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Segmentation of natural images using hierarchical and syntactic methods

  • Paul Stefan Williams
  • Michael Alder
Shape Representation and Image Segmentation
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1451)

Abstract

This paper examines the problem of image segmentation using hierarchical and syntactic methods. A bottom up approach takes low level feature vectors and combines them to form higher level objects corresponding to disjoint regions of the image with homogeneous characteristics. This transformation is known as The Up Write. A Down Write process is also introduced which reconstructs an image using only the higher level representation. This not only provides an insight into the effectiveness of the representation, but also outlines its weaknesses. The results of the UpWrite, or segmentation, and the DownWrite are illustrated from a database of 1000 Corel Photo-CD images. Finally a simple classification scheme is presented to distinguish between predefined image classes such as Fields, Brown Bears and Elephants. The classification results indicate the effectiveness of the approach for use in content based image retrieval (CBIR).

keywords

Image Segmentation Content Based Image Retrieval (CBIR) Syntactic Pattern Recognition Image Recognition 

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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Paul Stefan Williams
    • 1
  • Michael Alder
    • 1
  1. 1.Centre for Intelligent Information Processing Systems Department of Electrical & Electronic EngineeringThe University of Western AustraliaNedlandsAustralia

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