Preliminary communication

https://doi.org/10.17559/TV-20160517113602

Forgery detection using chaotic watermarking in image key areas

Rui Tao ; School of Information and Control Engineering, China University of Mining and Technology, No. 1 Daxue Road, Xuzhou 221116, Jiangsu, China
Yanjing Sun ; School of Information and Control Engineering, China University of Mining and Technology, No. 1 Daxue Road, Xuzhou 221116, Jiangsu, China
Weidong Liu ; School of Information and Control Engineering, China University of Mining and Technology, No. 1 Daxue Road, Xuzhou 221116, Jiangsu, China

Abstract

In this paper we study watermarking algorithm for compressed images in the application of antiforgery in financial bills. First, the basic watermarking algorithm based on image edge information is studied. The encrypted watermark is converted into binary values and embedded into the edges, meanwhile the original edge shape is preserved from noticeable destruction. Second, the flip-invariant SIFT features are used to localize the key content area like digits and letters in the image. Third, Tent map and a hash function is used to further protect the secrete watermark. The property of Tent map ensured the sensitivity towards changes in the initial value. Therefore we can better protect and encrypt the original watermark. The operations performing on the binary coded image are based on the encryption sequences generated from chaotic map. Different operations are chosen to generate robust encrypted watermark. Finally, we verify our algorithm in antiforgery detection. The sensitivity towards secrete key values is further investigated. The proposed system is sensitive to the key values, hence it effectively protects the watermark from attack. The computational cost is also measured for practical application of the chaotic watermarking. Experimental results show that the proposed method is reliably efficient.

Keywords

antiforgery; binary image; chaotic system; digital watermark

Hrčak ID:

185513

URI

https://hrcak.srce.hr/185513

Publication date:

31.7.2017.

Article data in other languages: croatian

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