Image pattern algorithms using neural networks

T. Kasparis, G. Eichmann, M. Georgiopoulos, G. L. Heileman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The ability to classify texture regions in images is considered to be an important aspect of scene analysis. The information gained from such classification can be used by a computer vision system to assist in image segmentation as well as object identification. In this paper, the use of a neural network model in performing classification of images containing regular textures is investigated. The texture features used in the classification process are Hough transform-based descriptors. The performance and capabilities of the neural network approach are then compared to classical technique utilizing a linear associative memory.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsDavid P. Casasent, Adnrew G. Tescher
PublisherPubl by Int Soc for Optical Engineering
Pages298-306
Number of pages9
ISBN (Print)0819403482
StatePublished - 1990
Externally publishedYes
EventHybrid Image and Signal Processing II - Orlando, FL, USA
Duration: Apr 18 1990Apr 20 1990

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume1297
ISSN (Print)0277-786X

Conference

ConferenceHybrid Image and Signal Processing II
CityOrlando, FL, USA
Period4/18/904/20/90

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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