MCS research paper for Copy-Move Forgery Detection Based on Automatic Threshold Estimation

This is one of my MCS research papers published in International Journal of Sociotechnology and Knowledge Development (IJSKD). Most clustering techniques highly depend on the existence of a specific threshold to terminate the clustering. Determination of the most suitable threshold requires a huge amount of experiments. In this article, a copy-move forgery detection method is proposed. The proposed method is based on automatic estimation of the clustering threshold. The cutoff threshold of hierarchical clustering is estimated automatically based on clustering evaluation measures. Experimental results tested on various datasets show that the proposed method outperforms other relevant state-of-the-art methods.