Skip to main content
Log in

Comparison between images via bilinear fuzzy relation equations

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

We present a comparison between two images A and B based on the greatest solution of a system of bilinear fuzzy relation equations A○x = B○x, where “○” is the max–min composition, being A and B known as fuzzy relations and x is unknown. Here A and B are images considered as fuzzy relations being their pixels normalized in [0, 1] with respect to the grey scale used. Due to symmetry of every equation involved, A (resp., B) could be the original image and B (resp., A) is an image modified of A (resp., B), for instance, either noised or watermarked. The comparison is made by using an index which is more robust than other two indices used in previous works: the first one is based on the greatest eigen fuzzy set (with respect to max–min composition) and smallest eigen fuzzy set (with respect to min–max composition) and the second one is based on the Lukasiewicz triangular norm. The comparison is made between the original image and the same image with noise introduced at several values σ of the standard deviation.

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

Similar content being viewed by others

References

Download references

Acknowledgements

We perform this research under the auspices of the INDAM-GCNS, Italy.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Salvatore Sessa.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Di Martino, F., Sessa, S. Comparison between images via bilinear fuzzy relation equations. J Ambient Intell Human Comput 9, 1517–1525 (2018). https://doi.org/10.1007/s12652-017-0576-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-017-0576-3

Keywords

Navigation