Automated detection of tampered images
AssigneeFacebook, Inc.
InventorsBrian Dolhansky, Cristian Canton Ferrer, Eric Erkon Hsin
Life of this patent
Estimating the term…
Abstract
A content analyzer determines whether various types of modification have been made to images. The content analyzer computes JPEG ghosts from the images that are concatenated with the image channels to generate a feature vector. The feature vector is provided as input to a neural network that determines whether the types of modification have been made to the image. The neural network may include a constrained convolution layer and several unconstrained convolution layers. An image fake model may also be applied to determine whether the image was generated using a computer model or algorithm.
Claims16
A method comprising:
- receiving an image;
- generating one or more JPEG ghosts from the image;
- generating a feature vector from the image and the JPEG ghosts;
- providing the feature vector as input to a neural network, the neural network including a constrained convolution layer and a plurality of unconstrained convolution layers, wherein the constrained convolution layer includes a plurality of convolution filters, each convolution filter including a central element value and a plurality of other element values, the central element value being a first predetermined value and the other element values summing to a second predetermined value;
- generating, by the neural network, an output from the feature vector, the output including an indication of whether a type of modification is present in the image;
- and
- associating metadata with the image indicating whether the type of modification is present in the image based on the output of the neural network.
A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:
- receiving an image;
- generating one or more JPEG ghosts from the image;
- generating a feature vector from the image and the JPEG ghosts;
- providing the feature vector as input to a neural network, the neural network including a constrained convolution layer and a plurality of unconstrained convolution layers, wherein the constrained convolution layer includes a plurality of convolution filters, each convolution filter including a central element value and a plurality of other element values, the central element value being a first predetermined value and the other element values summing to a second predetermined value;
- generating, by the neural network, an output from the feature vector, the output including an indication of whether a type of modification is present in the image;
- and
- associating metadata with the image indicating whether the type of modification is present in the image based on the output of the neural network.
Dependencies are inferred from the claim text.