Adaptive basis matrix for the morphological function processing opening and closing

Kyung Hoon Lee, Aldo Morales, Sung-Jea Ko

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

A method for adaptation of the basis matrix of the gray-scale function processing (FP) opening and closing under the least mean square (LMS) error criterion is presented. We proposed the basis matrix for efficient representation of opening and closing in [1] and [2]. With this representation, the opening and closing operations are accomplished by a local matrix operation rather than cascade operation. Moreover, the analysis of the basis matrix shows that the basis matrix is skew symmetric, permitting to derive a simpler matrix representation for opening and closing operators. Furthermore, we propose an adaptation algorithm of the basis matrix for both opening and closing. The LMS and backpropagation algorithms are utilized for adaptation of the basis matrix. At each iteration of the adaptation process, the elements of the basis matrix are updated using the estimation of gradient to decrease the mean square error (MSE) between the desired signal and the actual filter output. Some results of optimal morphological filters applied to two-dimensional (2-D) images are presented.

Original languageEnglish
Pages (from-to)769-774
Number of pages6
JournalIEEE Transactions on Image Processing
Volume6
Issue number5
DOIs
Publication statusPublished - 1997 Dec 1

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ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Graphics and Computer-Aided Design
  • Software
  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition

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