Multimedia files play an important role in everyday life. Today, the majority of the population owns state-of-the-art cameras integrated into their mobile devices. Technological development not only facilitates the generation of multimedia content, but also the intentional manipulation of it, and this is where forensic techniques of detecting manipulation on images and videos take on great importance. Although historically there has been confidence in the integrity of images, the advance of technology has begun to erode this confidence. This work proposes a digital image authentication method based on the quadratic mean error of the Color Filter Array interpolation pattern estimated from the analysed image. For the evaluation of the proposed method, experiments were carried out with public databases of forged images that are widely developed for research purposes. The results of the experiments demonstrate the efficiency of the proposed method.

In the last few years, the world has witnessed a ground-breaking growth in the use of digital images and their applications in the modern society. In addition, image editing applications have downplayed the modification of digital photos and this compromises the authenticity and veracity of a digital image. These applications allow for tampering the content of the image without leaving visible traces. In addition to this, the easiness of distributing information through the Internet has caused society to accept everything it sees as true without questioning its integrity. This paper proposes a digital image authentication technique that combines the analysis of local texture patterns with the discrete wavelet transform and the discrete cosine transform to extract features from each of the blocks of an image. Subsequently, it uses a vector support machine to create a model that allows verification of the authenticity of the image. Experiments were performed with falsified images from public databases widely used in the literature that demonstrate the efficiency of the proposed method.