Histogram-Based Perceptual Hashing for Minimally Changing Video Sequences

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Second International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (AXMEDIS'06)

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

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AXMEDIS.2006.30

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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