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A self-adaptable improved arithmetic based on wavelet transform in the image edge detection

  • Zhang Jingchao*
  • , Liu Songyan
  • , Hao Guangpu
  • , Sun Lingyun
  • , Yang Jin
  • *Corresponding author for this work
  • Yanshan University
  • Material Technology College

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Compared with traditional edge detection methods, the method based on wavelet transform is a high precision way. The scale, however, impacts the effect of output imagine. The high frequency could be controlled when the scale is large, and the SNR of the image is relatively great. But the precision of location is lower. On the other hand, the location could be realized precisely when the scale is small, and the detail of the image could be extracted. But the ability of denoising is weak. A self-adaptable scale selection method is given in this paper. The edge detection of an image can be realized well by different properties of wavelet transform on different scales. Accordingly, the gauss filter is adopted to pre-treat the figure, and the self-adaptable multi-scale wavelet transform is introduced to process the after-pretreat figure. Result of experiment shows that a highly quality edge figure by smooth disposal of different scales is received.

Original languageEnglish
Title of host publication2009 International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2009
Pages414-417
Number of pages4
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2009 - Zhangjiajie, Hunan, China
Duration: 11 Apr 200912 Apr 2009

Publication series

Name2009 International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2009
Volume1

Conference

Conference2009 International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2009
Country/TerritoryChina
CityZhangjiajie, Hunan
Period11/04/0912/04/09

Keywords

  • Edge detection
  • Image processing
  • Multi-scale analysis
  • Self-adaptable filter
  • Wavelet transform

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