Adaptive Image Steganography Based on Edge Detection Over Dual-Tree Complex Wavelet Transform

  • Inas Jawad KadhimEmail author
  • Prashan Premaratne
  • Peter James Vial
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10956)


The proposed method aims for an advanced steganographic approach based on an adaptive embedding process using edge detection over Dual Tree Complex Wavelet Transform (DT-CWT). Here, subband coefficients allow for maintaining high image imperceptibility even with a dense embedding of secret data. Prior to the embedding process, the cover image is divided into multiple non-overlapping blocks and the secret data bits are indirectly concealed in the selected subbands of DT-CWT coefficients. Amount of data bits embedded on different patches depends on the high frequency elements in each patch. These high frequency regions are identified by using Canny edge detection technique. This helps to embed more bits over highly textured regions and fewer bits over smooth regions and hence significantly reduce the distortion of the stego-image. The DT-CWT provides multiple subbands along multiple orientations increasing data capacity with high cover-stego image and secret-recovered image PSNR value. The performance is evaluated on the basis of different standard benchmarks like similarity index, PSNR, payload capacity etc. to evaluate different aspects of image steganography.


Image steganography Adaptive embedding Data hiding Wavelet transform DT-CWT Edge detection 



The first author would like to acknowledge higher committee of education development in Iraq (HCED) for the scholarship funding.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Electrical and Computer and Telecommunications EngineeringUniversity of WollongongNorth WollongongAustralia
  2. 2.Electrical Engineering Technical CollegeMiddle Technical UniversityBaghdadIraq

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