Fake Images Research Articles

Detecting fake images using watermarks and support vector machines

With the great convenience of computer graphics and digital imaging, it becomes much easier to alter the content of images than before without any visually traces to catch these manipulations, i.e., many fake images are produced whose content is feigned. Thus, the images can not be judged whether they are real or not visually. In order to detect fake images, this paper proposes a detection scheme, which, firstly, uses watermarks to locate the alteration, and then, uses support vector machine (SVM) as a classifier to make a binary decision on whether an image is fake or real. The experimental results also demonstrated the effectiveness of the proposed scheme.

Multiple-encoding retrieval for optical security

We propose a method for image encryption by multiple-step random phase encoding with an undercover multiplexing operation. The true image is stored in a multiple record we call encodegram; and then we can reconstruct it by the use of the appropriate random phase masks and a retrieval protocol. To increase the security of the true hidden image and confuse unauthorized receivers, we add to the encodegram an encoded fake image with different content. This fake image has only a small effect on the retrieval of the true hidden image, owing to the specific property of this protocol. In the decryption step, we can reveal the true image by applying the inverse protocol to two cyphertexts, one the encodegram containing the true image along with the fake image; and the other helping to get the random phase key to achieve the true image. Computer simulations verify the validity of this method for image encryption. Digital implementation of the method makes it particularly suitable for the remote transmission of information.

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.

Secure authentication watermarking for localization against the Holliman–Memon attack

Authentication watermarking schemes using block-wise watermarks for tamper localization are vulnerable to the Holliman---Memon attack. In this paper, we propose a novel method based on the Wong's localization scheme (Proceedings of the IS&T PIC, Portland) to resist this attack. A unique image index scheme is used for computing the authentication signature that is embedded in the least significant bit-plane of the block. The informed detector estimates the correct image index by using the side information about the watermarked image. The image index estimation from the fake image can definitely be an alternative to keeping a directory of image indices. So it is not necessary to manage the database of image indices for the verification purpose. The authenticity measure is defined to quantify the attack severity by taking the connectivity among possible authentic blocks into consideration. There are more blocks verified as authentic when this measure is high for a fake image constructed using this attack. As such, the blocks for a fake image can be chosen from a reduced number of database images. The blocks from any such image are to be connected with each other to maximize the authenticity measure. Thus, the attacker's task to generate a fake image of reasonable perceptual quality becomes increasingly difficult. With the proposed method there is no loss or ambiguity in localization after the Holliman---Memon attack and content tampering in an image. The localization accuracy in the proposed method is demonstrated by the simulation results and is equal to the chosen block size, similar to the Wong's scheme.

Blind Fake Image Detection Scheme Using SVD

The release of image processing techniques make image modification and fakery easier. Image fakery, here, is defined as a process to copy a region of source image and paste it onto the destination image, with some post processing methods applied, such as boundary smoothing, blurring, etc. to make it natural. The most important characteristic of image fakery is object copy and paste. In order to detect fake images, this letter introduces a blind detection scheme based on singular value decomposition (SVD). Experimental results also show the effectiveness of the proposed scheme.