Texture Classification Using VQ with Feature Extraction based on Transforms Motivated by the Human Visual System

D
DCC
2007
2007 Data Compression Conference (DCC'07)
Abstract - Texture Classification Using VQ with Feature Extraction based on Transforms Motivated by the Human Visual System

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2007 Data Compression Conference (DCC'07)

Texture Classification Using VQ with Feature Extraction based on Transforms Motivated by the Human Visual System (PDF)

Snowbird, Utah

March 27-March 29

ISBN: 0-7695-2791-4

	ASCII Text	x
	Antonella Di Lillo, James A. Storer, Giovanni Motta, "Texture Classification Using VQ with Feature Extraction based on Transforms Motivated by the Human Visual System," Data Compression Conference, pp. 392, 2007 Data Compression Conference (DCC'07), 2007.

	BibTex	x
	@article{ 10.1109/DCC.2007.74, author = {Antonella Di Lillo and James A. Storer and Giovanni Motta}, title = {Texture Classification Using VQ with Feature Extraction based on Transforms Motivated by the Human Visual System}, journal ={Data Compression Conference}, volume = {0}, year = {2007}, issn = {1068-0314}, pages = {392}, doi = {http://doi.ieeecomputersociety.org/10.1109/DCC.2007.74}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Data Compression Conference TI - Texture Classification Using VQ with Feature Extraction based on Transforms Motivated by the Human Visual System SN - 1068-0314 SP EP A1 - Antonella Di Lillo, A1 - James A. Storer, A1 - Giovanni Motta, PY - 2007 KW - null VL - 0 JA - Data Compression Conference ER -

Antonella Di Lillo, Brandeis University

James A. Storer, Brandeis University

Giovanni Motta, Bitfone Co.

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/DCC.2007.74

Texture identification can be a key component in CBIR (Content Based Image Recognition) systems. It can also be a tool for separation of video object planes in MPEG4 video compression systems. Although formal definitions of texture vary in the literature, it is commonly accepted that textures are naturally extracted and recognized as such by the human visual system, and that this analysis is performed in the frequency domain.

Citation:

Antonella Di Lillo, James A. Storer, Giovanni Motta, "Texture Classification Using VQ with Feature Extraction based on Transforms Motivated by the Human Visual System," dcc, pp.392, 2007 Data Compression Conference (DCC'07), 2007

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