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

Detection of image region-duplication forgery based on gray level co-occurrence matrix

2012 ◽  
Vol 31 (6) ◽  
pp. 1628-1630
Author(s):  
Jia-jia OU ◽  
Bi-ye CAI ◽  
Bing XIONG ◽  
Feng LI
Keyword(s):  
Gray Level ◽  
Image Region ◽  
Region Duplication ◽  
Occurrence Matrix

Copy-Move Forgery Detection Using DyWT

2017 ◽  
Vol 8 (2) ◽  
pp. 1-9
Author(s):  
Choudhary Shyam Prakash ◽  
Sushila Maheshkar
Keyword(s):  
Wavelet Transform ◽  
Input Image ◽  
Discrete Wavelet ◽  
Forgery Detection ◽  
High Similarity ◽  
Dyadic Wavelet ◽  
Region Duplication ◽  
Copy Move Forgery Detection ◽  
Duplication Detection ◽  
Better Than

In this paper, we proposed a passive method for copy-move region duplication detection using dyadic wavelet transform (DyWT). DyWT is better than discrete wavelet transform (DWT) for data analysis as it is shift invariant. Initially we decompose the input image into approximation (LL1) and detail (HH1) sub-bands. Then LL1 and HH1 sub-bands are divided into overlapping sub blocks and find the similarity between the blocks. In LL1 sub-band the copied and moved blocks have high similarity rate than the HH1 sub-band, this is just because, there is noise inconsistency in the moved blocks. Then we sort the LL1 sub-band blocks pair based on high similarity and in HH1 blocks are sorted based on high dissimilarity. Then we apply threshold to get the copied moved blocks. Here we also applied some post processing operations to check the robustness of our method and we get the satisfactory results to validate the copy move forgery detection.

Fast and Robust Forensics for Image Region-duplication Forgery

2010 ◽  
Vol 35 (12) ◽  
pp. 1488-1495 ◽  
Author(s):  
Jun-Wen WANG ◽  
Guang-Jie LIU ◽  
Zhan ZHANG ◽  
Yue-Wei DAI ◽  
Zhi-Quan WANG
Keyword(s):  
Image Region ◽  
Region Duplication

Copy-Move Forgery Detection Using DyWT

2020 ◽  
pp. 117-126
Author(s):  
Choudhary Shyam Prakash ◽  
Sushila Maheshkar
Keyword(s):  
Wavelet Transform ◽  
Input Image ◽  
Discrete Wavelet ◽  
Forgery Detection ◽  
High Similarity ◽  
Dyadic Wavelet ◽  
Region Duplication ◽  
Dyadic Wavelet Transform ◽  
Copy Move Forgery Detection ◽  
Duplication Detection

In this paper, we proposed a passive method for copy-move region duplication detection using dyadic wavelet transform (DyWT). DyWT is better than discrete wavelet transform (DWT) for data analysis as it is shift invariant. Initially we decompose the input image into approximation (LL1) and detail (HH1) sub-bands. Then LL1 and HH1 sub-bands are divided into overlapping sub blocks and find the similarity between the blocks. In LL1 sub-band the copied and moved blocks have high similarity rate than the HH1 sub-band, this is just because, there is noise inconsistency in the moved blocks. Then we sort the LL1 sub-band blocks pair based on high similarity and in HH1 blocks are sorted based on high dissimilarity. Then we apply threshold to get the copied moved blocks. Here we also applied some post processing operations to check the robustness of our method and we get the satisfactory results to validate the copy move forgery detection.

An Image Region Description Method Based on Step Sector Statistics and its Application in Image Copy-Rotate/Flip-Move Forgery Detection

2012 ◽  
Vol 4 (1) ◽  
pp. 49-62 ◽  
Author(s):  
Likai Chen ◽  
Wei Lu ◽  
Jiangqun Ni
Keyword(s):  
Radial Direction ◽  
Rotation Angle ◽  
Experimental Results ◽  
Robust Method ◽  
Forgery Detection ◽  
Image Region ◽  
Feature Description ◽  
Region Description ◽  
Region Feature ◽  
Local Image

A robust method for local image region feature description based on step sector statistics is proposed in this paper. The means and the standard deviations along the radial direction of the circle image region are extracted through the sector masks, and the rearrangement of these statistics makes this image region description method rotation-robust. The proposed description method is applied in the detection of copy-rotate-move forgery, and it can detect the exact rotation angle between the duplicate regions. With minor extension, the proposed description method can also be applied in the detection of copy-flip-move forgery. The experimental results show that the proposed description method can work well for the detection of copy-rotate/flip-move forgery.

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