Content-based image retrieval using blockconstrained fractal coding and nona-tree decomposition

Z. Wang, Zheru Chi, D. Feng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

10 Citations (Scopus)

Abstract

Fractal coding has been proved useful for image compression. In fractal coding, an image is represented by a number of self-transformations (fractal code) by which an approximation of the original image can be reconstructed. The authors present a block-constrained fractal coding scheme and a nona-tree decomposition based matching strategy for content-based image retrieval. In the coding scheme, an image is partitioned into non-overlapped blocks with a size close to that of a query iconic image. The fractal code is generated for each block independently. In the similarity measure of the fractal code, an improved nona-tree decomposition scheme is adopted to avoid matching the fractal code globally in order to reduce computational complexity. The experimental results show that the authors' coding scheme and matching strategy are useful for image retrieval, and compare favourably with other two methods tested in terms of storage usage and computing time.
Original languageEnglish
Pages (from-to)9-15
Number of pages7
JournalIEE Proceedings: Vision, Image and Signal Processing
Volume147
Issue number1
DOIs
Publication statusPublished - 1 Feb 2000

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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