Research Article

Perceptual Hashing-Based Image Copy-Move Forgery Detection

Algorithm 2

Similar region matching.
Input: All perceptual hash feature vectors ,
, where
and , which are the output
of Algorithm 1.
Output: A map that includes the detection results.
Step  1. Creating packages, denoted as ,
, and , where
and is a preset threshold.
Step  2. All perceptual hash feature vectors
are stored into the
packages, respectively, according to
the value of .
Step  3. A map is created with the same size of
suspicious image and all its initial pixel
values are set to zero.
Step  4. For each package   
Step  5. The block pairs contained in will be
matched according to their perceptual
hash feature vectors and coordinate
positions. The values of the corresponding
coordinate positions in the map will be
set to a same pixel value “255” according
to the coordinates of the suspicious
image if the block pairs are diagnosed
as similar.
Step  6. For each block contained in package ,
it will be matched with all blocks
contained in package if
with the same method
of Step  5.
Step  7. End For
Step  8. Outputting the map.