Image segmentation using a texture gradient based watershed transform

PR Hill; CN Canagarajah; DR Bull

doi:10.1109/TIP.2003.819311

Image segmentation using a texture gradient based watershed transform

PR Hill
, CN Canagarajah
, DR Bull

Research output: Contribution to journal › Article (Academic Journal) › peer-review

117 Citations (Scopus)

1256 Downloads (Pure)

Abstract

The segmentation of images into meaningful and homogenous regions is a key method for image analysis within applications such as content based retrieval. The watershed transform is a well established tool for the segmentation of images. However, watershed segmentation is often not effective for textured image regions that are perceptually homogeneous. In order to segment such regions properly, the concept of the "texture gradient" is introduced. Texture information and its gradient are extracted using a novel nondecimated form of a complex wavelet transform. A novel marker location algorithm is subsequently used to locate significant homogeneous textured or non textured regions. A marker driven watershed transform is then used to segment the identified regions properly. The combined algorithm produces effective texture and intensity based segmentation for application to content based image retrieval.

Translated title of the contribution	Image segmentation using a texture gradient based watershed transform
Original language	English
Pages (from-to)	1618 - 1633
Number of pages	16
Journal	IEEE Transactions on Image Processing
Volume	12
Issue number	12
DOIs	https://doi.org/10.1109/TIP.2003.819311
Publication status	Published - Dec 2003

Bibliographical note

Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Rose publication type: Journal article

Sponsorship: The authors would like to acknowledge the help of N. Kingsbury of the University of Cambridge for providing the Matlab code for the DT-CWT

Terms of use: Copyright © 2003 IEEE. Reprinted from IEEE Transactions on Image Processing.

This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bristol's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected].

By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

Keywords

image segmentation
image texture analysis
image edge analysis
wavelet transforms

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10.1109/TIP.2003.819311

HIll IEEE TransIP 2003Accepted author manuscript, 1.58 MB

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title = "Image segmentation using a texture gradient based watershed transform",

abstract = "The segmentation of images into meaningful and homogenous regions is a key method for image analysis within applications such as content based retrieval. The watershed transform is a well established tool for the segmentation of images. However, watershed segmentation is often not effective for textured image regions that are perceptually homogeneous. In order to segment such regions properly, the concept of the {"}texture gradient{"} is introduced. Texture information and its gradient are extracted using a novel nondecimated form of a complex wavelet transform. A novel marker location algorithm is subsequently used to locate significant homogeneous textured or non textured regions. A marker driven watershed transform is then used to segment the identified regions properly. The combined algorithm produces effective texture and intensity based segmentation for application to content based image retrieval.",

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author = "PR Hill and CN Canagarajah and DR Bull",

note = "Publisher: Institute of Electrical and Electronics Engineers (IEEE) Rose publication type: Journal article Sponsorship: The authors would like to acknowledge the help of N. Kingsbury of the University of Cambridge for providing the Matlab code for the DT-CWT Terms of use: Copyright {\textcopyright} 2003 IEEE. Reprinted from IEEE Transactions on Image Processing. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bristol's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. ",

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AU - Bull, DR

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N2 - The segmentation of images into meaningful and homogenous regions is a key method for image analysis within applications such as content based retrieval. The watershed transform is a well established tool for the segmentation of images. However, watershed segmentation is often not effective for textured image regions that are perceptually homogeneous. In order to segment such regions properly, the concept of the "texture gradient" is introduced. Texture information and its gradient are extracted using a novel nondecimated form of a complex wavelet transform. A novel marker location algorithm is subsequently used to locate significant homogeneous textured or non textured regions. A marker driven watershed transform is then used to segment the identified regions properly. The combined algorithm produces effective texture and intensity based segmentation for application to content based image retrieval.

AB - The segmentation of images into meaningful and homogenous regions is a key method for image analysis within applications such as content based retrieval. The watershed transform is a well established tool for the segmentation of images. However, watershed segmentation is often not effective for textured image regions that are perceptually homogeneous. In order to segment such regions properly, the concept of the "texture gradient" is introduced. Texture information and its gradient are extracted using a novel nondecimated form of a complex wavelet transform. A novel marker location algorithm is subsequently used to locate significant homogeneous textured or non textured regions. A marker driven watershed transform is then used to segment the identified regions properly. The combined algorithm produces effective texture and intensity based segmentation for application to content based image retrieval.

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Image segmentation using a texture gradient based watershed transform

Abstract

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Keywords

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