Image segmentation using a texture gradient based watershed transform

PR Hill, CN Canagarajah, DR Bull

Research output: Contribution to journalArticle (Academic Journal)peer-review

111 Citations (Scopus)
987 Downloads (Pure)


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 contributionImage segmentation using a texture gradient based watershed transform
Original languageEnglish
Pages (from-to)1618 - 1633
Number of pages16
JournalIEEE Transactions on Image Processing
Issue number12
Publication statusPublished - 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.

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  • image segmentation
  • image texture analysis
  • image edge analysis
  • wavelet transforms


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