Skip to main content
SpringerLink
Log in

A New Seam Carving Method for Image Resizing Based on Entropy Energy and Lyapunov Exponent

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

One of the most popular techniques in the field of image retargeting or content-aware resizing a digital image is the seam-carving technique. The performance of image resizing algorithms based on seam-carving indicates that these algorithms are highly dependent on the extraction of importance map techniques. So far, various algorithms have been proposed to extract the importance map. In this paper, a new method based on information entropy is proposed to extract of importance map. Also, a new method for selecting the most optimal seam based on the calculation of the Lyapunov exponents is presented. In simulating the proposed method, two datasets MSRA and RetargetMe have been used, which use two statistical opinions criteria and aspect ratio similarity (ARS) to evaluate the performance of the proposed method. Simulation results based on dynamical systems analysis showed that the proposed algorithm performs better than the classical seam-carving and generalized seam-carving algorithms.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

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

Similar content being viewed by others

References

  1. Avidan S, Shamir A (2007) Seam carving for content-aware image resizing. In: ACM Transactions on graphics (TOG), vol 26. ACM, p 10

  2. Ayubi P, Setayeshi S, Rahmani AM (2020) Deterministic chaos game: a new fractal based pseudo-random number generator and its cryptographic application. J Inf Secur Appl 52:102472

    Google Scholar 

  3. Ayubi P, Jafari Barani M, Yousefi Valandar M, Yosefnezhad Irani B, Sedagheh Maskan Sadigh R (2021) A new chaotic complex map for robust video watermarking. Artif Intell Rev 54(2):1237–1280

    Article  Google Scholar 

  4. Achanta R, Süsstrunk S (2009) Saliency detection for content-aware image resizing. In: 2009 16th IEEE international conference on image processing (ICIP). IEEE, pp 1005–1008

  5. Arar M, Danon D, Cohen-Or D, Shamir A Image resizing by reconstruction from deep features. arXiv:1904.08475

  6. Abebe MA, Hardeberg JY (2018) Application of radial basis function interpolation for content aware image retargeting. In: 2018 14th international conference on signal-image technology & internet-based systems (SITIS). IEEE, pp 174–183

  7. Bansal M, Kumar M, Kumar M, Kumar K (2021) An efficient technique for object recognition using shi-tomasi corner detection algorithm. Soft Comput 25(6):4423–4432

    Article  Google Scholar 

  8. Barani MJ, Ayubi P, Valandar MY, Irani BY (2020) A new pseudo random number generator based on generalized newton complex map with dynamic key. J Inf Secur Appl 53:102509

    Google Scholar 

  9. Battiato S, Farinella GM, Puglisi G, Ravi D (2014) Saliency-based selection of gradient vector flow paths for content aware image resizing. IEEE Trans Image Process 23(5):2081–2095

    Article  MathSciNet  MATH  Google Scholar 

  10. Chhabra P, Garg NK, Kumar M (2020) Content-based image retrieval system using orb and sift features. Neural Comput Appl 32(7):2725–2733

    Article  Google Scholar 

  11. Chen L-Q, Xie X, Fan X, Ma W-Y, Zhang H-J, Zhou H-Q (2003) A visual attention model for adapting images on small displays. Multimed Syst 9(4):353–364

    Article  Google Scholar 

  12. Cheng Z, Yang Q, Sheng B (2015) Deep colorization. In: Proceedings of the IEEE international conference on computer vision, pp 415–423

  13. Choi J, Kim C (2016) Sparse seam-carving for structure preserving image retargeting. J Sig Process Syst 85(2):275–283

    Article  Google Scholar 

  14. Cho D, Park J, Oh T-H, Tai Y-W, So Kweon I (2017) Weakly-and self-supervised learning for content-aware deep image retargeting. In: Proceedings of the IEEE international conference on computer vision, pp 4558–4567

  15. Cui J, Cai Q, Lu H, Jia Z, Tang M (2020) Distortion-aware image retargeting based on continuous seam carving model. Sig Process 166:107242

    Article  Google Scholar 

  16. Farri E, Ayubi P (2022) A robust digital video watermarking based on ct-svd domain and chaotic dna sequences for copyright protection. J Ambient Intell Humaniz Comput, 1–25

  17. Fu H, Liang F, Lei B, Zhang Q, Liang J, Tu C, Zhang G (2021) An extended context-based entropy hybrid modeling for image compression. Sig Process: Image Commun , 116244

  18. Gal R, Sorkine O, Cohen-Or D (2006) Feature-aware texturing. Rendering Techniques 2006(17th):2

    Google Scholar 

  19. Garg D, Garg NK, Kumar M (2018) Underwater image enhancement using blending of clahe and percentile methodologies. Multimed Tools Appl 77 (20):26545–26561

    Article  Google Scholar 

  20. Goferman S, Zelnik-Manor L, Tal A (2011) Context-aware saliency detection. IEEE Trans Pattern Anal Mach Intell 34(10):1915–1926

    Article  Google Scholar 

  21. Guo DJ, Ding J, Tang J, Xu M, Zhao C (2015) Nif-based seam carving for image resizing. Multimed Syst 21(6):603–613

    Article  Google Scholar 

  22. Guo Y, Liu F, Shi J, Zhou Z-H, Gleicher M (2009) Image retargeting using mesh parametrization. IEEE Trans Multimed 11(5):856–867

    Article  Google Scholar 

  23. Gupta S, Thakur K, Kumar M (2021) 2d-human face recognition using sift and surf descriptors of face’s feature regions. Vis Comput 37(3):447–456

    Article  Google Scholar 

  24. Gupta S, Kumar M, Garg A (2019) Improved object recognition results using sift and orb feature detector. Multimed Tools Appl 78(23):34157–34171

    Article  Google Scholar 

  25. Han D, Sonka M, Bayouth J, Wu X (2010) Optimal multiple-seams search for image resizing with smoothness and shape prior. Vis Comput 26(6-8):749–759

    Article  Google Scholar 

  26. Hashemzadeh M, Asheghi B, Farajzadeh N (2019) Content-aware image resizing: an improved and shadow-preserving seam carving method. Sig Process 155:233–246

    Article  Google Scholar 

  27. Ito I (2016) Gradient-based global features for seam carving. EURASIP J Image Video Proces 2016(1):1–9

    Article  Google Scholar 

  28. Itti L, Koch C, Niebur E (1998) A model of saliency-based visual attention for rapid scene analysis. IEEE Trans Pattern Anal Mach Intell (11),1254–1259

  29. Jin Y, Liu L, Wu Q (2010) Nonhomogeneous scaling optimization for realtime image resizing. Vis Comput 26(6-8):769–778

    Article  Google Scholar 

  30. Kantz H (1994) A robust method to estimate the maximal lyapunov exponent of a time series. Phys Lett A 185(1):77–87

    Article  MathSciNet  Google Scholar 

  31. Kantz H, Schreiber T (2004) Nonlinear time series analysis. vol 7. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  32. Kumar M, Chhabra P, Garg NK (2018) An efficient content based image retrieval system using bayesnet and k-nn. Multimed Tools Appl 77(16):21557–21570

    Article  Google Scholar 

  33. Krähenbühl P, Lang M, Hornung A, Gross M (2009) A system for retargeting of streaming video. In: ACM SIGGRAPH Asia 2009 papers, pp 1–10

  34. Li X, Ling H (2009) Learning based thumbnail cropping. In: 2009 IEEE international conference on multimedia and expo. IEEE, pp 558–561

  35. Li Y, Xia M, Liu X, Yang G (2020) Identification of various image retargeting techniques using hybrid features. J Inf Secur Appl 51:102459

    Google Scholar 

  36. Lin J, Zhou T, Chen Z (2019) Deepir: a deep semantics driven framework for image retargeting. In: 2019 IEEE international conference on multimedia & expo workshops (ICMEW). IEEE, pp 54–59

  37. Liu F, Gleicher M (2005) Automatic image retargeting with fisheye-view warping. In: Proceedings of the 18th annual ACM symposium on User interface software and technology. ACM, pp 153–162

  38. Luo Y, Yuan J, Xue P, Tian Q (2011) Saliency density maximization for efficient visual objects discovery. IEEE Trans Circ Syst video Technol 21 (12):1822–1834

    Article  Google Scholar 

  39. Msra10k salient object database. https://mmcheng.net/msra10k/. Accessed 2022

  40. Niu Y, Liu F, Li X, Gleicher M (2012) Image resizing via non-homogeneous warping. Multimed Tools Appl 56(3):485–508

    Article  Google Scholar 

  41. Nishiyama M, Okabe T, Sato Y, Sato I (2009) Sensation-based photo cropping. In: Proceedings of the 17th ACM international conference on Multimedia. ACM, pp 669–672

  42. Pritch Y, Kav-Venaki E, Peleg S (2009) Shift-map image editing. In: 2009 IEEE 12th international conference on computer vision. IEEE, pp 151–158

  43. Rosenstein MT, Collins JJ, De Luca CJ (1993) A practical method for calculating largest lyapunov exponents from small data sets. Physica D: Nonlinear Phenom 65(1-2):117–134

    Article  MathSciNet  MATH  Google Scholar 

  44. Rubinstein M, Shamir A, Avidan S (2008) Improved seam carving for video retargeting. In: ACM transactions on graphics (TOG), vol 27. ACM, p 16

  45. Rubinstein M, Shamir A, Avidan S (2009) Multi-operator media retargeting. ACM Trans graph (TOG) 28(3):1–11

    Article  Google Scholar 

  46. Rubinstein M, Gutierrez D, Sorkine O, Shamir A (2010) A comparative study of image retargeting. In: ACM SIGGRAPH Asia 2010 papers, pp 1–10

  47. Retargetme dataset. https://people.csail.mit.edu/mrub/retargetme/download.html. Accessed 2022

  48. Santella A, Agrawala M, DeCarlo D, Salesin D, Cohen M (2006) Gaze-based interaction for semi-automatic photo cropping. In: Proceedings of the SIGCHI conference on Human Factors in computing systems. ACM, pp 771–780

  49. Suh B, Ling H, Bederson BB, Jacobs DW (2003) Automatic thumbnail cropping and its effectiveness. In: Proceedings of the 16th annual ACM symposium on User interface software and technology. ACM, pp 95–104

  50. Shafieyan F, Karimi N, Mirmahboub B, Samavi S, Shirani S (2017) Image retargeting using depth assisted saliency map. Sig Process Image Commun 50:34–43

    Article  Google Scholar 

  51. Shannon CE (1949) Communication theory of secrecy systems. Bell Syst Techn J 28(4):656–715

    Article  MathSciNet  MATH  Google Scholar 

  52. Shamir A, Avidan S (2009) Seam carving for media retargeting. Commun ACM 52(1):77–85

    Article  Google Scholar 

  53. Song E, Lee M, Lee S (2018) Carvingnet: content-guided seam carving using deep convolution neural network. IEEE Access 7:284–292

    Article  Google Scholar 

  54. Tan W, Yan B, Lin C, Niu X (2019) Cycle-ir: deep cyclic image retargeting. IEEE Trans Multimed 22(7):1730–1743

    Article  Google Scholar 

  55. Valandar MY, Ayubi P, Barani MJ, Irani BY (2022) A chaotic video steganography technique for carrying different types of secret messages. J Inf Sec Appl 66:103160

    Google Scholar 

  56. Wu C, Kang Z (2021) Robust entropy-based symmetric regularized picture fuzzy clustering for image segmentation. Digit Sig Process 110:102905

    Article  Google Scholar 

  57. Wang Y-S, Tai C-L, Sorkine O, Lee T-Y (2008) Optimized scale-and-stretch for image resizing. In: ACM transactions on graphics (TOG), vol 27. ACM, p 118

  58. Wolf A, Swift JB, Swinney HL, Vastano JA (1985) Determining lyapunov exponents from a time series. Physica D: Nonlinear Phenom 16(3):285–317

    Article  MathSciNet  MATH  Google Scholar 

  59. Xie J, Xu L, Chen E (2012) Image denoising and inpainting with deep neural networks. In: Advances in neural information processing systems, pp 341–349

  60. Xu L, Ren JS, Liu C, Jia J (2014) Deep convolutional neural network for image deconvolution. In: Advances in neural information processing systems, pp 1790–1798

  61. Xu N, Price B, Cohen S, Huang T (2017) Deep image matting. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2970–2979

  62. Ye J, Shi Y-Q (2017) An effective method to detect seam carving. J Inf Secur Appl 35:13–22

    Google Scholar 

  63. Yin T, Yang G, Li L, Zhang D, Sun X (2015) Detecting seam carving based image resizing using local binary patterns. Comput Secur 55:130–141

    Article  Google Scholar 

  64. Yosefnezhad Irani B, Ayubi P, Amani Jabalkandi F, Yousefi Valandar M, Jafari Barani M (2019) Digital image scrambling based on a new one-dimensional coupled sine map. Nonlinear Dyn 97(4):2693–2721

    Article  MATH  Google Scholar 

  65. Zhang M, Zhang L, Sun Y, Feng L, Ma W (2005) Auto cropping for digital photographs. In: 2005 IEEE international conference on multimedia and expo. IEEE, p 4

  66. Zhang G-X, Cheng M-M, Hu S-M, Martin RR (2009) A shape-preserving approach to image resizing. In: Computer graphics forum. Wiley Online Library, pp 1897–1906

  67. Zhang L, Li K, Ou Z, Wang F (2017) Seam warping: a new approach for image retargeting for small displays. Soft Comput 21(2):447–457

    Article  Google Scholar 

  68. Zhang Y, Lin W, Zhang X, Fang Y, Li L (2016) Aspect ratio similarity (ars) for image retargeting quality assessment. In: 2016 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, pp 1080–1084

  69. Zhang D, Li Q, Yang G, Li L, Sun X (2017) Detection of image seam carving by using weber local descriptor and local binary patterns. J Inf Secur Appl 36:135–144

    Google Scholar 

Download references

Acknowledgements

I am dedicated to Imam Reza, who has all my scientific life from his love.

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Urmia University, Urmia, Iran

    Jila Ayubi, Mehdi Chehel Amirani & Morteza Valizadeh

Authors
  1. Jila Ayubi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mehdi Chehel Amirani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Morteza Valizadeh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jila Ayubi.

Ethics declarations

Conflict of Interests

All authors declare that they have no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ayubi, J., Amirani, M.C. & Valizadeh, M. A New Seam Carving Method for Image Resizing Based on Entropy Energy and Lyapunov Exponent. Multimed Tools Appl 82, 19417–19440 (2023). https://doi.org/10.1007/s11042-022-13823-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-022-13823-x

Keywords

Search

Navigation