Computer Vision Systems and Methods for Blind Localization of Image Forgery

Abstract

Computer vision systems and methods for localizing image forgery are provided. The system generates a constrained convolution via a plurality of learned rich filters. The system trains a convolutional neural network with the constrained convolution and a plurality of images of a dataset to learn a low level representation of each image among the plurality of images. The low level representation is indicative of a statistical signature of at least one source camera model of each image. The system can determine a splicing manipulation localization by the trained convolutional neural network.

What is claimed is: 
     
         1 . A computer vision system for localizing image forgery comprising:
 a memory; and   a processor in communication with the memory, the processor:
 generating a constrained convolution using a plurality of learned rich filters, 
 training a neural network with the constrained convolution and a plurality of images of a dataset to learn a low-level representation indicative of a statistical signature of at least one source camera model for each image among the plurality of images, and 
 localizing an attribute of an image of the dataset by the trained neural network.