Next Article in Journal
Modeling and Analysis of Entropy Generation in Light Heating of Nanoscaled Silicon and Germanium Thin Films
Next Article in Special Issue
Fractional State Space Analysis of Economic Systems
Previous Article in Journal / Special Issue
H Control for Markov Jump Systems with Nonlinear Noise Intensity Function and Uncertain Transition Rates
Article Menu

Export Article

Open AccessArticle
Entropy 2015, 17(7), 4775-4785; doi:10.3390/e17074775

Fractional Differential Texture Descriptors Based on the Machado Entropy for Image Splicing Detection

1
Institute of Mathematical Sciences, University of Malaya, 50603 Kuala Lumpur, Malaysia
2
Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia
*
Author to whom correspondence should be addressed.
Academic Editors: J. A. Tenreiro Machado and António M. Lopes
Received: 19 May 2015 / Revised: 2 July 2015 / Accepted: 3 July 2015 / Published: 8 July 2015
(This article belongs to the Special Issue Complex and Fractional Dynamics)
View Full-Text   |   Download PDF [872 KB, uploaded 8 July 2015]   |  

Abstract

Image splicing is a common operation in image forgery. Different techniques of image splicing detection have been utilized to regain people’s trust. This study introduces a texture enhancement technique involving the use of fractional differential masks based on the Machado entropy. The masks slide over the tampered image, and each pixel of the tampered image is convolved with the fractional mask weight window on eight directions. Consequently, the fractional differential texture descriptors are extracted using the gray-level co-occurrence matrix for image splicing detection. The support vector machine is used as a classifier that distinguishes between authentic and spliced images. Results prove that the achieved improvements of the proposed algorithm are compatible with other splicing detection methods. View Full-Text
Keywords: fractional differential; Machado entropy; image splicing; feature extraction; dimension reduction; support vector machine fractional differential; Machado entropy; image splicing; feature extraction; dimension reduction; support vector machine
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Ibrahim, R.W.; Moghaddasi, Z.; Jalab, H.A.; Noor, R.M. Fractional Differential Texture Descriptors Based on the Machado Entropy for Image Splicing Detection. Entropy 2015, 17, 4775-4785.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top