Abstract
It is crucial in the field of image steganography to find an algorithm for hiding information by using various combinations of compression techniques. The primary factors in this research are maximizing the capacity and improving the quality of the image. The image quality cannot be compromised up to a certain level as it breaks the concept of steganography by getting distorted visibly. The second primary factor is maximizing the data-carrying/embedding capacity, which makes the use of this technique more efficient. In this paper, we are proposing an image steganography tool by using Huffman Encoding and Particle Swarm Optimization, which will improve the performance of the information hiding scheme and improve overall efficiency. The combinational technique of Huffman PSO not only offers higher information embedment capabilities but also maintains the image quality. The experimental analysis and results on cover images along with different sizes of secret messages validate that the proposed HPSO scheme has superior results using parameters Peak-Signal-to-Noise-Ratio, Mean Square Error, Bit Error Rate, and Structural Similarity Index. It is also robust against statistical attacks.
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FA.HD. Mohsen, M. Hadhoud, K. Mostafa, K. Amin, (2012) A new image segmentation method based on particle swarm optimization. Int. Arab J Inform Technol, 9(5)
A. Aggarwal, S.K. Patra, Performance perdiction of OFDM based digital audio broadcasting system using channel protection mechanisms. Int. Conf. Electron. Comp. Technol 2, 57–61 (2011)
S.K. Sabnis, R.N. Awale, Statistical steganalysis of high capacity image steganography with cryptography. Proc. Comput. Sci. 79, 321–327 (2016)
M. Jain, S.K. Lenkab, S.K. Vasisthaa, Adaptive circular queue image steganography with RSA cryptosystem. Perspect. Sci. 8, 417–420 (2016)
S.U. Mahaeshwari, D.J. Hemanth, Performance enhanced image steganography systems using transforms and optimization techniques. Multimedia Tools Application (2015). https://doi.org/10.1007/s11042-015-3035-1
W. Hong, T.S. Chen, Reversible data embedding for high-quality images using interpolation and reference pixel distribution mechanism. J. Vis. Commun. Image Represent. 22, 131–140 (2011)
A. Sharif, M. Mollaeefar, M. Nazari, A novel method for digital image steganography based on a new three-dimensional chaotic map. Multimed. Tools Appl. 76(6), 7849–7867 (2017). https://doi.org/10.1007/s11042-016-3398-y
M.S. Subehdar, V.H. Mankar, Image steganography using redundant discrete wavelet transform and QR factorization. Comput. Electr. Eng. 54, 406–422 (2016)
S. Yan, G. Tang, Y. Chen, Incorporating data hiding into G. 729 speech codec. Multimed. Tools Appl. 75(18), 493–512 (2016)
G. Swain, Digital image steganography using variable length group of bits substitution. Proc Comput Sci 85, 31–38 (2016)
U. Dewangan, M. Sharma, S. Bera, Development and analysis of stego image using discrete wavelet transform. Int. J. Sci. Res. 2(1), 142–148 (2013)
A. Pradhan, A. K. Sahu, G. Swain, K. R. Sekhar, Performance evaluation parameters of image steganography techniques, Proceedings of International Conference on Research Advances in Integerated Navigation Systems, 1–8, 2016
Z.T.M. Al-Ta’i, E.R. Mohammad, Comparison between PSO and HPSO in Image Steganography. Int. J. Comput. Sci. Inf. Secur. 15(8), 161–168 (2017)
S.I. Nipanikar, V. Hima Deepthi, N. Kulkarni, A sparse representation based image steganography using Particle Swarm Optimization and Wavelet transform. Alex. Eng. J. (2017). https://doi.org/10.1016/j.aej.2017.09.005
A. Miri, K. Faez, Adaptive image steganography based on transform domain via genetic algorithm. Optik-Int. J. Light Electron Otics (2017). https://doi.org/10.1016/j.ijleo.2017.07.043
P. Rajeswari, P. Shwetha, S. Purushothaman (2017, March) Application of wavelet and particle swarm optimization in steganography. In 2017 2nd International Conference on Anti-Cyber Crimes (ICACC) (pp. 129–132). https://doi.org/10.1109/Anti-Cybercrime.2017.7905277
I. Hamid, Image steganography based on discrete wavelet transform and chaotic map. Int. J. Sci. Res. (2018). https://doi.org/10.21275/ART20179396
M. Khari, A.K. Garg, R.G. Crespo, E. Verdú, Gesture recognition of RGB and RGB-D static images using convolutional neural networks. Int. J. Interact. Multimed. Artif. Intell. 5(7), 22 (2019)
R. Gupta, M. Khari, D. Gupta, R.G. Crespo, Fingerprint image enhancement and reconstruction using the orientation and phase reconstruction. Inf. Sci. (2020). https://doi.org/10.1016/j.ins.2020.01.031
R. Gupta, M. Khari, V. Gupta, E. Verdú, X. Wu, E. Herrera-Viedma, R. González Crespo, Fast single image haze removal method for inhomogeneous environment using variable scattering coefficient. Comput. Modeling Eng. Sci. 123(3), 1175–1192 (2020)
M. Khari, A. Sinha, E. Verdu, R.G. Crespo, Performance analysis of six meta-heuristic algorithms over automated test suite generation for path coverage-based optimization. Soft Comput. (2019). https://doi.org/10.1007/s00500-019-04444-y
M. Khari, P. Kumar, D. Burgos, R.G. Crespo, Optimized test suites for automated testing using different optimization techniques. Soft Comput. 22(24), 8341–8352 (2018)
F. Mohsen, M.M. Hadhoud, K. Moustafa, K. Ameen, A new image segmentation method based on particle swarm optimization. Int. Arab J. Inform. Technol. 9(5), 487–493 (2012)
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Sharma, N., Batra, U. An enhanced Huffman-PSO based image optimization algorithm for image steganography. Genet Program Evolvable Mach 22, 189–205 (2021). https://doi.org/10.1007/s10710-020-09396-z
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DOI: https://doi.org/10.1007/s10710-020-09396-z