Forgery Detection

Introduction to Digital Image Forgery Detection

Image forgery and manipulation have become common in today’s technology-driven world. Several digital image processing software, photoshopping, and editing tools are used for manipulating images.

This criminal offence can cause rampant loss and damage to one’s reputation. There are several cases where images of different people are used for illegal purposes. 

But. YOU can easily avoid such incidents by implementing proper detection techniques. We at ID Forgery offer excellent image forgery detection services that will help you secure crucial data from theft and misuse.

Techniques of Image Forgery Detection

Some of the techniques used by ID Forgery to detect image forgery are
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Pixel-based Image Forgery Detection

This technique focuses on the number of pixels on a digital image. We use

 

  1. Cloning – Copying and pasting portions of an image to conceal a person or object.
  2. Resampling – Resize, rotate or stretch portions of an image to create a composite. A composite image is a single image made of multiple photos.
  3. Splicing – A photographic manipulation of two or more images to create a single composite.
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Format-based Image Forgery Detection

Usually, the JPEG format is used for format-based forgery detection. We implement

 

  1. JPEG Quantization– Since cameras encode images in JPEG format, the lossy compression scheme allows flexibility to detect discrepancies.
  2. Double JPEG – The manipulated image is compressed twice. The lossy feature of the JPEG image shows some specific details due to this procedure, thus, making detection easy.
  3. JPEG Blocking – Image is cropped and recompressed, due to which a new set of blocking artefacts may be introduced that did not exist originally.
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Camera-based Detection

When a digital camera captures an image, it undergoes a series of processing steps such as quantisation, colour-correlation, gamma correction, white balancing, filtering, and JPEG compression. Eventually, the image moves from the camera sensor to memory. The following techniques use this procedure.

 

  1. Chromatic aberration
  2. Colour filter array
  3. Camera response
  4. Sensor noise
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Physical Environment-based Detection

These use lighting of the environment under which an object or image is captured.

 

  1. Light direction 2-D– The light source is estimated to make simple assumptions.
  2. Light direction 3-D– The 3-D light directly from a light source is detected through its reflection on the human eye.
  3. Light environment– Under a complex environment, where there can be several light sources, we estimate a low-parameter representation using mathematical formulae to detect errors.
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Geometry-based Image Forgery Detection

In this technique, measurements of objects and their position relative to the camera are detected.

 

  1. Principal Point– In authentic images, the principal point is near the centre of the image while it moves proportionally when it is manipulated. These differences help in forgery detection.
  2. Metric Measures– Several tools from projective geometry that allow the rectification of planar surfaces is used to detect image forgery.

Benefits of Digital Image Forgery Detection

Image forgery is illegal. Early detection of image forgery can prevent misuse.

Our prompt forgery detection saves you from reputational loss and malpractices.

We at ID Forgery strive to enhance the ethical use of technology and provide forgery detection services without costing your time.

Early image forgery detection can prevent financial loss for businesses, as misuse is detected at an early stage.

Detecting image forgery at the right time can help you boost data security and safety.

Ready to Benefit from
ID Forgery Technology?

The primary benefit that our ID Forgery Detection algorithm provides you with is it considerably reduces the cost of labor required to cross-check the authenticity of the images and documents provided to you. This saves you time and energy that can be employed in other relevant fields to maximize profits.