Abstract
The strong energy compaction property of the Discrete Cosine Transform (DCT) has inspired researchers to utilize the DCT transform technique in steganography. The DCT transform can effectively represent a signal within a few significant coefficients leaving a large area with insignificant coefficients that can be safely replaced by a substantial amount of secret data. It has been proven that this strong energy compaction property has a relation with the correlation of the signal. The higher the correlation, the stronger the compaction, and thus more data can be hidden. Therefore, several state-of-the-art image steganography techniques tend to segment the cover image into homogeneous segments to exploit the strong compaction property of the DCT. In this paper, a precise segmentation process using the region-growing segmentation method is applied to maximize the homogeneity level between pixels in a segment, and thus, maximizing the hiding capacity while achieving improved stego quality.
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Rabie, T., Kamel, I., Baziyad, M.: Maximizing embedding capacity and stego quality: curve-fitting in the transform domain. Multimedia Tools Appl. (2017). https://doi.org/10.1007/s11042-017-4727-5
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Baziyad, M., Rabie, T., Kamel, I. (2020). Achieving Stronger Compaction for DCT-Based Steganography: A Region-Growing Approach. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S., Orovic, I., Moreira, F. (eds) Trends and Innovations in Information Systems and Technologies. WorldCIST 2020. Advances in Intelligent Systems and Computing, vol 1160. Springer, Cham. https://doi.org/10.1007/978-3-030-45691-7_24
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DOI: https://doi.org/10.1007/978-3-030-45691-7_24
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