Soft vector morphological gradient operators

Tao Lei, Yang Yu Fan, Xiao Peng Wang

Research output: Contribution to journalArticlepeer-review

Abstract

Since classical morphological gradient operator cannot be directly extended to color image processing, the existing vector morphological gradient operator is sensitive to noise and it has low performance. This paper proposes a new soft vector morphological gradient operator and applies it in the edge detection of color images in order to solve the problem. New morphological gradient operator takes the advantage of soft morphology theory, which effectively reduces the influence of noise on the edge, so as to improve the anti-interference ability of the vector morphological gradient operator. Experimental results show that compared with the existing vector morphological gradient operators, the new soft vector morphology gradient operators achieve better gradient vector in the case of noise, and plays an important role in the following steps of color image segmentation and recognition.

Original languageEnglish
Pages (from-to)910-916
Number of pages7
JournalDianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China
Volume43
Issue number6
DOIs
StatePublished - 30 Nov 2014

Keywords

  • Color image processing
  • Edge detection
  • Soft morphological operators
  • Vector ordering

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