Enhancing image forgery detection using 2-D cross products

Abstract

The availability of sophisticated, easy-to-use image editing tools means that the authenticity of digital images can no longer be guaranteed. This chapter proposes a new method for enhancing image forgery detection by combining two detection techniques using a 2-dimensional cross product. Compared with traditional approaches, the method yields better detection results in which the tampered regions are clearly identified. Another advantage is that the method can be applied to enhance a variety of detection algorithms. The method was tested on the CASIA TIDE v2.0 public dataset of color images and the results compared against those obtained using the re-interpolation, JPEG noise quantization and noise estimation techniques. The experimental results indicate that the proposed method is efficient and has superior detection characteristics.