In recent years Content Based Information Retrieval (CBIR) has received a lot of research
attention, starting with audio, followed by images and video. Video ngerprinting is a
CBIR technique that creates a digital descriptor, also known as a ngerprint, for videos
based on its content. These ngerprints are then saved to a database and used to detect
unknown videos by comparing the unknown video's ngerprint to the ngerprints in the
database to get a match. Many techniques have already been proposed with various levels
of success, but most of the existing techniques focus mainly on robustness and neglect the
speed of implementation.
In this dissertation a novel video ngerprinting technique will be developed with the main
focus on detecting advertisements in a television broadcast. Therefore the system must be
able to process the incoming video stream in real-time and detect all the advertisements
that are present. Even though the algorithm has to be fast, it still has to be robust enough
to handle a moderate amount of distortions.
These days video ngerprinting still holds many challenges as it involves characterizing
videos, made up of sequences of images, e ectively. This means the algorithm must
somehow imitate the inherent ability of humans to recognize a video almost instantly.
The technique uses the content of the video to derive a ngerprint, thus the features used
by the ngerprinting algorithm should be robust to distortions that don't a ect content
according to humans. / Thesis (MIng (Computer and Electronic Engineering))--North-West University, Potchefstroom Campus, 2013
| Identifer | oai:union.ndltd.org:NWUBOLOKA1/oai:dspace.nwu.ac.za:10394/9525 |
| Date | January 2012 |
| Creators | Moolman, Ruan |
| Publisher | North-West University |
| Source Sets | North-West University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
Page generated in 0.0015 seconds