Color texture invariants for natural image recognition based on human visual system

J. F. Camapum Wanderley; M. H. Fisher

doi:10.1109/ICECS.2000.911540

Color texture invariants for natural image recognition based on human visual system

J. F. Camapum Wanderley, M. H. Fisher

Research output: Contribution to conference › Paper › peer-review

3 Citations (Scopus)

Abstract

The main contribution of this work is the proposal of a new set of color texture affine and illumination invariants based on the human visual system (HVS). A description regarding the importance of texture as a feature and a new color texture descriptor for natural image recognition, invariant to illumination and rotation, is introduced. The new feature vector extracted to represent the color texture images is generated by decomposing each of the three color channels of the image into several frequency and orientation bands using a bank of Gabor filters and then extracting several features from each color channel response independently and also from the combination of different color channel responses

Original language	English
Pages	295-298
Number of pages	4
DOIs	https://doi.org/10.1109/ICECS.2000.911540
Publication status	Published - Dec 2000
Event	7th IEEE International Conference on Electronics, Circuits and Systems - Jounieh, Lebanon Duration: 17 Dec 2000 → 20 Dec 2000

Conference

Conference	7th IEEE International Conference on Electronics, Circuits and Systems
Abbreviated title	ICECS 2000
Country/Territory	Lebanon
City	Jounieh
Period	17/12/00 → 20/12/00

Access to Document

10.1109/ICECS.2000.911540

Cite this

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title = "Color texture invariants for natural image recognition based on human visual system",

abstract = "The main contribution of this work is the proposal of a new set of color texture affine and illumination invariants based on the human visual system (HVS). A description regarding the importance of texture as a feature and a new color texture descriptor for natural image recognition, invariant to illumination and rotation, is introduced. The new feature vector extracted to represent the color texture images is generated by decomposing each of the three color channels of the image into several frequency and orientation bands using a bank of Gabor filters and then extracting several features from each color channel response independently and also from the combination of different color channel responses",

author = "{Camapum Wanderley}, {J. F.} and Fisher, {M. H.}",

year = "2000",

month = dec,

doi = "10.1109/ICECS.2000.911540",

language = "English",

pages = "295--298",

note = "7th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2000 ; Conference date: 17-12-2000 Through 20-12-2000",

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AU - Camapum Wanderley, J. F.

AU - Fisher, M. H.

PY - 2000/12

Y1 - 2000/12

N2 - The main contribution of this work is the proposal of a new set of color texture affine and illumination invariants based on the human visual system (HVS). A description regarding the importance of texture as a feature and a new color texture descriptor for natural image recognition, invariant to illumination and rotation, is introduced. The new feature vector extracted to represent the color texture images is generated by decomposing each of the three color channels of the image into several frequency and orientation bands using a bank of Gabor filters and then extracting several features from each color channel response independently and also from the combination of different color channel responses

AB - The main contribution of this work is the proposal of a new set of color texture affine and illumination invariants based on the human visual system (HVS). A description regarding the importance of texture as a feature and a new color texture descriptor for natural image recognition, invariant to illumination and rotation, is introduced. The new feature vector extracted to represent the color texture images is generated by decomposing each of the three color channels of the image into several frequency and orientation bands using a bank of Gabor filters and then extracting several features from each color channel response independently and also from the combination of different color channel responses

U2 - 10.1109/ICECS.2000.911540

DO - 10.1109/ICECS.2000.911540

M3 - Paper

SP - 295

EP - 298

T2 - 7th IEEE International Conference on Electronics, Circuits and Systems

Y2 - 17 December 2000 through 20 December 2000

ER -