Authors: [tex2html_wrap4218]S.Shah, M.D.Levine
Investigator username: levine
Subcategory: sensor and processor design
At the retinal level, the strategies utilized by biological visual systems allow them to outperform machine vision systems, serving to motivate the design of electronic or "smart" sensors based on similar principles. Design of such sensors in silicon first requires a model of retinal information processing which captures the essential features exhibited by biological retinas.
In this project, a simple retinal model has been developed, which qualitatively accounts for the achromatic information processing in the primate cone system. The computer retina model exhibits many of the properties found in biological retinas such as data reduction through non-uniform sampling, adaptation to a large dynamic range of illumination levels, variation of visual acuity with illumination level, and enhancement of spatiotemporal contrast information. Experiments were performed to test the validity of the model and compare its outputs to published recordings of biological retinal neurons under similar test conditions.
REPORTS: 1. S. Shah and M.D. Levine, ``Information Processing in the Retina: A Biological Summary'', CIM-92-11. 2. S. Shah and M.D. Levine, ``Information Processing in the Primate Retina: A Model'', CIM-93-18. 3. S. Shah and M.D. Levine, ``Information Processing in the Primate Retina: Experiments and Results'', CIM-93-19. 4. S.Shah, ``An Adaptive Model of Information Processing in the Primate Retina'', M.Eng Thesis, Sept 1993, McGill U.