Abstract—Steganography is the science that involves communicating secret data in an appropriate multimedia carrier. This paper presents the application of contourlet Transform and Genetic Algorithm (GA) in a novel steganography scheme. We employ a genetic algorithm based mapping function to embed data in Discrete contourlet Transform coefficients in 4x4blocks on the cover image. The optimal pixel adjustment process (OPAP) is applied after embedding the message. GA employed to obtain an optimal mapping function to lessen the error difference between the cover and the stego image and use the block mapping method to preserve the local image properties. Also we applied the OPAP to increase the hiding capacity of the algorithm in comparison with other systems.According to the experimental results, the proposed method is capable of providing a larger embedding capacity without causing noticeable distortions of stego-images in comparison with similar existing methods. Moreoverthe results of our experiments show that employing two of powerful steganalyzers on stego-images produced by our method, they could not discriminate between stego and clean-images reliably. Index Terms—Steganography, discrete contourlet transform, genetic algorithm, optimal pixel adjustment process. I. INTRODUCTION Since the rise of the Internet one of the most important factors of information technology and communication has been the security of information. Cryptography was created as a technique for securing the secrecy of communication and many different methods have been developed to encrypt and decrypt data in order to keep the message secret. Unfortunately it is sometimes not enough to keep thecontents of a message secret, it mayalso be necessary to keep the existence of the message secret. The technique used to implement this, is called steganography [1]. The word steganography is derived from the Greek words “stegos” meaning “cover” and “grafia” meaning “writing”[2]. Steganography methods hide the secret data in a cover carrier so that the existence of the embedded data is undetectable [3]. The cover carrier can be different kinds of digital media such as text, image, audio and video [4]. Many image steganography methods have been proposed. In these methods, the secret data is embedded into the cover-image by modifying the cover-image to form a stego- Manuscript received September 5, 2012; revised October 11, 2012. F. H. Ramezani is with the Department of Computer Engineeringat Science and Research branch Islamic Azad University, Kerman, Iran (e- mail: hadiseramezani@yahoo.com). C. F.Keynia is with the Department of Electrical Engineering, Semnan University, Molavi, Semnan 35195-363, Iran (e-mail: keynia@yahoo.com). T. F. Ramezani is with the Department of Electrical Engineering, Yazd university, Yazd, Iran (e-mail: fereshte.ramezani@gmail.com). image.The most important requirement for a steganographic algorithm is to be imperceptible [5]. Imperceptibility involves [5]: Invisibility-The invisibility of a steganographic algorithm is the first and foremost requirement, since the strength of steganography lies in its ability to be unnoticed by the human eye. Capacity-Steganography aims at hidden communication and requires sufficient embedding capacity. Capacity is measured in bits per pixel (bpp) in images. Robustness against statistical attacks and image manipulation-The amount of modification the stego amount medium can withstand before an adversary can destroy the hidden information. Achieving all this requirements simultaneously is difficult to a great extend.Steganographic methods can be broadly classified in to 3 categories [20]. 1. Spatial transform, 2. Transform domain, 3. Adaptive steganography methods. Common approaches in spatial domain include Least Significant Bit (LSB) manipulation [6]. LSB insertion is the simplest method and very weak in resisting even simple attack such as transform, compression, etc [5]. The transform technique involves modulating the coefficients of the cover data in the frequency domain. There are a few methods in fourier transform owing to it is not used for JPEG image format. In contrast DCT is used extensively with image compression such as JPEG lossy compression. Although modification of properly selected DCT coefficient during embedding process will not cause noticeable visualartifacts, nevertheless they cause detectable statistical degradations [3]. Various steganography methods like YASS [7], MB [8], Outguess [9], Perturbed Quantization (PQ) [10] have been proposed with the purpose of minimizing the statistical artifacts which are produced by modifications of DCT coefficients. In the Wavelet transform there are some steganography methods such as StegJasper [11] have been proposed that in comparison with DCT is more adaptive with HVS. Adaptive steganography is special case of the two former methods. These techniques analyse the image and hide information in significant areas so that the hidden message is more a part of the image than being added noise in the image. e.g. [12] is an adaptive steganography based on contourlet domain. This paper proposes a method to embed data in contourlet coefficients using a mapping function based on GA in 4x4 blocks on the cover image and, it applies the OPAP after embedding the message to maximize the Pick signal to noise ratio (PSNR).Only a few works on data hiding are done in contourlet transform domain [5], [12], [13], [26], besides there are some image steganography methods that A Novel Image Steganography in Contourletdomain Using Genetic Algorithm H. Ramezani, F. Keynia, and F. Ramezani International Journal of Future Computer and Communication, Vol. 2, No. 4, August 2013 359 DOI: 10.7763/IJFCC.2013.V2.185