Robust image adaptive steganography using integer wavelets

Raja, K B; Sindhu, Siva S. Sivatha; Mahalakshmi, T.; Akshatha, S; Nithin, B.K.; Sarvajith, M.; Venugopal, K R; Patnaik, L. M.

doi:10.1109/comswa.2008.4554484

Cited by 18 publications

(15 citation statements)

References 6 publications

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“…18). The hidden message is more a part of the image than being added noise [67]. The ABCDE method introduced a large embedding capacity; however, certain control parameters had to be configured manually, e.g., finding an appropriate section length for sectioning a stream of resource blocks and finding the threshold value that controls identification of complex blocks.…”

Section: Adaptive Steganographymentioning

confidence: 99%

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Digital image steganography: Survey and analysis of current methods

et al. 2010

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Steganography is the science that involves communicating secret data in an appropriate multimedia carrier, e.g., image, audio, and video files. It comes under the assumption that if the feature is visible, the point of attack is evident, thus the goal here is always to conceal the very existence of the embedded data. Steganography has various useful applications. However, like any other science it can be used for ill intentions. It has been propelled to the forefront of current security techniques by the remarkable growth in computational power, the increase in security awareness by, e.g., individuals, groups, agencies, government and through intellectual pursuit. Steganography's ultimate objectives, which are undetectability, robustness (resistance to various image processing methods and compression) and capacity of the hidden data, are the main factors that separate it from related techniques such as watermarking and cryptography. This paper provides a state-of-the-art review and analysis of the different existing methods of steganography along with some common standards and guidelines drawn from the literature. This paper concludes with some recommendations and advocates for the object-oriented embedding mechanism. Steganalysis, which is the science of attacking steganography, is not the focus of this survey but nonetheless will be briefly discussed.

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Section: Adaptive Steganographymentioning

confidence: 99%

“…In [67], the authors chose to use Wavelet transforms that map integers to integers instead of using the conventional Wavelet Transforms. This can overcome the difficulty of floating point conversion that occurs after embedding.…”

Section: Adaptive Steganographymentioning

confidence: 99%

Digital image steganography: Survey and analysis of current methods

et al. 2010

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“…Narasimmalou, T., et al, [5] proposed an optimal Discrete Wavelet Transform based steganography in which a single level DWT decomposition is done on a host image and the secret information is hidden by manipulating the transform coefficients of the decomposed image. Raja.K.B, et al, [6] have proposed a novel image adaptive steganographic technique in integer wavelet transform domain. Babita Ahuja, et al, [7] proposed for more hiding capacity achieved by Filter Based scheme in Steganography.…”

Section: Related Workmentioning

confidence: 99%

Eliminating Cover Image Requirement in Discrete Wavelet Transform based Digital Image Steganography

Sehgal¹,

Sharma²

2013

IJCA

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Image steganography is the art and science of hiding secret image into digital media such that no one apart from the intended recipient is able to detect the existence of the information. There are many different carriers that can be used to hide the information such as digital images, videos, sound files and other computer files but digital images are the most popular. In this paper, a method has been proposed using which a large size secret image can be hidden into small size cover image securely. The main aim here is the absolute invisibility of the large size secret image. The secret image is first scrambled by using Arnold transformation. Haar Discrete Wavelet Transformation (DWT) is then applied on cover image and Arnold transformed secret image, followed by Alpha Blending operation. Then the Haar Inverse Discrete Wavelet Transformation (IDWT) is applied to obtain the stego image. At the receiver side, first the cover image is obtained from the stego image. Then Haar DWT is applied on the cover image and the stego image followed by the alpha blending operation. Haar IDWT is applied on the resulting image. Then by applying Arnold transformation, the secret image is obtained. The proposed method does not require the sender to send the cover image to the receiver for obtaining the secret image.The performance of the proposed method is investigated by comparing the cover image and the stego image in terms of Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Normalized Cross Correlation (NCC). Experimental results demonstrate the effectiveness and accuracy of the proposed method.

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“…In [49], the authors chose to use wavelet transforms that map integers to integers instead of using the conventional wavelet Transforms. It embeds the secret data in low and mid frequency regions of image which have large energies.…”

Section: Milestones For Adaptive Steganographymentioning

confidence: 99%