Photo Manipulation (Forgery) Detection
Are digital images submitted as court evidence genuine, or have the pictures
been altered or modified? Belkasoft developed a solution that helps you find out.
Belkasoft Forgery Detection Module automates authenticity analysis of JPEG images.
The tool produces a concise estimate of the image's authenticity, and clearly displays
the probability of the image being forged on a scale of 1-100.
The Forgery Detection Module can reliably detect forged and tampered photos among
the thousands of files available on a computer. A unique feature of this module
is the ability to detect manipulated images based on analysis of JPEG compression
and quantization artifacts. The module offers reliable detection of images and videos
that were edited, modified or manipulated on a PC after they've been taken with
still or video camera.
Why Using Belkasoft Forgery Detection Module
- Detects fake evidence automatically
Automates the detection of altered, modified and forged images taken with the
widest range of digital cameras.
- Concise reporting
The probability of an image being forged or genuine is reported on a numeric
scale of 1 to 100.
- Based on comprehensive scientific research
The tool is based on a scientific research performed and published by the tool's
- Robust digital analysis
Analyzing the images in digital domain results in repeatable performance and
- Makes expert work easier
Many signs of a forged image will escape the human eye completely. Performing
a bit-level analysis is a great addition to what can be seen by the human eye.
- Fast batch processing
Allows processing hundreds of images in a matter of minutes.
- Eliminates false positives
Altered, modified and re-saved images are detected with extreme reliability.
- Supports about 3,000+ camera models
At least 100 images were taken with each camera and carefully analyzed before
adding it to a database of supported models.
At a glance, the module employs innovative heuristic algorithms to calculate
the probability of the forgery for each particular image. The algorithms assign
files numeric values corresponding to the probability that the file has been manipulated.
The module detects double compression artifacts that are typical for JPEG images
lossy compression algorithms. The presence of such artifacts in an image is a reliable
sign of the image being edited and saved.
In addition, the module checks for various bits and pieces of information that
should be present in images when they come off a particular camera such as camera-specific
tags and EXIF data. These bits and pieces are often dropped by image editing software.
The Forgery Detection module comes with a comprehensive camera database containing
information about more than a thousand popular camera models. By comparing the features
present in a particular photo or video file with ones expected from camera, the
Forgery Detection module can detect manipulation attempts.
Photos with Forged Digital Signatures
Today's high-end digital cameras such as those produced by Canon or Nikon can
digitally sign images to ensure their authenticity. In theory, when such images
are altered, the embedded digital signature will no longer validate. Unfortunately,
the technology is inherently flawed. There are tools allowing to put a valid digital
signature on obviously fake images. It only takes minutes to produce a set of forged
images that successfully pass validation with Nikon Image Authentication Software
or Canon Original Data Security Kit (OSK-E3).
Therefore, digital signatures cannot be trusted, and should be disregarded
completely as a positive proof of authenticity.
The Forgery Detection module looks elsewhere in the image to find signs that
the image has been forged or altered.
How It Works
Error Level Analysis
Manipulation attempts are detected by comparing compression quality between different
areas of the image.
Cloning, copying and pasting of certain objects or areas in the image is detected
with scaling and rotation support.
Quantization Table Analysis
Digital cameras and PC-based image editing tools use different quantization tables
when saving encoding images into JPEG format. Quantization tables can be extracted
and analyzed. If the tables are different from those used by the camera model as
specified in the image's EXIF information, then a manipulation attempt is present.
Double Compression Artifacts
JPEG is a lossy compression format, meaning that certain artifacts are introduced
every time an image is saved. By opening, editing and saving a JPEG picture, one
inevitably introduces compression artifacts that were not present in the original
JPEG. As certain correlation of neighboring pixels is only present in JPEG images
when they are opened and compressed again, it becomes possible to detect these artifacts
and bring investigator's attention to the altered image.
Double Quantization Effect
This algorithm is based on certain quantization artifacts appearing when applying
JPEG compression more than once. If a JPEG file was opened, edited, then saved,
certain compression artifacts will inevitably appear.
In order to determine the double quantization effect, the algorithm creates 192
histograms containing discrete cosine transform values. Certain quantization effects
will only appear on these histograms if an image was saved in JPEG format more than
once. If the effect is discovered, we can definitely tell the image was edited (or
at least saved by a graphic editor) at least once. However, if this effect is not
discovered, we cannot make any definite conclusions about the image as it could,
for example, be developed from a RAW file, edited in a graphic editor and saved
to a JPEG file just once.
Foreign Artifacts and Pasted Image Detection
An image saved by a certain camera model features a characteristic camera response
function. The function describes the dependency of pixel's color on the amount of
light falling to that pixel. A camera response function is computed for each camera
model, and compared to the same function applicable to different areas in the image.
If the two functions diverge, the Forgery Detection module assumes that the region
has possibly been altered.
Supported Camera Models
We proudly support about 3,000+ camera models from a wide range of manufacturers.
For supported cameras, Belkasoft Forgery Detection Module keeps a record of all
standard EXIF tags, and recognizes the specific nuances of each camera's JPEG output,
like standard quantization table and quality parameters. If a camera model is available
in our database, any alterations to images captured with that model are spotted
on forgery detection.