Optimal Image Watermarking using Hybrid Optimization Algorithm

Optimal Image Watermarking using Hybrid Optimization Algorithm

Satish Ramchandra Todmal (Department of Information Technology, JSPM's Imperial College of Engineering and Research, Pune, India) and Suhas Haribhau Patil (Department of Computer Engineering, Bharati Vidyapeeth Deemed University College of Engineering, Pune, India)
Copyright: © 2015 |Pages: 21
DOI: 10.4018/IJCVIP.2015010102
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Abstract

Image watermarking is a process of embedding secret information into cover image to secure transmission of secret data. Literature presents several image watermarking techniques are based on different transformation such as, wavelet transform, Fourier transform and cosine transform. Most of the authors have been developed an embedding and extraction algorithm newly with the transformed image. Then, the optimal location for embedding the secret data was identified by using optimization algorithm. Accordingly, the authors have developed an optimal robust watermarking technique using genetic algorithm and wavelet transform. In the previous work, watermarks were embedded into the wavelet coefficients of HL and LH band after searching the optimal locations in order to improve both quality of watermarked image and robustness of the watermark. In this work, the authors have developed to improve the genetic algorithm by combining it with Artificial Bee Colony algorithm (ABC Algorithm). Here, they have used hybrid algorithm for finding of optimal location in watermarking process. Finally, the comparative evaluation of the hybrid algorithm will be done with the existing and previous technique using different images and the performance of the extended algorithm will be analyzed using the PSNR, NC with convergence rate.
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1. Introduction

Generally, a watermark is perceptually a non-obstructive mark embedded in an image, audio or video clip or other multimedia asset Raj and Alli, (2012). In order to protect the ownership of text, music, video and images watermarking plays an important role in the process of embedding information in a carrier. Normally watermarks are embedded in images but in the majority of commercial image databases, such as Getty (gettyimages.ie) or I Stock Photo (istockphoto.com) it remains visible. For tampering these traditional watermarking techniques becomes more vulnerable. To resistant against detection and consequently to tampering steganographic techniques for watermarking is most important Lusson, Bailey, Leeney, and Curran (2012). Moreover, the basic idea in digital watermarking for the purpose of copy-right protection, access control, broadcast monitoring, etc. it is embedded into a watermark signal into the host data. A watermark preserved to be a tag, label or digital signal Aslantas (2008).

In order to produce watermarked signal for use in certain applications such as copyright protection, content authentication, copy protection, broadcast monitoring this digital watermarking plays an important role in embedding information (watermark signal) into the multimedia data (such as image, audio, video, and text), called host signal or cover signal. To guarantee desired functionalities a digital watermark must have special features Lang, Zhou Cang, Yu and Shang (2012). Additionally, about the source and copyright status of a document or its intended recipient, its rights and restrictions watermark can carry further information Raj and Alli (2012). Usually, two performance measures such as imperceptibility and robustness are mostly compatible in digital watermarking. However, embedding watermarks into digital images can degrade the images’ visual quality, and it is desirable for the degradation cannot be easily noticed. Therefore, imperceptibility denotes the idea that an embedded watermark should be invisible to the human visual system (HVS) Wang, Peng and Shi (2011).

Further, for the copy attack most of robust watermarking schemes are susceptible, from one document to another by any unauthorized person a watermark can be copied, making these schemes inefficient in all authentication applications. Usually, the digital watermarking schemes are based on transform-domain techniques such as Discrete Cosine Transform (DCT) Huang and Wu (2000). Discrete Fourier Transform (DFT) Seok and Hong, 2001) and Discrete Wavelet Transform (DWT) Wang, Xu, Chen, and Du, 2004). Haar wavelet and more. Currently, some digital watermarking algorithms have been developed based on wavelet transform. Additionally, here using an artificial intelligence (AI) techniques are applied in the watermarking schemes. It can enhance the performance in an efficient way. The problems in watermarking system are considered as an optimization problem. Hence, such problem can be solved by using genetic algorithm Kumsawat, Attakitmongcol, and Srikaew, 2005) adaptive tabu search (ATS) Sriyingyong, and Attakitmongcol, 2006 or support vector machine (SVM) Wang, Niu, and Yang, (2009).

In this paper, a hybrid watermarking method joining a robust and a fragile or semi-fragile watermark is presented, and thus combining copyright protection and tamper. As a result, this approach is mainly resistant against any copy attack. We have developed to improve the genetic algorithm by combining it with ABC (Artificial Bee Colony Algorithm) algorithm. Here, we have used hybrid algorithm for finding of optimal location in watermarking process.

The main contribution of this research includes:

  • The main contribution of this research is used to find out the optimal location using Hybrid algorithm such as Genetic and artificial bee colony algorithm. These algorithm improves performance of the embedding process;

  • For comparison analysis we have taken previous and existing technique with higher PSNR and NC value.

The rest of the paper is organized as follows: a brief review represents existing and previous works of watermarking technique in wavelet domain is presented in Section 2. The proposed efficient image watermarking technique using genetic algorithm is elaborate in Section 3. The experimental results and comparative analysis discussion are explained in Section 4. Finally, the conclusions are summed up in Section 6.

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