Cargando…

Statistical Assessment of Discrimination Capabilities of a Fractional Calculus Based Image Watermarking System for Gaussian Watermarks

In this paper, we explore the advantages of a fractional calculus based watermarking system for detecting Gaussian watermarks. To reach this goal, we selected a typical watermarking scheme and replaced the detection equation set by another set of equations derived from fractional calculus principles...

Descripción completa

Detalles Bibliográficos
Autores principales: Gonzalez-Lee, Mario, Vazquez-Leal, Hector, Morales-Mendoza, Luis J., Nakano-Miyatake, Mariko, Perez-Meana, Hector, Laguna-Camacho, Juan R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7927010/
https://www.ncbi.nlm.nih.gov/pubmed/33672152
http://dx.doi.org/10.3390/e23020255
_version_ 1783659593889480704
author Gonzalez-Lee, Mario
Vazquez-Leal, Hector
Morales-Mendoza, Luis J.
Nakano-Miyatake, Mariko
Perez-Meana, Hector
Laguna-Camacho, Juan R.
author_facet Gonzalez-Lee, Mario
Vazquez-Leal, Hector
Morales-Mendoza, Luis J.
Nakano-Miyatake, Mariko
Perez-Meana, Hector
Laguna-Camacho, Juan R.
author_sort Gonzalez-Lee, Mario
collection PubMed
description In this paper, we explore the advantages of a fractional calculus based watermarking system for detecting Gaussian watermarks. To reach this goal, we selected a typical watermarking scheme and replaced the detection equation set by another set of equations derived from fractional calculus principles; then, we carried out a statistical assessment of the performance of both schemes by analyzing the Receiver Operating Characteristic (ROC) curve and the False Positive Percentage (FPP) when they are used to detect Gaussian watermarks. The results show that the ROC of a fractional equation based scheme has 48.3% more Area Under the Curve (AUC) and a False Positives Percentage median of 0.2% whilst the selected typical watermarking scheme has 3%. In addition, the experimental results suggest that the target applications of fractional schemes for detecting Gaussian watermarks are as a semi-fragile image watermarking systems robust to Gaussian noise.
format Online
Article
Text
id pubmed-7927010
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-79270102021-03-04 Statistical Assessment of Discrimination Capabilities of a Fractional Calculus Based Image Watermarking System for Gaussian Watermarks Gonzalez-Lee, Mario Vazquez-Leal, Hector Morales-Mendoza, Luis J. Nakano-Miyatake, Mariko Perez-Meana, Hector Laguna-Camacho, Juan R. Entropy (Basel) Article In this paper, we explore the advantages of a fractional calculus based watermarking system for detecting Gaussian watermarks. To reach this goal, we selected a typical watermarking scheme and replaced the detection equation set by another set of equations derived from fractional calculus principles; then, we carried out a statistical assessment of the performance of both schemes by analyzing the Receiver Operating Characteristic (ROC) curve and the False Positive Percentage (FPP) when they are used to detect Gaussian watermarks. The results show that the ROC of a fractional equation based scheme has 48.3% more Area Under the Curve (AUC) and a False Positives Percentage median of 0.2% whilst the selected typical watermarking scheme has 3%. In addition, the experimental results suggest that the target applications of fractional schemes for detecting Gaussian watermarks are as a semi-fragile image watermarking systems robust to Gaussian noise. MDPI 2021-02-23 /pmc/articles/PMC7927010/ /pubmed/33672152 http://dx.doi.org/10.3390/e23020255 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gonzalez-Lee, Mario
Vazquez-Leal, Hector
Morales-Mendoza, Luis J.
Nakano-Miyatake, Mariko
Perez-Meana, Hector
Laguna-Camacho, Juan R.
Statistical Assessment of Discrimination Capabilities of a Fractional Calculus Based Image Watermarking System for Gaussian Watermarks
title Statistical Assessment of Discrimination Capabilities of a Fractional Calculus Based Image Watermarking System for Gaussian Watermarks
title_full Statistical Assessment of Discrimination Capabilities of a Fractional Calculus Based Image Watermarking System for Gaussian Watermarks
title_fullStr Statistical Assessment of Discrimination Capabilities of a Fractional Calculus Based Image Watermarking System for Gaussian Watermarks
title_full_unstemmed Statistical Assessment of Discrimination Capabilities of a Fractional Calculus Based Image Watermarking System for Gaussian Watermarks
title_short Statistical Assessment of Discrimination Capabilities of a Fractional Calculus Based Image Watermarking System for Gaussian Watermarks
title_sort statistical assessment of discrimination capabilities of a fractional calculus based image watermarking system for gaussian watermarks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7927010/
https://www.ncbi.nlm.nih.gov/pubmed/33672152
http://dx.doi.org/10.3390/e23020255
work_keys_str_mv AT gonzalezleemario statisticalassessmentofdiscriminationcapabilitiesofafractionalcalculusbasedimagewatermarkingsystemforgaussianwatermarks
AT vazquezlealhector statisticalassessmentofdiscriminationcapabilitiesofafractionalcalculusbasedimagewatermarkingsystemforgaussianwatermarks
AT moralesmendozaluisj statisticalassessmentofdiscriminationcapabilitiesofafractionalcalculusbasedimagewatermarkingsystemforgaussianwatermarks
AT nakanomiyatakemariko statisticalassessmentofdiscriminationcapabilitiesofafractionalcalculusbasedimagewatermarkingsystemforgaussianwatermarks
AT perezmeanahector statisticalassessmentofdiscriminationcapabilitiesofafractionalcalculusbasedimagewatermarkingsystemforgaussianwatermarks
AT lagunacamachojuanr statisticalassessmentofdiscriminationcapabilitiesofafractionalcalculusbasedimagewatermarkingsystemforgaussianwatermarks