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Second International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (AXMEDIS'06)
Histogram-Based Perceptual Hashing for Minimally Changing Video Sequences
Leeds, UK
December 13-December 15
ISBN: 0-7695-2625-X
ASCII Text
x 
 
Kevin Hamon, Martin Schmucker, Xuebing Zhou, "Histogram-Based Perceptual Hashing for Minimally Changing Video Sequences," Automated Production of Cross Media Content for Multi-Channel Distribution, International Conference on, pp. 236-241, Second International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (AXMEDIS'06), 2006.
 
 
BibTex
x
 
@article{ 10.1109/AXMEDIS.2006.30,
author = {Kevin Hamon and Martin Schmucker and Xuebing Zhou},
title = {Histogram-Based Perceptual Hashing for Minimally Changing Video Sequences},
journal ={Automated Production of Cross Media Content for Multi-Channel Distribution, International Conference on},
volume = {0},
year = {2006},
isbn = {0-7695-2625-X},
pages = {236-241},
doi = {http://doi.ieeecomputersociety.org/10.1109/AXMEDIS.2006.30},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Automated Production of Cross Media Content for Multi-Channel Distribution, International Conference on
TI - Histogram-Based Perceptual Hashing for Minimally Changing Video Sequences
SN - 0-7695-2625-X
SP236
EP241
A1 - Kevin Hamon,
A1 - Martin Schmucker,
A1 - Xuebing Zhou,
PY - 2006
KW - null
VL - 0
JA - Automated Production of Cross Media Content for Multi-Channel Distribution, International Conference on
ER -
 
Kevin Hamon, Fraunhofer Institute for Computer Graphics Research (IGD), Germany
Martin Schmucker, Fraunhofer Institute for Computer Graphics Research (IGD), Germany
Xuebing Zhou, Fraunhofer Institute for Computer Graphics Research (IGD), Germany
An increasing number of multimedia applications require techniques for efficient and automatic content identification and verification. Here, perceptual hashing technologies apply. Due to the diverseness of video data, algorithms whose design considers the properties of the different video classes are required. Therefore, different approaches exist to extract a perceptual hash.

In this article, we propose a histogram-based perceptual hashing algorithm for minimally changing video sequences. The algorithm is described and the performed evaluation shows improvements of the identification performance for minimally changing video content.

Citation:
Kevin Hamon, Martin Schmucker, Xuebing Zhou, "Histogram-Based Perceptual Hashing for Minimally Changing Video Sequences," axmedis, pp.236-241, Second International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (AXMEDIS'06), 2006
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