A copy-move image forgery detection technique based on tetrolet transform

2020 ◽  
Vol 52 ◽  
pp. 102481
Author(s):  
Kunj Bihari Meena ◽  
Vipin Tyagi
Keyword(s):  
Detection Technique ◽  
Forgery Detection ◽  
Image Forgery ◽  
Image Forgery Detection ◽  
Tetrolet Transform

scholarly journals CLIFD: A novel image forgery detection technique using digital signatures

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Sahib Khan ◽  
◽  
Arslan Ali ◽  
Keyword(s):  
Digital Signature ◽  
Digital Signatures ◽  
Detection Technique ◽  
Forgery Detection ◽  
Image Forgery ◽  
Signature Generation ◽  
Image Forgery Detection ◽  
Substitution Mechanism ◽  
Different Types ◽  
Message Digest

The paper presents a new image forgery detection technique. The proposed technique uses digital signatures; it generates a digital signature for each column and embeds the signature in the least significant bits of each corresponding column’s selected pixels. The message digest algorithm 5 (MD5) is used for digital signature generation, and the fourleast-significant-bit substitution mechanism is used to embed the signature in the designated pixels. The embedding of the digital signature in the selected pixel remains completely innocent and undetectable for the human visual system. The proposed forgery detection technique has demonstrated significant results against different types of forgeries introduced to digital images and successfully detected and pointed out the forged columns.

Image Forgery Detection Based on Trigonometric Transforms

2019 ◽  
Vol 28 (2) ◽  
pp. 203-216
Author(s):  
Faten Al-Azrak ◽  
Moawad Dessouky ◽  
Fathi Abd El-Samie ◽  
Ahmed Elkorany ◽  
Zeinab Elsharkawy
Keyword(s):  
Forgery Detection ◽  
Image Forgery ◽  
Image Forgery Detection ◽  
Trigonometric Transforms
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