Using PSO in Image Hiding Scheme Based on LSB Substitution

With the massive growth in internet applications, there is a continuous need of efficient steganography techniques for the purpose of secret data communication and for the authentication and ownership identification of host data. This paper presents an efficient image hiding scheme using Particle Swarm Optimization (PSO) in the spatial domain of digital images. The proposed technique uses PSO to find the best pixel locations in an image where the secret image pixel data can be embedded. This PSO algorithm uses the Structural similarity Index (SSIM) as the objective function which is based on the simple visual effect of the human visual perception capability. As a result, the pixel positions generated by the proposed method, when used for embedding secret image data, result in minimum distortion of the host image. The results of the proposed technique have been analyzed qualitatively and quantitatively and also compared with some recent LSB techniques. The results show better stego image quality along with high embedding capacity.

[1]  Andries Petrus Engelbrecht,et al.  Fundamentals of Computational Swarm Intelligence , 2005 .

[2]  Chin-Chen Chang,et al.  A Fast and Secure Image Hiding Scheme Based on LSB Substitution , 2002, Int. J. Pattern Recognit. Artif. Intell..

[3]  Min-Shiang Hwang,et al.  A high quality steganographic method with pixel-value differencing and modulus function , 2008, J. Syst. Softw..

[4]  Abderrahim Elmoataz,et al.  Image and Signal Processing, 4th International Conference, ICISP 2010, Trois-Rivières, QC, Canada, June 30-July 2, 2010. Proceedings , 2010, ICISP.

[5]  Binh Pham,et al.  System Architecture Analysis of a Hybrid Watermarking Method , 2005, KES.

[6]  Chin-Chen Chang,et al.  Image hiding scheme with modulus function and dynamic programming strategy on partitioned pixels , 2006, Pattern Recognit..

[7]  Andries P. Engelbrecht,et al.  Computational Intelligence: An Introduction , 2002 .

[8]  Punam Bedi,et al.  Best Hiding Capacity Scheme for Variable Length Messages Using Particle Swarm Optimization , 2010, SEMCCO.

[9]  Stephan Katzenbeisser,et al.  Information Hiding Techniques for Steganography and Digital Watermaking , 1999 .

[10]  Mauro Barni,et al.  A DCT-domain system for robust image watermarking , 1998, Signal Process..

[11]  Wen-Hsiang Tsai,et al.  A steganographic method for images by pixel-value differencing , 2003, Pattern Recognit. Lett..

[12]  Lee-Ming Cheng,et al.  Hiding data in images by simple LSB substitution , 2004, Pattern Recognit..

[13]  Ja-Chen Lin,et al.  Image hiding by optimal LSB substitution and genetic algorithm , 2001, Pattern Recognit..

[14]  Kevin Curran,et al.  Digital image steganography: Survey and analysis of current methods , 2010, Signal Process..

[15]  Karim Faez,et al.  Image Hiding by Using Genetic Algorithm and LSB Substitution , 2010, ICISP.

[16]  Binh Pham,et al.  Performance Factors Analysis of a Wavelet-based Watermarking Method , 2005, ACSW.

[17]  Cheng-Hsing Yang,et al.  Adaptive Data Hiding in Edge Areas of Images With Spatial LSB Domain Systems , 2008, IEEE Transactions on Information Forensics and Security.

[18]  A. Bovik,et al.  A universal image quality index , 2002, IEEE Signal Processing Letters.

[19]  Tieyong Zeng,et al.  A Generalization of LSB Matching , 2009, IEEE Signal Processing Letters.