Adaptive dual-threshold edge detection based on wavelet transform

Shu Juan Hou*, Wen Bo Mei, Zhi Ming Zhang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

In order to solve the problems of local-maximum modulus extraction and threshold selection in the edge detection of finite-resolution digital images, a wavelet transform based adaptive dual-threshold edge detection algorithm is proposed. The local-maximum modulus is extracted by linear interpolation in wavelet domain. With the analysis on histogram, the image is filtered with an adaptive dual-threshold method, which effectively detects the contours of small structures as well as the boundaries of large objects. A wavelet domain's propagation function is used to further select weak edges. Experimental results show that the self-adaptivity of the threshold to images have the same kind of histogram, and the efficiency are even in noise-tampered images.

Original languageEnglish
Pages (from-to)247-250
Number of pages4
JournalJournal of Beijing Institute of Technology (English Edition)
Volume12
Issue number3
Publication statusPublished - Sept 2003

Keywords

  • Dual-threshold
  • Edge detection
  • Propagation function
  • Wavelet transform

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