Keypoint-Based Copy-Move Area Detection

Identifying which part of the image has been manipulated in real-world photo is a challenging research area. Generally, images are tampered using image editing tools to hide the information from pictures and to mislead people by providing wrong information intentionally. The authenticity of images becomes crucial to check for whether the image has been tampered before extracting meaningful information from images. In his paper, copy-move forgery area detection, one of several tampering techniques, has been presented based on identifying Scale-Invariant Feature Transform (SIFT) keypoints in an image. Preprocessing is done using fuzzy contrast enhancement. Features are extracted using SIFT algorithm and identical portions are clustered using Density-Based Spatial Clustering Application with Noise (DBSCAN) clustering. The experiments are performed on MICC-F220 dataset and results obtained are compared with other methods in the literature.