A novel passive forgery detection algorithm for video region duplication

2017 ◽  
Vol 29 (3) ◽  
pp. 1173-1190 ◽  
Author(s):  
Lichao Su ◽  
Cuihua Li
Keyword(s):  
Detection Algorithm ◽  
Forgery Detection ◽  
Region Duplication

A Fast Forgery Detection Algorithm Based on Exponential-Fourier Moments for Video Region Duplication

2018 ◽  
Vol 20 (4) ◽  
pp. 825-840 ◽  
Author(s):  
Lichao Su ◽  
Cuihua Li ◽  
Yuecong Lai ◽  
Jianmei Yang
Keyword(s):  
Detection Algorithm ◽  
Forgery Detection ◽  
Region Duplication

scholarly journals Copy-Move Forgery Detection Using Scale Invariant Feature and Reduced Local Binary Pattern Histogram

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 492 ◽  
Author(s):  
Jun Young Park ◽  
Tae An Kang ◽  
Yong Ho Moon ◽  
Il Kyu Eom
Keyword(s):  
Local Binary Pattern ◽  
Detection Algorithm ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Forgery Detection ◽  
Scale Invariant ◽  
Region Duplication ◽  
Invariant Feature ◽  
Copy Move Forgery Detection ◽  
Scale Invariant Feature

Because digitized images are easily replicated or manipulated, copy-move forgery techniques are rendered possible with minimal expertise. Furthermore, it is difficult to verify the authenticity of images. Therefore, numerous efforts have been made to detect copy-move forgeries. In this paper, we present an improved region duplication detection algorithm based on the keypoints. The proposed algorithm utilizes the scale invariant feature transform (SIFT) and the reduced local binary pattern (LBP) histogram. The LBP values with 256 levels are obtained from the local window centered at the keypoint, which are then reduced to 10 levels. For a keypoint, a 138-dimensional is generated to detect copy-move forgery. We test the proposed algorithm on various image datasets and compare the detection accuracy with those of existing methods. The experimental results demonstrate that the performance of the proposed scheme is superior to that of other tested copy-move forgery detection methods. Furthermore, the proposed method exhibits a uniform detection performance for various types of test datasets.

scholarly journals A Keypoint-Based Region Duplication Forgery Detection Algorithm

2016 ◽  
Vol E99.D (9) ◽  
pp. 2413-2416
Author(s):  
Mahmoud EMAM ◽  
Qi HAN ◽  
Liyang YU ◽  
Hongli ZHANG
Keyword(s):  
Detection Algorithm ◽  
Forgery Detection ◽  
Region Duplication

scholarly journals Image Region Duplication Forgery Detection Based on Angular Radial Partitioning and Harris Key-Points

Symmetry ◽  
2016 ◽  
Vol 8 (7) ◽  
pp. 62 ◽  
Author(s):  
Diaa Uliyan ◽  
Hamid Jalab ◽  
Ainuddin Abdul Wahab ◽  
Somayeh Sadeghi
Keyword(s):  
Forgery Detection ◽  
Image Region ◽  
Region Duplication ◽  
Key Points
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