A study of two different biological insect eye maps with artificial neural network processing

Roy E. Williams, Ron G. Driggers, William R. Clayton, Laura A. Anderson, Carl E. Halford

Research output: Contribution to journalConference articlepeer-review


Insect eyes have a large number of facets or lenses, also known as ommatidia or eyelets, with different arrangements of biological photoreceptors coupled to each eyelet. The output of each photoreceptor is coupled to sets of neurons where the optical information is processed. It is interesting to note that different insects are comprised of entirely different visual systems. These varying eyelet arrangements appear to be particular to the insect's habits and habitats. To test this premise, two very different insect ommatidia maps coupled to artificial neural network (NN) processors were modeled and simulated on a Silicon Graphics workstation. The performance of each ommatidia/NN system was tested in point source target location tasks and finite target location tasks in order to compare the two to each other and to man-made multi-aperture vision systems. The results of these simulations are presented.

Original languageEnglish (US)
Pages (from-to)253-261
Number of pages9
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - Apr 6 1995
Externally publishedYes
EventApplications and Science of Artificial Neural Networks 1995 - Orlando, United States
Duration: Apr 17 1995Apr 21 1995


  • Insect vision
  • Multi-aperture vision
  • Neural networks
  • Target tracking

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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