Localisation map
Definition
The output of a forgery detection algorithm that marks, at pixel or block resolution, which regions of the image are identified as manipulated. A binary or heatmap localisation output is the primary forensic deliverable: it tells the fact-finder where the forgery occurred, not merely that one occurred.
Related terms
- Affine transform estimation
- The recovery of the geometric transformation (rotation, scaling, shear) relating a copied region to its source, using matched keypoint pairs. Geometrically consistent...
- Block-matching
- A copy-move detection strategy that divides the image into overlapping fixed-size blocks, computes a compact feature vector per block, sorts vectors, and...
- Chromatic aberration
- Colour fringing at high-contrast edges caused by differential refraction of light wavelengths by a lens. The pattern is lens-specific and inconsistent across...
- Copy-move forgery
- An intra-image manipulation in which a patch copied from one location within the image is pasted over another location in the same...
- Noiseprint
- A CNN-based camera-model fingerprint extractor by Cozzolino and Verdoliva. Applied to deepfakes, it reveals inconsistency between the camera fingerprint in the genuine...
- Passive forgery detection
- Detection that operates on the image data alone, without any pre-embedded watermark or signature. Distinguished from active methods such as digital watermarking...
- SIFT (Scale-Invariant Feature Transform)
- A keypoint descriptor algorithm that detects interest points and computes 128-dimensional descriptors invariant to scale and rotation. In forgery detection, matching SIFT...
- Splicing
- An inter-image manipulation in which content from one or more external images is inserted into a target image. Splicing introduces cross-boundary inconsistencies...
Explained in
- Copy-Move and Splicing Detection in ImagesThe output of a forgery detection algorithm that marks, at pixel or block resolution, which regions of the image are identified as manipulated. A binary or hea...