Abstract
The neurological process known as lateral inhibition (LI) has long been acknowledged as a critical operation for the preprocessing many types of sensory stimuli. In the mammalian retina, LI is utilized to enhance visual images by performing differential amplification upon the pixels from which the image is composed. This lends definition to an image by improving its contrast against its surroundings. With such pervasive feedback, LI is difficult to simulate in software, and was therefore characterized in hardware. In this study, lateral inhibition is implemented, using VLSI-based models. These models consist of small two dimensional arrays of generalized sensory pixels, each of which inhibits, and in turn is inhibited by each of its immediate neighbors. Two custom CMOS array prototypes circuits were designed, fabricated, and characterized. Test results indicate that both circuits are able to impart contrast to arbitrary two dimensional geometric images, and do so in a flexible yet stable manner. Being able to do so immediately and simultaneously, these arrays offer a level of performance not attainable by software methods. As such, this method is well suited for machine vision systems that utilize parallel architectures.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 955-961 |
| Number of pages | 7 |
| Journal | IEEE Transactions on Neural Networks |
| Volume | 4 |
| Issue number | 6 |
| DOIs | |
| State | Published - Nov 1993 |
All Science Journal Classification (ASJC) codes
- Software
- Computer Science Applications
- Computer Networks and Communications
- Artificial Intelligence