scholarly journals A High-Capacity Image Steganography Method Using Chaotic Particle Swarm Optimization

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Aya Jaradat ◽  
Eyad Taqieddin ◽  
Moad Mowafi
Keyword(s):  
Particle Swarm Optimization ◽  
Image Quality ◽  
High Capacity ◽  
Particle Swarm ◽  
Image Steganography ◽  
Embedding Capacity ◽  
Secret Data ◽  
Stego Image ◽  
Swarm Optimization ◽  
Chaotic Particle Swarm Optimization

Image steganography has been widely adopted to protect confidential data. Researchers have been seeking to improve the steganographic techniques in order to increase the embedding capacity while preserving the stego-image quality. In this paper, we propose a steganography method using particle swarm optimization and chaos theory aiming at finding the best pixel locations in the cover image to hide the secret data while maintaining the quality of the resultant stego-image. To enhance the embedding capacity, the host and secret images are divided into blocks and each block stores an appropriate amount of secret bits. Experimental results show that the proposed scheme outperforms existing methods in terms of the PSNR and SSIM image quality metrics.

High Capacity Steganographic Scheme for JPEG Compression Using Particle Swarm Optimization

2012 ◽  
Vol 433-440 ◽  
pp. 5118-5122
Author(s):  
Feno Heriniaina Rabevohitra ◽  
Jun Sang
Keyword(s):  
Particle Swarm Optimization ◽  
High Capacity ◽  
Particle Swarm ◽  
Jpeg Compression ◽  
Substitution Matrix ◽  
Secret Data ◽  
Stego Image ◽  
Swarm Optimization ◽  
Best Fit

A steganographic scheme for JPEG compressed image with high capacity and with good quality of the stego-image was presented. A quantization table of size 16*16 was used instead of the commonly used size 8*8 in most JPEG compression to obtain higher embedding capacity. In addition, to improve the quality of the stego-image, particle swarm optimization (PSO) was applied to find an optimal substitution matrix to transform the secret data into the best fit for the cover image before embedding. The experimental results show that, for the proposed scheme, the improvement of the quality of the stego-image and a higher capacity of the secret data was achieved.

scholarly journals Application of Genetic Algorithm and Particle Swarm Optimization techniques for improved image steganography systems

Open Physics ◽  
2016 ◽  
Vol 14 (1) ◽  
pp. 452-462 ◽  
Author(s):  
Duraisamy Jude Hemanth ◽  
Subramaniyan Umamaheswari ◽  
Daniela Elena Popescu ◽  
Antoanela Naaji
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Frequency Domain ◽  
Particle Swarm ◽  
Optimization Techniques ◽  
Image Steganography ◽  
Secret Data ◽  
Stego Image ◽  
Swarm Optimization ◽  
Transform Coefficients

AbstractImage steganography is one of the ever growing computational approaches which has found its application in many fields. The frequency domain techniques are highly preferred for image steganography applications. However, there are significant drawbacks associated with these techniques. In transform based approaches, the secret data is embedded in random manner in the transform coefficients of the cover image. These transform coefficients may not be optimal in terms of the stego image quality and embedding capacity. In this work, the application of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) have been explored in the context of determining the optimal coefficients in these transforms. Frequency domain transforms such as Bandelet Transform (BT) and Finite Ridgelet Transform (FRIT) are used in combination with GA and PSO to improve the efficiency of the image steganography system.

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