3rd International ICST Conference on COMmunication System SoftWAre and MiddlewaRE

Research Article

Robust image adaptive steganography using integer wavelets

  • @INPROCEEDINGS{10.1109/COMSWA.2008.4554484,
        author={K. B. Raja and S. Sindhu and T. D. Mahalakshmi and S. Akshatha and B. K. Nithin and M. Sarvajith and K. R. Venugopal and L. M Patnaik},
        title={Robust image adaptive steganography using integer wavelets},
        proceedings={3rd International ICST Conference on COMmunication System SoftWAre and MiddlewaRE},
        keywords={Steganography Integer Wavelet Transforms Wavelet Lifting Cover Image Adjustment.},
  • K. B. Raja
    S. Sindhu
    T. D. Mahalakshmi
    S. Akshatha
    B. K. Nithin
    M. Sarvajith
    K. R. Venugopal
    L. M Patnaik
    Year: 2008
    Robust image adaptive steganography using integer wavelets
    DOI: 10.1109/COMSWA.2008.4554484
K. B. Raja1,*, S. Sindhu1, T. D. Mahalakshmi1, S. Akshatha1, B. K. Nithin1, M. Sarvajith1, K. R. Venugopal1, L. M Patnaik2
  • 1: Department of Computer Science and Engineering University Visvesvaraya College of Engineering, Bangalore University, Bangalore 560 001
  • 2: Microprocessor Applications Laboratory, Indian Institute of Science, Bangalore 560 012
*Contact email: raja_kb@yahoo.com


Information-Theoretic Analysis for Parallel Gaussian Models of Images prescribe embedding the secret data in low and mid frequency regions of image which have large energies. In this paper, we propose a novel steganographic scheme called Robust Image Adaptive Steganography using Integer Wavelet Transform(RIASIWT), which is a practical realization of these prescriptions. Using this scheme we can hide large volumes of data without causing any perceptual degradation of the cover image. The scheme embeds the payload in every non-overlapping 4x4 blocks of the low frequency band of cover image, two pixels at a time, one on either sides of the principal diagonal. Tests for the similarity between the Condition Number of the cover image and the stego image are done for further embedding. We also perform cover image adjustment before embedding the payload in order to ensure lossless recovery. Embedding done in the low frequency bands ensures robustness against attacks such as compression and filtering. Experimental results show better trade off between Visual perceptivity and capacity compared to the existing algorithms.