Detection of copy–move forgery using a method based on blur moment invariants

In our society digital images are a powerful and widely used communication medium. They have an important impact on our life. In recent years, due to the advent of high-performance commodity hardware and improved human–computer interfaces, it has become relatively easy to create fake images. Modern, easy to use image processing software enables forgeries that are undetectable by the naked eye. In this work we propose a method to automatically detect and localize duplicated regions in digital images. The presence of duplicated regions in an image may signify a common type of forgery called copy–move forgery. The method is based on blur moment invariants, which allows successful detection of copy–move forgery, even when blur degradation, additional noise, or arbitrary contrast changes are present in the duplicated regions. These modifications are commonly used techniques to conceal traces of copy–move forgery. Our method works equally well for lossy format such as JPEG. We demonstrate our method on several images affected by copy–move forgery.