A Forensic Signature Based on Spatial Distributed Bag of Features for Image Alignment and Tampering Detection

The distribution of digital images with the classic and newest technologies available on Internet has induced a growing interest on systems able to protect the visual content against malicious manipulations performed during their transmission. One of the main problems addressed in this context is the authentication of the image received in a communication. This task is usually performed by localizing the regions of the image which have been tampered. To this aim the received image should be first aligned with the one at the sender by exploiting the information provided by a specific component of the forensic hash associated with the image. In this paper we propose a robust alignment method which makes use of an image hash component based on the Bag of Features paradigm. In order to deal with highly textured and contrasted tampering patterns the spatial distribution of the image features has been encoded in the alignment signature. A block-wise tampering detection based on histograms of oriented gradients representation is also proposed. Specifically, a non-uniform quantization of the histogram of oriented gradient space is used to build the signature of each image block for tampering purposes. Experiments show that the proposed approach obtains good margin in terms of performances with respect to state-of-the-art methods.