Double JPEG Compression Detection Using Statistical Analysis

Abstract

Nowadays with advancement of technology, tampering of digital images using computer and advanced software packages like Photoshop has become a simple task. Many algorithms have been proposed to detect tampered images that have been kept developing. In this regard, verification of accuracy of image content and detection of manipulations in image regardless of any previous knowledge about the image content and can be an important research field. Recently, many efforts have been made in the area of image forensics, especially passive algorithms for detecting tampered images. JPEG format is one of the most common formats used for image compression. Hence, JPEG images are subjected to attacks such as manipulation and cropping. Since single compressed and double compressed JPEG images contain blocking artifacts, therefore these images can be detected by assessment of these artifacts. JPEG artifacts will be not aligned in double compressed images which have been manipulated. This paper intends to examine challenges existing in blocking artifact extraction and improve the detection of double compressed JPEG images. Results of experiments show that new proposed approach has a proper functionality.