Particle Swarm Optimization Algorithm vs. Genetic Algorithm for Image Watermarking Based Discrete Wavelet Transform
Over communication networks, images can be easily copied and distributed in an illegal way. The copyright protection for authors and owners is necessary. Therefore, the digital watermarking techniques play an important role as a valid solution for authority problems. Digital image watermarking techniques are used to hide watermarks into images to achieve copyright protection and prevent its illegal copy. Watermarks need to be robust to attacks and maintain data quality. Therefore, we discussed in this paper two approaches for image watermarking, first is based on Particle Swarm Optimization (PSO) and the second approach is based on Genetic Algorithm (GA). Discrete wavelet transformation (DWT) is used with the two approaches separately for embedding process to cover image transformation. Each of PSO and GA is based on co-relation coefficient to detect the high energy coefficient watermark bit in the original image and then hide the watermark in original image. Many experiments were conducted for the two approaches with different values of PSO and GA parameters. From experiments, PSO approach got better results with PSNR equal 53, MSE equal 0.0039. Whereas GA approach got PSNR equal 50.5 and MSE equal 0.0048 when using population size equal to 100, number of iterations equal to 150 and 3×3 block. According to the results, we can note that small block size can affect the quality of image watermarking based PSO/GA because small block size can increase the search area of the watermarking image. Better PSO results were obtained when using swarm size equal to 100.
[1] J. Waleed, H. D. Jun, T. Abbas, S. Hameed and H. Hatem, “A Survey of Digital Image Watermarking Optimization based on Nature Inspired Algorithms NIAs”, International Journal of Security and Its Applications, vol. 8, no. 6, pp. 315-334, 2014.
[2] R. Dugad, K. Ratakonda and N. Ahuja, A new wavelet-based scheme for watermarking images, Proc. IEEE Intl. Conf. on Image Processing, ICIP’98, Chicago, IL, USA, pp:419-423, Oct. 1998.
[3] C. Karthikeyan and D. Selvamani, Multimodal Biometric Watermarking Techniques: A Review, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Eng, Vol.3, Issue.10, Oct2014.
[4] Jumana Waleed, Huang Dong Jun, Saad Hameed and May Kamil, Optimal Positions Selection for Watermark Inclusion based on a Nature Inspired Algorithm, International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.8, No.1, pp:147-160, 2015.
[5] Sonil Sood, Digital Watermarking Using Hybridization of Optimization Techniques:A Review, (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5 (4), pp: 5249- 5251, 2014.
[6] Qinghai Bai, Analysis of Particle Swarm Optimization Algorithm, Computer and Info Science, Vol.3, No.1, 2010.
[7] Kennedy, J. and Eberhart, R., Particle swarm optimization, Proceedings of IEEE International Conf on Neural Networks, Perth, WA, 1995.
[8] H. Kuo, J. Chang and C. Liu, Particle Swarm Optimization For Global Optimization Problems, Journal of Marine Science and Technology, Vol. 14, No. 3, pp:170-181, 2006.
[9] Dian P.R., Siti M.S. and Siti S.Y., Particle Swarm Optimization: Technique, System and Challenges, International Journal of Computer Applications, Vol.14, No.1, pp:19-27, Jan2011.
[10] Satyobroto T., Mathematical Modelling and Applications of Particle Swarm Optimization, Master’s Thesis, Mathematical Modelling and Simulation, School of Eng. at Blekinge Institute of Technology, Master of Science, Feb 2011.
[11] Voratas K., Comparison of Three Evolutionary Algorithms: GA, PSO, and DE, Industrial Engineering & Management Systems, Vol.11, No.3, pp.215-223, Sep2012.
[12] Daniel Bratton and James Kennedy, Defining a Standard for Particle Swarm Optimization, Proceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS, 2007.
[13] Davoud S. and Ellips M., Particle Swarm Optimization Methods, Taxonomy and Applications, Int. Journal of Computer Theory and Eng., Vol.1, No.5, pp:486-502, 2009.
[14] Mitchell M., An Introduction to Genetic Algorithms, A Bradford Book, The MIT Press, Cambridge, Massachusetts, London, UK, 1999.
[15] Sivanandam S. N. and Deepa S.N, Introduction to Genetic Algorithms, LCCN: 2007930221, ISBN 978-3-540-73189-4 Springer Berlin Heidelberg New York, 2008.
[16] Cong Jin and Shi-Hui Wang, Robust Watermark Algorithm using Genetic Algorithm, Journal Of Information Science And Engineering, 23, pp: 661-670, 2007.
[17] Dahlia R. ElShafie and Nawwaf Kharma , and Rabab Ward , Parameter Optimization of an Embedded Watermark Using a Genetic Algorithm, ISCCSP 2008, Malta, 12-14 March 2008
[18] Sachin Goyal, Roopam Gupta and Ashish Bansal, Application of Genetic Algorithm to Optimize Robustness and Fidelity of Watermarked Images (A conceptual approach), /International Journal on Computer Science and Engineering Vol.1, No.3, pp:239-242, 2009.
[19] P. Surekha1 and S. Sumathi2, Implementation of Genetic Algorithm For A Dwt Based Image Watermarking Scheme, ICTACT Journal On Soft Computing: Special Issue On Fuzzy In Industrial And Process Automation, Vol.02, Issue.1, July 2011.
[20] Abduljabbar Shaamala, et al, Study of the effect DCT and DWT domains on the imperceptibility and robustness of Genetic watermarking, IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 5, No 2, pp:1694-0814, September 2011.
[21] K. Ramanjaneyulu, K. Rajarajeswari, Robust And Oblivious Image Watermarking Scheme In The DWT Domain Using Genetic Algorithm, International Journal of Advanced Engineering Technology, Vol.II, Issue III, pp:85-92, Sep2011.
[22] Cauvery N K, Water Marking on Digital Image using Genetic Algorithm, IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 6, No 2, pp:323-331, Nov2011.
[23] Abduljabbar Shaamala, Azizah A. Manaf, Study Of The Effected Genetic Watermarking Robustness Under DCT And DWT Domains, International Journal on New Computer Architectures and Their Applications, The Society of Digital Information and Wireless Communications (IJNCAA), Vol. 2, No.2, pp: 353-360,2012.
[24] Seyed Ziabari, et al, The Optimized Image Watermarking Using Genetic Algorithm, Current Trends in Technology and Science ISSN: 2279-0535. Vol. II, Issue.VI, pp:359-363, 2013.
[25] Mei Jiansheng, Li Sukang and Tan Xiaomei, A Digital Watermarking Algorithm Based On DCT and DWT, Proceedings of Int Symposium on Web Information Systems and Applications (WISA’09), Nanchang, P. R. China, May 22-24, pp: 104-107, 2009.
[26] Hannu Olkkonen, Discrete Wavelet Transforms: Algorithms And Applications, InTech, Janeza Trdine 9, 51000 Rijeka, Croatia, 2011.
[27] Anumol T.J and P Karthigaikumar, DWT based Invisible Image Watermarking Algorithm for Color Images, IJCA Special Issue on Computational Science- New Dimensions & Perspectives, 2011.
[28] Prashant Kaushik, Digital Image Watermarking using BFO Optimized DWT and DCT, International Journal of Enhanced Research in Science Technology & Eng., Vol. 3, Issue.10, pp:57-61, Oct2014.
[29] Surekha P, and S. Sumathi, Application of GA and PSO to the Analysis of Digital Image Watermarking Processes, International Journal of Computer Science & Emerging Technologies, Vol.1, Issue.4, pp: 350-362, Dec 2010.
[30] Mona M. Soliman, et al, An adaptive Watermarking Approach for Medical Imaging Using Swarm Intelligent, International Journal of Smart Home Vol. 6, No. 1, pp:37-50, Jan 2012.
[31] S. Anu H Nair And P. Aruna, PSO Watermarking Model for Multimodal Biometric System, International Journal of Computer Applications, Vol.100, No.16, pp:23-29, Aug 2014.
[32] Abdelaziz I. Hammouri, et al, Optimization in Discrete Wavelet Domain, IJCSI International Journal of Computer Science Issues, Vol. 10, Issue 2, No.1, pp:330-338, March 2013.
[33] Vikas Kumar, et al, DWT and Particle Swarm Optimization Based Digital Image Watermarking, International Journal of Engineering Research & Technology, Vol.2 Issue 9, pp:2144-2149, Sep2013.
[34] Ahmed. A. Saleh and M. A. Abdou, Evolutionary Computation Methods in Image Watermarking, International Journal of Computer Applications, Vol.63, No.10, pp:1-6, Feb2013.
[35] S. Manikanda prabu, et al, Highly Secured Image Steganography Using Particle Swarm Optimization, International Journal On Engineering Technology and Sciences, Vol.2 Issue.3, pp:26-31, Mar 2015.
[36] S. Gayathri and D. Venkatesan, Particle Swarm Optimization and Discrete Wavelet Transform based Robust Image Watermarking, Indian Journal of Science and Technology, Vol.9, No.48, pp:1-5, Dec 2016.
[37] Shahlla A. Abdalkader and Omaima N. Ahmad AL-Allaf, Particle Swarm Optimization Based Discrete Cosine Transform for Person Identification by Gait Recognition, The 7th Int. Conf on IT, AlZaytoonah University of Jordan, Amman, Jordan, pp:156-163, 12 May 2015.
[38] Omaima N. Ahmad AL-Allaf, Shahlla A. AbdAlKader, Performance Analysis of Different Feature Extraction Algorithms Used with Particle Swarm Optimization for Gait Recognition System, International Journal of Recent Technology and Engineering (IJRTE), Vol.4, Issue.2, pp:23-30, 19 May 2015, Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd
[39] Omaima N. Ahmad AL-Allaf, Improving the Performance of Particle Swarm Optimization for Iris Recognition Systems Using Independent Component Analysis, The 2015 World Congress in Computer Science, Computer Engineering, and Applied Computing (WORLDCOMP’15), The 17th International Conference on Artificial Intelligence, (ICAI'15), July 27-30, 2015, Las Vegas, USA.
[40] Omaima N. Ahmad AL-Allaf and Shahlla A. AbdAlKader, Genetic Algorithm Based on Parallel Computing to Improve the Performance of Fractal Image Compression System, European Journal of Scientific Research, Vol.92, No.2, pp.172-183, Dec2012.
[41] Omaima N. Ahmad AL-Allaf, ParFor and Co-Distributor Parallel Approaches for Implementing Fractal Image Compression Based Genetic Algorithm, IEEE Technically Co-Sponsored Science and Information Conference, pp:345-350, 27-29Aug 2014, London, UK.
[42] Omaima N. Ahmad AL-Allaf, Performance Analysis of MATLAB Parallel Computing Approaches to Implement Genetic Algorithm for Image Compression, chapter 25, pp:397-425, Springer International Publishing Switzerland 2015, K. Arai et al. (eds.), Intelligent Systems in Science and Information 2014, Studies in Computational Intelligence 591.
[1] J. Waleed, H. D. Jun, T. Abbas, S. Hameed and H. Hatem, “A Survey of Digital Image Watermarking Optimization based on Nature Inspired Algorithms NIAs”, International Journal of Security and Its Applications, vol. 8, no. 6, pp. 315-334, 2014.
[2] R. Dugad, K. Ratakonda and N. Ahuja, A new wavelet-based scheme for watermarking images, Proc. IEEE Intl. Conf. on Image Processing, ICIP’98, Chicago, IL, USA, pp:419-423, Oct. 1998.
[3] C. Karthikeyan and D. Selvamani, Multimodal Biometric Watermarking Techniques: A Review, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Eng, Vol.3, Issue.10, Oct2014.
[4] Jumana Waleed, Huang Dong Jun, Saad Hameed and May Kamil, Optimal Positions Selection for Watermark Inclusion based on a Nature Inspired Algorithm, International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.8, No.1, pp:147-160, 2015.
[5] Sonil Sood, Digital Watermarking Using Hybridization of Optimization Techniques:A Review, (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5 (4), pp: 5249- 5251, 2014.
[6] Qinghai Bai, Analysis of Particle Swarm Optimization Algorithm, Computer and Info Science, Vol.3, No.1, 2010.
[7] Kennedy, J. and Eberhart, R., Particle swarm optimization, Proceedings of IEEE International Conf on Neural Networks, Perth, WA, 1995.
[8] H. Kuo, J. Chang and C. Liu, Particle Swarm Optimization For Global Optimization Problems, Journal of Marine Science and Technology, Vol. 14, No. 3, pp:170-181, 2006.
[9] Dian P.R., Siti M.S. and Siti S.Y., Particle Swarm Optimization: Technique, System and Challenges, International Journal of Computer Applications, Vol.14, No.1, pp:19-27, Jan2011.
[10] Satyobroto T., Mathematical Modelling and Applications of Particle Swarm Optimization, Master’s Thesis, Mathematical Modelling and Simulation, School of Eng. at Blekinge Institute of Technology, Master of Science, Feb 2011.
[11] Voratas K., Comparison of Three Evolutionary Algorithms: GA, PSO, and DE, Industrial Engineering & Management Systems, Vol.11, No.3, pp.215-223, Sep2012.
[12] Daniel Bratton and James Kennedy, Defining a Standard for Particle Swarm Optimization, Proceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS, 2007.
[13] Davoud S. and Ellips M., Particle Swarm Optimization Methods, Taxonomy and Applications, Int. Journal of Computer Theory and Eng., Vol.1, No.5, pp:486-502, 2009.
[14] Mitchell M., An Introduction to Genetic Algorithms, A Bradford Book, The MIT Press, Cambridge, Massachusetts, London, UK, 1999.
[15] Sivanandam S. N. and Deepa S.N, Introduction to Genetic Algorithms, LCCN: 2007930221, ISBN 978-3-540-73189-4 Springer Berlin Heidelberg New York, 2008.
[16] Cong Jin and Shi-Hui Wang, Robust Watermark Algorithm using Genetic Algorithm, Journal Of Information Science And Engineering, 23, pp: 661-670, 2007.
[17] Dahlia R. ElShafie and Nawwaf Kharma , and Rabab Ward , Parameter Optimization of an Embedded Watermark Using a Genetic Algorithm, ISCCSP 2008, Malta, 12-14 March 2008
[18] Sachin Goyal, Roopam Gupta and Ashish Bansal, Application of Genetic Algorithm to Optimize Robustness and Fidelity of Watermarked Images (A conceptual approach), /International Journal on Computer Science and Engineering Vol.1, No.3, pp:239-242, 2009.
[19] P. Surekha1 and S. Sumathi2, Implementation of Genetic Algorithm For A Dwt Based Image Watermarking Scheme, ICTACT Journal On Soft Computing: Special Issue On Fuzzy In Industrial And Process Automation, Vol.02, Issue.1, July 2011.
[20] Abduljabbar Shaamala, et al, Study of the effect DCT and DWT domains on the imperceptibility and robustness of Genetic watermarking, IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 5, No 2, pp:1694-0814, September 2011.
[21] K. Ramanjaneyulu, K. Rajarajeswari, Robust And Oblivious Image Watermarking Scheme In The DWT Domain Using Genetic Algorithm, International Journal of Advanced Engineering Technology, Vol.II, Issue III, pp:85-92, Sep2011.
[22] Cauvery N K, Water Marking on Digital Image using Genetic Algorithm, IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 6, No 2, pp:323-331, Nov2011.
[23] Abduljabbar Shaamala, Azizah A. Manaf, Study Of The Effected Genetic Watermarking Robustness Under DCT And DWT Domains, International Journal on New Computer Architectures and Their Applications, The Society of Digital Information and Wireless Communications (IJNCAA), Vol. 2, No.2, pp: 353-360,2012.
[24] Seyed Ziabari, et al, The Optimized Image Watermarking Using Genetic Algorithm, Current Trends in Technology and Science ISSN: 2279-0535. Vol. II, Issue.VI, pp:359-363, 2013.
[25] Mei Jiansheng, Li Sukang and Tan Xiaomei, A Digital Watermarking Algorithm Based On DCT and DWT, Proceedings of Int Symposium on Web Information Systems and Applications (WISA’09), Nanchang, P. R. China, May 22-24, pp: 104-107, 2009.
[26] Hannu Olkkonen, Discrete Wavelet Transforms: Algorithms And Applications, InTech, Janeza Trdine 9, 51000 Rijeka, Croatia, 2011.
[27] Anumol T.J and P Karthigaikumar, DWT based Invisible Image Watermarking Algorithm for Color Images, IJCA Special Issue on Computational Science- New Dimensions & Perspectives, 2011.
[28] Prashant Kaushik, Digital Image Watermarking using BFO Optimized DWT and DCT, International Journal of Enhanced Research in Science Technology & Eng., Vol. 3, Issue.10, pp:57-61, Oct2014.
[29] Surekha P, and S. Sumathi, Application of GA and PSO to the Analysis of Digital Image Watermarking Processes, International Journal of Computer Science & Emerging Technologies, Vol.1, Issue.4, pp: 350-362, Dec 2010.
[30] Mona M. Soliman, et al, An adaptive Watermarking Approach for Medical Imaging Using Swarm Intelligent, International Journal of Smart Home Vol. 6, No. 1, pp:37-50, Jan 2012.
[31] S. Anu H Nair And P. Aruna, PSO Watermarking Model for Multimodal Biometric System, International Journal of Computer Applications, Vol.100, No.16, pp:23-29, Aug 2014.
[32] Abdelaziz I. Hammouri, et al, Optimization in Discrete Wavelet Domain, IJCSI International Journal of Computer Science Issues, Vol. 10, Issue 2, No.1, pp:330-338, March 2013.
[33] Vikas Kumar, et al, DWT and Particle Swarm Optimization Based Digital Image Watermarking, International Journal of Engineering Research & Technology, Vol.2 Issue 9, pp:2144-2149, Sep2013.
[34] Ahmed. A. Saleh and M. A. Abdou, Evolutionary Computation Methods in Image Watermarking, International Journal of Computer Applications, Vol.63, No.10, pp:1-6, Feb2013.
[35] S. Manikanda prabu, et al, Highly Secured Image Steganography Using Particle Swarm Optimization, International Journal On Engineering Technology and Sciences, Vol.2 Issue.3, pp:26-31, Mar 2015.
[36] S. Gayathri and D. Venkatesan, Particle Swarm Optimization and Discrete Wavelet Transform based Robust Image Watermarking, Indian Journal of Science and Technology, Vol.9, No.48, pp:1-5, Dec 2016.
[37] Shahlla A. Abdalkader and Omaima N. Ahmad AL-Allaf, Particle Swarm Optimization Based Discrete Cosine Transform for Person Identification by Gait Recognition, The 7th Int. Conf on IT, AlZaytoonah University of Jordan, Amman, Jordan, pp:156-163, 12 May 2015.
[38] Omaima N. Ahmad AL-Allaf, Shahlla A. AbdAlKader, Performance Analysis of Different Feature Extraction Algorithms Used with Particle Swarm Optimization for Gait Recognition System, International Journal of Recent Technology and Engineering (IJRTE), Vol.4, Issue.2, pp:23-30, 19 May 2015, Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd
[39] Omaima N. Ahmad AL-Allaf, Improving the Performance of Particle Swarm Optimization for Iris Recognition Systems Using Independent Component Analysis, The 2015 World Congress in Computer Science, Computer Engineering, and Applied Computing (WORLDCOMP’15), The 17th International Conference on Artificial Intelligence, (ICAI'15), July 27-30, 2015, Las Vegas, USA.
[40] Omaima N. Ahmad AL-Allaf and Shahlla A. AbdAlKader, Genetic Algorithm Based on Parallel Computing to Improve the Performance of Fractal Image Compression System, European Journal of Scientific Research, Vol.92, No.2, pp.172-183, Dec2012.
[41] Omaima N. Ahmad AL-Allaf, ParFor and Co-Distributor Parallel Approaches for Implementing Fractal Image Compression Based Genetic Algorithm, IEEE Technically Co-Sponsored Science and Information Conference, pp:345-350, 27-29Aug 2014, London, UK.
[42] Omaima N. Ahmad AL-Allaf, Performance Analysis of MATLAB Parallel Computing Approaches to Implement Genetic Algorithm for Image Compression, chapter 25, pp:397-425, Springer International Publishing Switzerland 2015, K. Arai et al. (eds.), Intelligent Systems in Science and Information 2014, Studies in Computational Intelligence 591.
@article{"International Journal of Information, Control and Computer Sciences:76500", author = "Omaima N. Ahmad AL-Allaf", title = "Particle Swarm Optimization Algorithm vs. Genetic Algorithm for Image Watermarking Based Discrete Wavelet Transform", abstract = "Over communication networks, images can be easily copied and distributed in an illegal way. The copyright protection for authors and owners is necessary. Therefore, the digital watermarking techniques play an important role as a valid solution for authority problems. Digital image watermarking techniques are used to hide watermarks into images to achieve copyright protection and prevent its illegal copy. Watermarks need to be robust to attacks and maintain data quality. Therefore, we discussed in this paper two approaches for image watermarking, first is based on Particle Swarm Optimization (PSO) and the second approach is based on Genetic Algorithm (GA). Discrete wavelet transformation (DWT) is used with the two approaches separately for embedding process to cover image transformation. Each of PSO and GA is based on co-relation coefficient to detect the high energy coefficient watermark bit in the original image and then hide the watermark in original image. Many experiments were conducted for the two approaches with different values of PSO and GA parameters. From experiments, PSO approach got better results with PSNR equal 53, MSE equal 0.0039. Whereas GA approach got PSNR equal 50.5 and MSE equal 0.0048 when using population size equal to 100, number of iterations equal to 150 and 3×3 block. According to the results, we can note that small block size can affect the quality of image watermarking based PSO/GA because small block size can increase the search area of the watermarking image. Better PSO results were obtained when using swarm size equal to 100.
", keywords = "Image watermarking, genetic algorithm, particle swarm optimization, discrete wavelet transform.", volume = "11", number = "9", pages = "1095-7", }
