A Blind Image Steganography Algorithm Based on Knight Tour Algorithm and QR Codes


  • Younis Mohammed Younis Department of Computer Science, University of Zakho Kurdistan Region, Iraq
  • Ramadhan J. Mstafa Department of Computer Science, University of Zakho Kurdistan Region, Iraq (and Department of Computer Science, Nawroz University, Duhok, KRG - Iraq)
  • Haval I. Hussein Department of Computer Science, University of Zakho Kurdistan Region, Iraq
  • Ahmed L. Alyousify Department of Computer Science, University of Zakho Kurdistan Region, Iraq




Image Steganography, FAST feature points, QR code, blind model, knight tour algorithm


Internet proliferation and technological progress have made multimedia information quickly accessible, but they have also posed a threat to privacy and security. Researchers have been interested in digital images due to their capacity to store large amounts of data due to the possibility of protecting sensitive information through digital steganography. Despite their visual imperceptibility, robustness, and ability to embed information, existing image steganography techniques face several challenges. To overcome these challenges, a novel image steganography approach based on a blind model strategy has been proposed for hiding covert messages. The model consists of two stages: embedding and extracting. In the embedding stage, a suitable cover image is selected using the FAST feature point detector. A text message is then converted to a QR code and embedded in the feature points' neighbors using knight tour steps in a chess game. The result is a stego image that appears identical to the original cover image but contains the secret message in its feature points' neighbors. The extracting stage involves finding the feature points and extracting the QR code to obtain the original text message. Since the feature points were not altered during the embedding process, the proposed model is known as a blind model. This approach eliminates the need for the original cover image during the extracting stage. The proposed model was evaluated using several metrics, including the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). The results demonstrate that the proposed algorithm can effectively embed and extract secret messages with high accuracy while maintaining the visual quality of the cover image with 100% of (SSIM), and 73.48 as an average of (PSNR).


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How to Cite

Mohammed Younis, Y., J. Mstafa, R., I. Hussein, H., & L. Alyousify, A. (2023). A Blind Image Steganography Algorithm Based on Knight Tour Algorithm and QR Codes. Academic Journal of Nawroz University, 12(3), 332–343. https://doi.org/10.25007/ajnu.v12n3a1891