• DocumentCode
    2191313
  • Title

    Cover Selection Steganography Method Based on Similarity of Image Blocks

  • Author

    Sajedi, Hedieh ; Jamzad, Mansour

  • Author_Institution
    Dept. of Comput. Eng., Sharif Univ. of Technol., Tehran
  • fYear
    2008
  • fDate
    8-11 July 2008
  • Firstpage
    379
  • Lastpage
    384
  • Abstract
    An advantage of steganography, as opposed to other information hiding techniques, is that the embedder can select a cover image that results in the least detectable stego image. In a previously proposed method, a technique based on block texture similarity was introduced where blocks of cover image were replaced with the similar secret image blocks; then indices of secret image blocks were stored in cover image. In this method, the blocks of secret image are compared with blocks of a set of cover images and the image with most similar blocks to those of the secret image is selected as the best candidate to carry the secret image. Using appropriate features for comparing image blocks, guaranties higher quality of stego images and consequently, allows for higher embedding capacity, less delectability and, enhanced security. Based on this idea, in this paper, an adaptive cover selection steganography method is proposed, that uses statistical features of image blocks and their neighborhood. Using the block neighborhood information, we prevent appearing virtual edges in the sides and corners of the replaced blocks. Our method is examined with feature based and wavelet based steganalysis algorithms. The results prove the effectiveness and benefits of the proposed method.
  • Keywords
    cryptography; data encapsulation; image texture; block texture similarity; image blocks; information hiding; steganography; Gabor filter; Steganography; steganalysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Technology Workshops, 2008. CIT Workshops 2008. IEEE 8th International Conference on
  • Conference_Location
    Sydney, QLD
  • Print_ISBN
    978-0-7695-3242-4
  • Electronic_ISBN
    978-0-7695-3239-1
  • Type

    conf

  • DOI
    10.1109/CIT.2008.Workshops.34
  • Filename
    4568533