An enhanced Huffman-PSO based image optimization algorithm for image steganography
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- @Article{Sharma:GPEM,
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author = "Neha Sharma and Usha Batra",
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title = "An enhanced {Huffman-PSO} based image optimization
algorithm for image steganography",
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journal = "Genetic Programming and Evolvable Machines",
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year = "2021",
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volume = "22",
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number = "2",
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pages = "189--205",
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month = jun,
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keywords = "genetic algorithms, genetic programming, PSO,
Huffman-PSO, swarm intelligence, HPSO, DWT, Image
steganography",
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ISSN = "1389-2576",
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DOI = "doi:10.1007/s10710-020-09396-z",
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size = "17 pages",
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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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notes = "GD Goenka University, Gurugram 122103, India",
- }
Genetic Programming entries for
Neha Sharma
Usha Batra
Citations