A new algorithm for training multi-layered morphological networks

Ricardo Barrón, Humberto Sossa, Benjamin Cruz

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

Abstract

In this work we present an algorithm for training an associative memory based on the so-called multi-layered morphological perceptron with maximal support neighborhoods. We compare the proposal with the original one by performing some experiments with real images. We show the superiority of the new one. We also give formal conditions for correct classification. We show that the proposal can be applied to the case of gray-level images and not only binary images.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis and Applications - 12th Iberoamerican Congress on Pattern Recognition, CIARP 2007, Proceedings
Pages546-555
Number of pages10
StatePublished - 2007
Event12th Iberoamerican Congress on Pattern Recognition, CIARP 2007 - Vina del Mar-Valparaiso, Chile
Duration: 13 Nov 200716 Nov 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4756 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th Iberoamerican Congress on Pattern Recognition, CIARP 2007
Country/TerritoryChile
CityVina del Mar-Valparaiso
Period13/11/0716/11/07

Keywords

  • Associative memories
  • Maximal support neighborhoods
  • Morphological neural networks

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