Image segmentation by spatially adaptive color and texture features

Junqing Chen; Thrasyvoulos N. Pappas; Aleksandra Mojsilovic; Bernice E. Rogowitz

doi:10.1252/jcej.36.1005

Image segmentation by spatially adaptive color and texture features

Junqing Chen^*, Thrasyvoulos N. Pappas, Aleksandra Mojsilovic, Bernice E. Rogowitz

^*Corresponding author for this work

Electrical and Computer Engineering

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

24 Scopus citations

Abstract

We present an image segmentation algorithm that is based on spatially adaptive color and texture features. The proposed algorithm is based on a previously proposed algorithm but introduces a number of new elements. We use a new set of texture features based on a steerable filter decomposition. The steerable filters combined with a new spatial texture segmentation scheme provide a finer and more robust segmentation into texture classes. The proposed algorithm includes an elaborate border estimation procedure, which extends the idea of Pappas' adaptive clustering segmentation algorithm to color texture. The performance of the proposed algorithm is demonstrated in the domain of photographic images, including low resolution compressed images.

Original language	English (US)
Pages	1005-1008
Number of pages	4
DOIs	https://doi.org/10.1252/jcej.36.1005
State	Published - 2003
Event	Proceedings: 2003 International Conference on Image Processing, ICIP-2003 - Barcelona, Spain Duration: Sep 14 2003 → Sep 17 2003

Other

Other	Proceedings: 2003 International Conference on Image Processing, ICIP-2003
Country/Territory	Spain
City	Barcelona
Period	9/14/03 → 9/17/03

ASJC Scopus subject areas

Hardware and Architecture
Computer Vision and Pattern Recognition
Electrical and Electronic Engineering

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10.1252/jcej.36.1005

Cite this

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title = "Image segmentation by spatially adaptive color and texture features",

abstract = "We present an image segmentation algorithm that is based on spatially adaptive color and texture features. The proposed algorithm is based on a previously proposed algorithm but introduces a number of new elements. We use a new set of texture features based on a steerable filter decomposition. The steerable filters combined with a new spatial texture segmentation scheme provide a finer and more robust segmentation into texture classes. The proposed algorithm includes an elaborate border estimation procedure, which extends the idea of Pappas' adaptive clustering segmentation algorithm to color texture. The performance of the proposed algorithm is demonstrated in the domain of photographic images, including low resolution compressed images.",

author = "Junqing Chen and Pappas, {Thrasyvoulos N.} and Aleksandra Mojsilovic and Rogowitz, {Bernice E.}",

year = "2003",

doi = "10.1252/jcej.36.1005",

language = "English (US)",

pages = "1005--1008",

note = "Proceedings: 2003 International Conference on Image Processing, ICIP-2003 ; Conference date: 14-09-2003 Through 17-09-2003",

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AU - Chen, Junqing

AU - Pappas, Thrasyvoulos N.

AU - Mojsilovic, Aleksandra

AU - Rogowitz, Bernice E.

PY - 2003

Y1 - 2003

N2 - We present an image segmentation algorithm that is based on spatially adaptive color and texture features. The proposed algorithm is based on a previously proposed algorithm but introduces a number of new elements. We use a new set of texture features based on a steerable filter decomposition. The steerable filters combined with a new spatial texture segmentation scheme provide a finer and more robust segmentation into texture classes. The proposed algorithm includes an elaborate border estimation procedure, which extends the idea of Pappas' adaptive clustering segmentation algorithm to color texture. The performance of the proposed algorithm is demonstrated in the domain of photographic images, including low resolution compressed images.

AB - We present an image segmentation algorithm that is based on spatially adaptive color and texture features. The proposed algorithm is based on a previously proposed algorithm but introduces a number of new elements. We use a new set of texture features based on a steerable filter decomposition. The steerable filters combined with a new spatial texture segmentation scheme provide a finer and more robust segmentation into texture classes. The proposed algorithm includes an elaborate border estimation procedure, which extends the idea of Pappas' adaptive clustering segmentation algorithm to color texture. The performance of the proposed algorithm is demonstrated in the domain of photographic images, including low resolution compressed images.

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T2 - Proceedings: 2003 International Conference on Image Processing, ICIP-2003

Y2 - 14 September 2003 through 17 September 2003

ER -

Image segmentation by spatially adaptive color and texture features

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