Abstract—A video copy detection system that is based on content
fingerprinting and can be used for video indexing and copyright
applications is proposed. The system relies on a fingerprint
extraction algorithm followed by a fast approximate search algorithm.
The fingerprint extraction algorithm extracts compact content-
based signatures from special images constructed from the
video. Each such image represents a short segment of the video and
contains temporal as well as spatial information about the video
segment. These images are denoted by temporally informative representative
images. To find whether a query video (or a part of
it) is copied from a video in a video database, the fingerprints of
all the videos in the database are extracted and stored in advance.
The search algorithm searches the stored fingerprints to find close
enough matches for the fingerprints of the query video. The proposed
fast approximate search algorithm facilitates the online application
of the system to a large video database of tens of millions
of fingerprints, so that a match (if it exists) is found in a few seconds.
The proposed system is tested on a database of 200 videos in
the presence of different types of distortions such as noise, changes
in brightness/contrast, frame loss, shift, rotation, and time shift.
It yields a high average true positive rate of 97.6% and a low average
false positive rate of 1.0%. These results emphasize the robustness
and discrimination properties of the proposed copy detection
system. As security of a fingerprinting system is important for
certain applications such as copyright protections, a secure version
of the system is also presented.