Robust Adaptable Segmentation-Based Copy Move Forgery Detection Method

2020 ◽  
pp. 723-733
Author(s):  
R. Dhanya ◽  
R. KalaiSelvi
Keyword(s):  
Detection Method ◽  
Forgery Detection ◽  
Copy Move Forgery Detection

scholarly journals Copy move forgery detection using key point localized super pixel based on texture features

2019 ◽  
Vol 43 (2) ◽  
pp. 270-276
Author(s):  
C. Rajalakshmi ◽  
Al.M. Germanus ◽  
R. Balasubramanian
Keyword(s):  
Detection Method ◽  
Texture Features ◽  
Experimental Result ◽  
Forgery Detection ◽  
Scale Invariant ◽  
Image Forensic ◽  
Important Barrier ◽  
Copy Move Forgery Detection ◽  
Yield Good Result ◽  
Scale Invariant Feature

The most important barrier in the image forensic is to ensue a forgery detection method such can detect the copied region which sustains rotation, scaling reflection, compressing or all. Traditional SIFT method is not good enough to yield good result. Matching accuracy is not good. In order to improve the accuracy in copy move forgery detection, this paper suggests a forgery detection method especially for copy move attack using Key Point Localized Super Pixel (KLSP). The proposed approach harmonizes both Super Pixel Segmentation using Lazy Random Walk (LRW) and Scale Invariant Feature Transform (SIFT) based key point extraction. The experimental result indicates the proposed KLSP approach achieves better performance than the previous well known approaches.

scholarly journals An Image Copy-Move Forgery Detection Method Based on SURF and PCET

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 170032-170047 ◽  
Author(s):  
Chengyou Wang ◽  
Zhi Zhang ◽  
Qianwen Li ◽  
Xiao Zhou
Keyword(s):  
Detection Method ◽  
Forgery Detection ◽  
Copy Move Forgery Detection
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