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


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
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
ISSN (Print)0277-786X


ConferenceHybrid Image and Signal Processing II
CityOrlando, FL, USA

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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