2-D orthogonal lattice filter based image segmentation

Saide Zeynep Aykut; Ridvan Gurcan; Isin Erer

2-D orthogonal lattice filter based image segmentation

Saide Zeynep Aykut^*, Ridvan Gurcan, Isin Erer

^*Corresponding author for this work

Department of Electronics and Communication Engineering

Istanbul Technical University

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

Abstract

The purpose of image segmentation is to partition an image into homogeneous regions. Features are of major importance in image segmentation. In this work, a new method is proposed in which features used for segmentation are reflection coefficients of the two-dimensional(2-D) orthogonal lattice filters. Principal Component Analysis (PCA) is applied to the features for reducing the complexity of the work. A minimum distance classifier is used in the classification algorithms. The proposed method is compared with the discrete wavelet transform which is a common segmentation algorithm. In our work, selected image is a monospectral optical image.

Original language	English
Pages	3814-3817
Number of pages	4
Publication status	Published - 2004
Event	2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004 - Anchorage, AK, United States Duration: 20 Sept 2004 → 24 Sept 2004

Conference

Conference	2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004
Country/Territory	United States
City	Anchorage, AK
Period	20/09/04 → 24/09/04

Keywords

2-D orthogonal lattice filters
Feature
Image segmentation

Cite this

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title = "2-D orthogonal lattice filter based image segmentation",

abstract = "The purpose of image segmentation is to partition an image into homogeneous regions. Features are of major importance in image segmentation. In this work, a new method is proposed in which features used for segmentation are reflection coefficients of the two-dimensional(2-D) orthogonal lattice filters. Principal Component Analysis (PCA) is applied to the features for reducing the complexity of the work. A minimum distance classifier is used in the classification algorithms. The proposed method is compared with the discrete wavelet transform which is a common segmentation algorithm. In our work, selected image is a monospectral optical image.",

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author = "Aykut, {Saide Zeynep} and Ridvan Gurcan and Isin Erer",

year = "2004",

language = "English",

pages = "3814--3817",

note = "2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004 ; Conference date: 20-09-2004 Through 24-09-2004",

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2-D orthogonal lattice filter based image segmentation. / Aykut, Saide Zeynep; Gurcan, Ridvan; Erer, Isin.
2004. 3814-3817 Paper presented at 2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004, Anchorage, AK, United States.

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

TY - CONF

T1 - 2-D orthogonal lattice filter based image segmentation

AU - Aykut, Saide Zeynep

AU - Gurcan, Ridvan

AU - Erer, Isin

PY - 2004

Y1 - 2004

N2 - The purpose of image segmentation is to partition an image into homogeneous regions. Features are of major importance in image segmentation. In this work, a new method is proposed in which features used for segmentation are reflection coefficients of the two-dimensional(2-D) orthogonal lattice filters. Principal Component Analysis (PCA) is applied to the features for reducing the complexity of the work. A minimum distance classifier is used in the classification algorithms. The proposed method is compared with the discrete wavelet transform which is a common segmentation algorithm. In our work, selected image is a monospectral optical image.

AB - The purpose of image segmentation is to partition an image into homogeneous regions. Features are of major importance in image segmentation. In this work, a new method is proposed in which features used for segmentation are reflection coefficients of the two-dimensional(2-D) orthogonal lattice filters. Principal Component Analysis (PCA) is applied to the features for reducing the complexity of the work. A minimum distance classifier is used in the classification algorithms. The proposed method is compared with the discrete wavelet transform which is a common segmentation algorithm. In our work, selected image is a monospectral optical image.

KW - 2-D orthogonal lattice filters

KW - Feature

KW - Image segmentation

UR - http://www.scopus.com/inward/record.url?scp=15944429678&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:15944429678

SP - 3814

EP - 3817

T2 - 2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004

Y2 - 20 September 2004 through 24 September 2004

ER -

2-D orthogonal lattice filter based image segmentation

Abstract

Conference

Keywords

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