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

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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.

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