Adaptive Digital Watermarking Scheme Based on Support Vector Machines and Optimized Genetic Algorithm

Joint Authors

Cao, Chunjie
Zhou, Xiaoyi
Ma, Jixin
Wang, Longjuan

Source

Mathematical Problems in Engineering

Issue

Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2018-03-26

Country of Publication

Egypt

No. of Pages

9

Main Subjects

Civil Engineering

Abstract EN

Digital watermarking is an effective solution to the problem of copyright protection, thus maintaining the security of digital products in the network.

An improved scheme to increase the robustness of embedded information on the basis of discrete cosine transform (DCT) domain is proposed in this study.

The embedding process consisted of two main procedures.

Firstly, the embedding intensity with support vector machines (SVMs) was adaptively strengthened by training 1600 image blocks which are of different texture and luminance.

Secondly, the embedding position with the optimized genetic algorithm (GA) was selected.

To optimize GA, the best individual in the first place of each generation directly went into the next generation, and the best individual in the second position participated in the crossover and the mutation process.

The transparency reaches 40.5 when GA’s generation number is 200.

A case study was conducted on a 256 × 256 standard Lena image with the proposed method.

After various attacks (such as cropping, JPEG compression, Gaussian low-pass filtering (3,0.5), histogram equalization, and contrast increasing (0.5,0.6)) on the watermarked image, the extracted watermark was compared with the original one.

Results demonstrate that the watermark can be effectively recovered after these attacks.

Even though the algorithm is weak against rotation attacks, it provides high quality in imperceptibility and robustness and hence it is a successful candidate for implementing novel image watermarking scheme meeting real timelines.

American Psychological Association (APA)

Zhou, Xiaoyi& Cao, Chunjie& Ma, Jixin& Wang, Longjuan. 2018. Adaptive Digital Watermarking Scheme Based on Support Vector Machines and Optimized Genetic Algorithm. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1206397

Modern Language Association (MLA)

Zhou, Xiaoyi…[et al.]. Adaptive Digital Watermarking Scheme Based on Support Vector Machines and Optimized Genetic Algorithm. Mathematical Problems in Engineering No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1206397

American Medical Association (AMA)

Zhou, Xiaoyi& Cao, Chunjie& Ma, Jixin& Wang, Longjuan. Adaptive Digital Watermarking Scheme Based on Support Vector Machines and Optimized Genetic Algorithm. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1206397

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1206397