Image forensic for digital image copy move forgery detection

• Published in: 2018 IEEE 14th International Colloquium on Signal Processing & Its Applications (CSPA) pp. 239 - 244
• Main Authors: Yeap, Yong Yew, Sheikh, U.U., Ab Rahman, Ab Al-Hadi
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.03.2018
• Subjects: Copy Move Forgery Detection; Correlation; Digital images; Feature extraction; Forgery; image forensics; Oriented FAST; Robustness; rotated BRIEF; Signal processing
• DOI: 10.1109/CSPA.2018.8368719

In recent years, digital image forgery detection has become an active research area due to the advancement of photo editing software. This paper focuses on passive forgery detection on images tampered using copy move technique, better known as Copy Move Forgery Detection (CMFD). A CMFD technique consisting of oriented Features from Accelerated Segment Test and rotated Binary Robust Independent Elementary Features (Oriented FAST and rotated BRIEF) as the feature extraction method and 2 Nearest Neighbour (2NN) with Hierarchical Agglomerative Clustering (HAC) as the feature matching method is proposed. Evaluation of the proposed CMFD technique was performed on images that underwent various geometrical attacks. With the proposed technique, an overall accuracy rate of 84.33% and 82.79% are obtained for evaluation carried out with images from the MICC-F600 and MICC-F2000 databases. Forgery detection achieved True Positive Rate of more than 91% for tampered images with object translation, different degree of rotation and enlargement.