Abstract
Many Scientists in Image Processing try to find an efficient way for digital multimedia protection. Although standards and criteria are still in developing, the watermarking which performs mark picture embedding and extraction with original image has been identified as major technology to achieve ownership and copyright protection. This paper is aim to find a more efficient way to embedding watermark into a gray-scale original image using a new algorithm – Artificial Bee Colony to optimize pixel by pixel embedding at different frequency levels (sub-band) with Discrete Wavelet Transform (DWT) Technology in order to enhance the security, invisibility to human visual and robustness of image watermarking. The proposed scheme will take efforts in higher level of DWT decomposition which provide better robustness but low quality of watermarked image and perform better quality of watermarked image and visible watermark compare to random embedding. The proposed new embedding method has been tested against most types of image modifications and in different frequency domain and levels of DWT to provide both high quality watermarked images and superior robustness.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Yusof, Y., Khalifa, O.O.: Imperceptibility and robustness analysis of DWT-based digital image watermarking. In: International Conference on Computer and Communication Engineering, ICCCE 2008, pp. 1325–1330. IEEE (2008)
Hsieh, M.-S.: Perceptual Copyright Protection Using Multiresolution Wavelet-Based Watermarking And Fuzzy Logic. arXiv preprint arXiv:1007.5136 (2010)
Wang, F.-H., Pan, J.-S., Jain, L.C.: Innovations in Digital Watermarking Techniques. Springer (2009)
Rohani, M., Nasiri Avanaki, A.: A watermarking method based on optimizing SSIM index by using PSO in DCT domain. In: 14th International CSI on Computer Conference, CSICC 2009, pp. 418–422 (2009)
Karaboga, D., Basturk, B.: Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems. In: Melin, P., Castillo, O., Aguilar, L.T., Kacprzyk, J., Pedrycz, W. (eds.) IFSA 2007. LNCS (LNAI), vol. 4529, pp. 789–798. Springer, Heidelberg (2007)
Karaboga, D.: http://mf.erciyes.edu.tr/abc/
Basheer, N.M., Abdulsalam, S.S.: Digital Image Watermarking Algorithm in Discrete Wavelet Transform Domain Using HVS Characteristics. In: Proceedings of the IEEE International Conference on Information Technology: Coding and Computing, pp. 122–127 (2011)
Mistry, D., Banerjee, A.: Discrete Wavelet Transform using MATLAB. International Journal (2013)
Chowdhury, M.M.H., Khatun, A.: Image Compression Using Discrete Wavelet Transform. IJCSI International Journal of Computer Science Issues 9 (2012)
Karaboga, D.: An idea based on honey bee swarm for numerical optimization. Technical report-tr06, Erciyes university, engineering faculty, computer engineering department (2005)
Akay, B.: A study on particle swarm optimization and artificial bee colony algorithms for multilevel thresholding. Applied Soft Computing 13, 3066–3091 (2013)
Turanoğlu, E., Özceylan, E., Kiran, M.S.: Particle Swarm Optimization and Artificial Bee Colony Approaches to Optimize of Single Input-Output Fuzzy Membership Functions. In: The 41st International Conference on Computers & Industrial Engineering (2011)
Bae, C., Yeh, W.-C., Shukran, M., Chung, Y.Y., Hsieh, T.-J.: A novel anomaly-network intrusion detection system using ABC algorithm. Int. J. Innov. Comput. Inf. Control 8, 8231–8248 (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Sha, F., Lo, F., Chung, Y.Y., Chen, X., Yeh, WC. (2015). A Novel Optimized Watermark Embedding Scheme for Digital Images. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds) MultiMedia Modeling. MMM 2015. Lecture Notes in Computer Science, vol 8936. Springer, Cham. https://doi.org/10.1007/978-3-319-14442-9_18
Download citation
DOI: https://doi.org/10.1007/978-3-319-14442-9_18
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14441-2
Online ISBN: 978-3-319-14442-9
eBook Packages: Computer ScienceComputer Science (R0)