Next Article in Journal
Self-Supervised Contextual Data Augmentation for Natural Language Processing
Previous Article in Journal
Investigations of Laser Produced Plasmas Generated by Laser Ablation on Geomaterials. Experimental and Theoretical Aspects
Previous Article in Special Issue
A Multi-Stage Homotopy Perturbation Method for the Fractional Lotka-Volterra Model
Open AccessArticle

Improved Image Splicing Forgery Detection by Combination of Conformable Focus Measures and Focus Measure Operators Applied on Obtained Redundant Discrete Wavelet Transform Coefficients

1
Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia
2
Informetrics Research Group, Ton Duc Thang University, 758307, Ho Chi Minh, Vietnam
3
Faculty of Mathematics & Statistics, Ton Duc Thang University, 758307, Ho Chi Minh, Vietnam
*
Author to whom correspondence should be addressed.
Symmetry 2019, 11(11), 1392; https://doi.org/10.3390/sym11111392 (registering DOI)
Received: 8 October 2019 / Revised: 2 November 2019 / Accepted: 7 November 2019 / Published: 10 November 2019
(This article belongs to the Special Issue Recent Advances in Discrete and Fractional Mathematics)
The image is the best information carrier in the current digital era and the easiest to manipulate. Image manipulation causes the integrity of this information carrier to be ambiguous. The image splicing technique is commonly used to manipulate images by fusing different regions in one image. Over the last decade, it has been confirmed that various structures in science and engineering can be demonstrated more precisely by fractional calculus using integrals or derivative operators. Many fractional-order-based techniques have been used in the image-processing field. Recently, a new specific fractional calculus, called conformable calculus, was delivered. Herein, we employ the combination of conformable focus measures (CFMs), and focus measure operators (FMOs) in obtaining redundant discrete wavelet transform (RDWT) coefficients for improving the image splicing forgery detection. The process of image splicing disorders the content of tampered image and causes abnormality in the image features. The spliced region’s boundaries are usually blurring to avoid detection. To make use of the blurred information, both CFMs and FMOs are used to calculate the degree of blurring of the tampered region’s boundaries for image splicing detection. The two public image datasets IFS-TC and CASIA TIDE V2 are used for evaluation of the proposed method. The obtained results of the proposed method achieved accuracy rate 98.30% for Cb channel on IFS-TC image dataset and 98.60% of the Cb channel on CASIA TIDE V2 with 24-D feature vector. The proposed method exhibited superior results compared with other image splicing detection methods.
Keywords: image splicing; fractional calculus; conformable calculus; RDWT; focus image splicing; fractional calculus; conformable calculus; RDWT; focus
MDPI and ACS Style

Subramaniam, T.; Jalab, H.A.; Ibrahim, R.W.; Mohd Noor, N.F. Improved Image Splicing Forgery Detection by Combination of Conformable Focus Measures and Focus Measure Operators Applied on Obtained Redundant Discrete Wavelet Transform Coefficients. Symmetry 2019, 11, 1392.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop