy Smooth Support Vector Machine (FSSVM). First of all, improved AT (IAT) is obtained by adding variables and expanding transformation space, and FSSVM is proposed by introducing fuzzy membership degree. The embedding positions of watermark are obtained from IAT, and the pixel values are embedded in carrier image by quantization embedding rules. Then, the watermark can be embedded in carrier image. In order to realize blind extraction of watermark, FSSVM model is used to find the embedding positions of watermark, and the pixel values are extracted by using quantization extraction rules. Through using improved Arnold inverse transformation for embedding positions, the watermark coordinates can be calculated, and the extraction of watermark is carried out. Compared with other watermarking techniques, the presented scheme can promote the security by adding more secret keys, and the imperceptibility of watermark is improved by introducing quantization rules. The experimental results show that the proposed method outperforms many existing methods against various types of attacks.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.3
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available