A wavelet-based coarse-to-fine image matching scheme in a parallel virtual machine environment

Jia You, Prabir Bhattacharya

Research output: Journal article publicationJournal articleAcademic researchpeer-review

84 Citations (Scopus)


We present a wavelet-based, high performance, hierarchical scheme for image matching which includes 1) dynamic detection of interesting points as feature points at different levels of subband images via wavelet transform, 2) adaptive thresholding selection based on compactness measures of fuzzy sets in image feature space, and 3) a guided searching strategy for the best matching from coarse level to fine level. In contrast to the traditional parallel approaches which rely on specialized parallel machines, we explored the potential of distributed systems for parallelism. The proposed image matching algorithms were implemented on a network of workstation clusters using parallel virtual machine (PVM). The results show that our wavelet-based hierarchical image matching scheme is efficient and effective for object recognition.
Original languageEnglish
Pages (from-to)1547-1559
Number of pages13
JournalIEEE Transactions on Image Processing
Issue number9
Publication statusPublished - 1 Jan 2000


  • Feature detection
  • Guided matching
  • Hausdorff distance
  • Image matching
  • Image pyramid
  • Parallel algorithms
  • Parallel virtual machine (PVM)
  • Wavelet transform

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design


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