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High payload image steganography based on Laplacian of Gaussian (LoG) edge detector

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Abstract

Image Steganography is the method of concealing secret information into the digital image, and LSB replacement policy is recognized as the foremost and widely used approach. In traditional LSB based scheme, the secret bits are fabricated into the LSB position of each pixel without making a prior analysis of the image contents. As a consequence, the visual quality as well as the security of the stego-image becomes a concern even to achieve a low embedding rate. In this paper, the embedding of secret data has been made by classifying the pixels of the cover image into following two categories: edge and non-edge. This classification is made by applying the Laplacian of Gaussian (LoG) edge detector over the gray-scale images. It has been observed that the non-edge pixels get affected severely compared to edge pixels at higher embedding rate and therefore, more bits are embedded in edge pixels rather than in the non-edge pixels. The disadvantage of existing edge detection based Steganography schemes is the embedding of (extra) edge information besides the actual embedding. Unlikely, the proposed scheme proficiently avoids the burden of embedding of extra edge information and utilizes the embedding space fully. Experimental results ensure that the proposed scheme achieves higher payload and better stego-image quality compared to existing schemes.

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Authors and Affiliations

  1. Department of Computer Science & Engineering, Future Institute of Technology, 240, Boral Main Road, Kolkata, 7000154, India

    S. K. Ghosal

  2. Department of Computer Science & Engineering, University of Kalyani, Kalyani, Dist-, Nadia, 741235, India

    J. K. Mandal

  3. Department of Computer Science & Engineering, Jadavpur University, Kolkata, 700032, India

    R. Sarkar

Authors
  1. S. K. Ghosal
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  2. J. K. Mandal
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  3. R. Sarkar
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Correspondence to S. K. Ghosal.

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Ghosal, S.K., Mandal, J.K. & Sarkar, R. High payload image steganography based on Laplacian of Gaussian (LoG) edge detector. Multimed Tools Appl 77, 30403–30418 (2018). https://doi.org/10.1007/s11042-018-6126-y

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  • DOI: https://doi.org/10.1007/s11042-018-6126-y

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