A fast 2D entropic thresholding method by wavelet decomposition

Q. Wang, Q. Wang, D. Feng, R. Zhao, Zheru Chi

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Compared with ID grayscale histogram analysis, 2D entropic thresholding makes use of local average as well as pixel gray level. However, it is time consuming to search the threshold vector in the 2D histogram. In the paper, a fast algorithm using wavelet decomposition is proposed, with which a set of candidates of the vector was first obtained in the decomposed histogram. The optimal threshold vector is then obtained without exhaustive searching. Experimental results have shown that our algorithm not only finds the threshold vector as well as Brink's method (1992) but also saves computation costs, using up only 0.53% of the processing time taken by exhaustive searching.
Original languageEnglish
Title of host publicationProceedings 2002 International Conference on Image Processing : 22-25 September 2002, Rochester Riverside Convention Center, Rochester, New York, USA
PublisherIEEE
PagesIII-265-III-268
Number of pages1
ISBN (Print)0780376226
DOIs
Publication statusPublished - 2002
EventIEEE International Conference on Image Processing [ICIP] -
Duration: 1 Jan 2002 → …

Publication series

NameInternational Conference on Image Processing. Proceedings
Volume3
ISSN (Print)1522-4880

Conference

ConferenceIEEE International Conference on Image Processing [ICIP]
Period1/01/02 → …

Keywords

  • Computational complexity
  • Entropy
  • Image segmentation
  • Wavelet transforms

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Software

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