Generalized skeleton formation for texture segmentation

Zs Marczell, Zs Kalmar, A. Lorincz

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

An algorithm and an artificial neural architecture that approximates the algorithm are proposed for the formation of generalized skeleton transformations. The algorithm includes the original grassfire proposal of Blum and is extended with an integrative on-center off-surround detector system. It is shown that the algorithm can elicit textons by skeletonization. Slight modification of the architecture corresponds to the Laplace transformation followed by full wave rectification, another algorithm for texture discrimination proposed by Bergen and Adelson.

Original languageEnglish
Pages (from-to)79-87
Number of pages9
JournalNeural Network World
Volume6
Issue number1
Publication statusPublished - Jan 1 1996

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ASJC Scopus subject areas

  • Software
  • Neuroscience(all)
  • Hardware and Architecture
  • Artificial Intelligence

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