Skip to main content
Log in

A predictive model-based image watermarking scheme using Regression Tree and Firefly algorithm

  • Methodologies and Application
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

Digital image watermarking has a great importance in the image security nowadays. In this paper, we have proposed a novel robust image watermarking scheme based on combining Regression Tree as a predictive model and Firefly algorithm as a flexible optimization algorithm. In the proposed scheme, Lifting Wavelet Transform as a strong transform domain is employed to separate the host image into four sub-bands and the low frequency sub-band is used to produce non-overlapping blocks. Then, we sort the blocks in ascending order due to the block’s standard derivation. Primary required blocks (owing to the size of watermark image) are used for embedding process, and others used for making Regression Tree. Firefly algorithm is used to optimize multi-scaling factor according to its significant influence in imperceptibility and robustness. For satisfying security aspects, Fibonacci-Q transform is applied to watermark and the bits of resulted scrambled image participated in embedding process. To evaluate the proposed method, it has been investigated by various image processing operations and due to standard metrics, the experimental results are satisfactory.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  • Agarwal C, Mishra A, Sharma A (2013) Gray-scale image watermarking using GA-BPN hybrid network. J Vis Commun Image Represent 24(7):1135–1146. doi:10.1016/j.jvcir.2013.07.007

    Article  Google Scholar 

  • Agarwal C, Mishra A, Sharma A, Bedi P (2014) Optimized gray-scale image watermarking using DWT-SVD and firefly algorithm. Expert Syst Appl. doi:10.1016/j.eswa.2014.06.011

  • Agoyi M, Çelebi E, Anbarjafari G (2015) A watermarking algorithm based on chirp z-transform, discrete wavelet transform, and singular value decomposition. SIViP 9:735–745. doi:10.1007/s11760-014-0624-9

    Article  Google Scholar 

  • Ali ES (2015) Speed control of DC series motor supplied by photovoltaic system via firefly algorithm. Neural Comput Appl 26:1321–1322. doi:10.1007/s00521-014-1796-5

    Article  Google Scholar 

  • Ali M, Ahn CW, Pant M (2014) Cuckoo search algorithm for the selection of optimal scaling factors in image watermarking. soft computing for problem solving. In: Proceedings of the third international conference on, 413–425. doi:10.1007/978-81-322-1771-8_36

  • Ali M, Ahn CW (2014) An optimal image watermarking approach through cuckoo search algorithm in wavelet domain. Int J Syst Assur Eng Manag. doi:10.1007/s13198-014-0288-4

  • Arora S, Singh S (2013) The firefly optimization algorithm: convergence analysis and parameter selection. Int J Comput Appl. doi:10.5120/11826-7528

  • Chang CY, Su SJ (2005) A neural-network-based robust watermarking scheme. In: Systems, man and cybernetics, 2005 international conference on, vol 3, pp 2482–2487, 10–12 Oct. doi:10.1109/ICSMC.2005.1571521

  • Chen YH, Huang HC (2015) Coevolutionary genetic watermarking for owner identification. Neural Comput Appl 26:291–298. doi:10.1007/s00521-014-1615-z

    Article  Google Scholar 

  • Chrysochos E, Fotopoulos V, Xenos M, Skodras AN (2012) Hybrid watermarking based on chaos and histogram modification. Signal Image Video Process. doi:10.1007/s11760-012-0307-3

  • Daubeches I, Sweldens W (1998) Factoring wavelet transform into lifting steps. J Fourier Anal Appl 4(3):247–269. doi:10.1007/BF02476026

    Article  MathSciNet  MATH  Google Scholar 

  • Davis KJ, Najarian K (2001) Maximizing strength of digital watermarks using neural networks. Neural networks, 2001. In: Proceedings. IJCNN ’01. International joint conference on, vol 4, pp 2893–2898, 15–19 Jul. doi:10.1109/IJCNN.2001.938836

  • Dongxu Q, Jiancheng Z, Xiaoyou H (2000) A new class of scrambling transformation and its application in the image information covering. Sci China. doi:10.1007/BF02916835

  • Elshazly EH, Faragallah OS, Abbas AM, Ashour MA, El-Rabaie EM, Kazemian H et al (2014) Robust and secure fractional wavelet image watermarking. SIViP. doi:10.1007/s11760-014-0684-x

  • Fan W, Chen J, Zhen j (2005) SPIHT algorithm based on fast lifting wavelet transform in image compression. In: Hao Y et al (ed) CIS 2005, Part II, LNAI 3802, pp 838–844. doi:10.1007/11596981_122

  • Fu Y, Shen R, Lu H (2004) Watermarking scheme based on support vector machine for colour images. Electron Lett. doi:10.1049/el:20040600

  • Helle C, Perona P (2000) Pasadena houses. \(\copyright \) California Institute of Technology. http://vision.caltech.edu/archive.html

  • Jagadeesh B, Kumar PR, Reddy PC (2015) Robust digital image watermarking based on fuzzy inference system and back propagation neural networks using DCT. Soft Comput. doi:10.1007/s00500-015-1729-y

  • Kaur R, Rattan M (2015) Optimization of the return loss of differentially fed microstrip patch antenna using ANN and firefly algorithm. Wirel Pers Commun 80:1547–1556. doi:10.1007/s11277-014-2099-y

    Article  Google Scholar 

  • Kumsawat P, Attakitmongcol K, Srikaew A (2005) A new approach for optimization in image watermarking by using genetic algorithms. IEEE Trans Signal Process. doi:10.1109/TSP.2005.859323

  • Lai CC, Tsai CC (2010) Digital image watermarking using discrete wavelet transform and singular value decomposition. IEEE Trans Instrum Meas. doi:10.1109/TIM.2010.2066770

  • Lei B, Soon IY, Zhou F, Li Z, Lei H (2012) A robust audio watermarking scheme based on lifting wavelet transform and singular value decomposition. Signal Process 92(9):1985–2001. doi:10.1016/j.sigpro.2011.12.021

    Article  Google Scholar 

  • Lin WH, Horng SJ, Kao TW, Fan P, Lee CL, Pan Y (2008) An efficient watermarking method based on significant difference of wavelet coefficient quantization. IEEE Trans Multimed 10(5):746–757. doi:10.1109/TMM.2008.922795

    Article  Google Scholar 

  • Loh WY (2011) Classification and regression trees. WIREs Data Min Knowl Discov. doi:10.1002/widm.8

  • Loukhaoukha K, Chouinard JY, Haj Taieb M (2011) Optimal image watermarking algorithm based on LWT-SVD via multi-objective ant colony optimization. J Inf Hiding Multimed Signal Process 2:303–319

    Google Scholar 

  • Mehta R, Rajpal N, Vishwakarma VP (2015a) A robust and efficient image watermarking scheme based on Lagrangian SVR and lifting wavelet transform. Int J Mach Learn Cybern. doi:10.1007/s13042-015-0331-z

  • Mehta R, Rajpal N, Vishwakarma VP (2015b) Robust image watermarking scheme in lifting wavelet domain using GA-LSVR hybridization. Int J Mach Learn Cybern. doi:10.1007/s13042-015-0329-6

  • Miller ML, Doerr GJ, Cox IJ (2002) Dirty-paper trellis codes for watermarking, image processing. In: Proceedings. 2002 international conference on (2002). doi:10.1109/ICIP.2002.1039904

  • Rahebi J, Hardalaç F (2015) A new approach to optic disc detection in human retinal images using the firefly algorithm. Med Biol Eng Comput. doi:10.1007/s11517-015-1330-7

  • Raja NSM, Manic KS, Rajinikanth V (2013) Firefly algorithm with various randomization parameters: an analysis. In: SEMCCO 2013, Part I, LNCS 8297, pp 110–121. doi:10.1007/978-3-319-03753-0_11

  • Sheikh HR, Bovik AC (2006) Image information and visual quality. IEEE Trans Image Process. doi:10.1109/TIP.2005.859378

  • Soliman MM, Hassanien AE, Onsi HM (2015) An adaptive watermarking approach based on weighted quantum particle swarm optimization. Neural Comput Appl. doi:10.1007/s00521-015-1868-1

  • Su Q, Wang G, Jia S, Zhang X, Liu Q, Liu X (2015) Embedding color image watermark in color image based on two-level DCT. SIViP 9:991–1007. doi:10.1007/s11760-013-0534-2

    Article  Google Scholar 

  • Thafasal Ijyas VP, Sameer SM (2014) Firefly algorithm for joint estimation of frequency offsets and channel in OFDMA uplink. Wirel Pers Commun 79:565–580. doi:10.1007/s11277-014-1873-1

    Article  Google Scholar 

  • Verma VS, Jha RK (2015) Improved watermarking technique based on significant difference of lifting wavelet coefficients. SIViP 9:1443–1450. doi:10.1007/s11760-013-0603-6

    Article  Google Scholar 

  • Walia E, Suneja A (2014) A robust watermark authentication technique based on Weber’s descriptor. SIViP 8:859–872. doi:10.1007/s11760-012-0312-6

    Article  Google Scholar 

  • Wang Z, Wang N, Shi B (2006) A novel blind watermarking scheme based on neural network in wavelet domain. In: Intelligent control and automation, 2006 6th world congress on, 3024–3027. doi:10.1109/WCICA.2006.1712921

  • Wen XB, Zhang H, Xu XQ, Quan JJ (2009) A new watermarking approach based on probabilistic neural network in wavelet domain. Soft Comput 13(4):355–360. doi:10.1007/s00500-008-0331-y

    Article  Google Scholar 

  • Yang XS (2008) Nature-inspired metaheuristic algorithms. Luniver Press, Frome ISBN: 1-905986-10-6

    Google Scholar 

  • Yang XS (2009) Firefly algorithms for multimodal optimization. In: Stochastic algorithms: foundations and applications, SAGA (2009). Lecture notes in computer sciences, vol 5792, pp 169–178. doi:10.1007/978-3-642-04944-6_14

  • Yang XS (2010) Firefly algorithm, stochastic test functions and design optimization. Int J Bio-Inspired Comput 2(2):78–84. doi:10.1504/IJBIC.2010.032124

    Article  Google Scholar 

  • Zhang SQ, He N, Zang HY (2006) Research of the lifting wavelet arithmetic and applied in rotary mechanic fault diagnosis. J Phys Conf Ser 48:696–700. doi:10.1088/1742-6596/48/1/131

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohsen Ebrahimi Moghaddam.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Communicated by V. Loia.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kazemivash, B., Moghaddam, M.E. A predictive model-based image watermarking scheme using Regression Tree and Firefly algorithm. Soft Comput 22, 4083–4098 (2018). https://doi.org/10.1007/s00500-017-2617-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-017-2617-4

Keywords

Navigation