Region Duplication Forgery Detection using Histogram of Oriented Gradients

Abstract

Digital images are powerful means of communication and it is widely used in many fields. With the availability of powerful image editing software packages altering of digital images is done. The use of digital images in law enforcement and forensics necessitates the development of efficient forgery detection technique to prove the reliability and authenticity of image. The most common type of image forgery is copy move forgery or region duplication. In this type of forgery, one region of image is copied and pasted somewhere else in the image. Main aim of this type of forgery is to hide some important information. Tampered images may affect the statistical properties of the image which is used to detect forgery. In this paper, we propose a block based approach in which discrete wavelet transform is applied to the input image. Then the image is divided into overlapping blocks. Discriminative features are extracted by applying histogram of gradients to each block. These features are lexicographically sorted and duplicated blocks are detected after applying block matching step. Experimental results show that the proposed method can identify the forged region in the images very efficiently.