Perceptual Hashing-Based Image Copy-Move Forgery Detection
Joint Authors
Source
Security and Communication Networks
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-01-22
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Information Technology and Computer Science
Abstract EN
This paper proposes a blind authentication scheme to identify duplicated regions for copy-move forgery based on perceptual hashing and package clustering algorithms.
For all fixed-size image blocks in suspicious images, discrete cosine transform (DCT) is used to obtain their DCT coefficient matrixes.
Their perceptual hash matrixes and perceptual hash feature vectors are orderly addressed.
Moreover, a package clustering algorithm is proposed to replace traditional lexicographic order algorithms for improving the detection precision.
Similar blocks can be identified by matching the perceptual hash feature vectors in each package and its adjacent package.
The experimental results show that the proposed scheme can locate irregular tampered regions and multiple duplicated regions in suspicious images although they are distorted by some hybrid trace hiding operations, such as adding white Gaussian noise and Gaussian blurring, adjusting contrast ratio, luminance, and hue, and their hybrid operations.
American Psychological Association (APA)
Wang, Huan& Wang, Hongxia. 2018. Perceptual Hashing-Based Image Copy-Move Forgery Detection. Security and Communication Networks،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1214308
Modern Language Association (MLA)
Wang, Huan& Wang, Hongxia. Perceptual Hashing-Based Image Copy-Move Forgery Detection. Security and Communication Networks No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1214308
American Medical Association (AMA)
Wang, Huan& Wang, Hongxia. Perceptual Hashing-Based Image Copy-Move Forgery Detection. Security and Communication Networks. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1214308
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1214308