Abstract
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 language | English (US) |
---|---|
Pages (from-to) | 253-261 |
Number of pages | 9 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 2492 |
DOIs | |
State | Published - Apr 6 1995 |
Externally published | Yes |
Event | Applications and Science of Artificial Neural Networks 1995 - Orlando, United States Duration: Apr 17 1995 → Apr 21 1995 |
Keywords
- 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