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Blind Detection of Region Duplication Forgery Using Fractal Coding and Feature Matching
Mohsen Jenadeleh1, Mohsen Ebrahimi Moghaddam1
1Faculty of Computer Science and Engineering, Shahid Beheshti University, G.C., Evin, Tehran, Iran.
Journal of Forensic Sciences
|April 29, 2016
Summary
This study introduces a novel blind detection method for digital image copy-move forgery. The technique effectively identifies duplicated regions, even after complex manipulations and common image attacks.
Area of Science:
- Computer Science
- Digital Forensics
- Image Processing
Background:
- Digital image forgery, particularly copy-move manipulation, poses a significant threat in various fields.
- Existing detection methods struggle with sophisticated forgeries created by advanced software and post-processing operations.
Purpose of the Study:
- To develop a robust blind detection method for copy-move image forgery.
- To address limitations of current algorithms in detecting complex and post-processed forgeries.
Main Methods:
- A novel approach combining modified fractal coding and feature vector matching for forgery detection.
- Implementation of techniques to identify duplicated regions subjected to rotation, scaling, and reflection.
Main Results:
- The proposed method successfully detects typical copy-move forgeries.
- It effectively identifies multiple copied regions even after various transformations and common image attacks like blurring and contrast adjustments.
Conclusions:
- The developed method offers a valid and efficient solution for blind copy-move forgery detection.
- It demonstrates robustness against a range of image manipulations and post-processing operations.
