DBSCAN-Copy-Move-Foregry-Detection

Summary:

Copy move forgery detection using DBSCAN clustering algorithm. If you want to read about the approach here is my article on medium: https://medium.com/@jainh246/copy-move-forgery-detection-using-sift-and-dbscan-clustering-4a179c36293e?source=friends_link&sk=2e2c61feeade3753b82347c851594ec1

And here is a jyputer notebook version https://www.kaggle.com/himj26/copy-move-forgery-detection-dbscan-clustering .

Requirements

• Python3
• OpenCV (pip install opencv-python)
• OpenCV-contrib-python https://stackoverflow.com/questions/60065707/cant-use-sift-in-opencv-v4-20?noredirect=1&lq=1
• Sklearn (pip install -U scikit-learn)

How To Run

Type this command in the terminal. (See examples for complete idea)

python main.py "path to the image" eps min_samples

• (Mandatory) "path to the image" - this is the exact path to the image file (See examples).
• (Optional) eps - Eps value for DBSCAN algorithm. Increasing this will generate more clusters.(Value should be between 0-500)
• (Optional) min_samples - Min sample for DBSCAN algorithm. Increasing this will reduce clusters.(Value should be between 0-50).

After running press 'S/s' if you want to save the forgery detected image. Press 'Q/q' to exit. (Make sure You have Selected the image window while pressing keys).

Examples

Example 1

Example 2