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A High Capacity Image Steganography in Wavelet Transform Domain

Sarreshtedari, Saeed | 2009

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 40341 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Ghaemmaghami, Shahrokh
  7. Abstract:
  8. Recent developments of internet technology and digital media have led to the rapid growth of the steganography systems. Steganography is the art and science of concealing a secret message in a cover without leaving a perceptible or detectable trace of the message. Therefore, steganography methods, capable of embedding the largest possible amount of data with least distortion to the cover media, are highly demanding. The LSB steganography is a primary and simple method with high embedding capacity, where higher robustness is achieved if it is applied to the cover signal in the transform domain. However, regardless of the embedding domain, an essential robustness issue with the LSB steganography is to have minimal changes to cover signal that are unavoidably made by the embedding process. In this research, an LSB steganography method that decreases the probability of change per pixel to one-third – so named one-third algorithm - is introduced at first. Then, it is proven that this fraction is not only less than those for current similar methods, but also is a lower bound on the probability of change per pixel in LSB techniques with additive noise model and mentioned assumptions. The second approach to the LSB steganography introduced in this thesis is a high capacity steganography technique in wavelet transform domain. In this method, the capacity of different regions of the wavelet representation of the image is determined proportional to their complexities. The one-third algorithm is used if this capacity is equal to one; otherwise, an extension to the one-third algorithm is employed. Experimental results show that the proposed method improves both capacity and imperceptibility constraints simultaneously and significantly, as compared to conventional LSB steganography methods. At the end, the reasons for such improvement are discussed
  9. Keywords:
  10. Steganography ; Wavelet Transform ; Least Significant Bit ; Histogram Characteristic Function ; Mass Center Analysis ; Bit Plane Segmentation ; Bit Plane Complexity ; Capacity Imperceptibility Trade Off

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