Neural Scene Segmentation by Oscillatory Correlation
Abstract
The segmentation of a visual scene into a set of coherent patterns (objects) is a fundamental aspect of perception, which underlies a variety of important tasks such as figure/ground segregation, and scene analysis. An innovative approach has been developed that uses neural oscillator networks to segment images. The framework, called oscillatory correlation, encodes the binding of pixels by phases of neural oscillators, resulting in a dynamical systems approach. The approach has been evaluated by computer simulations using both synthetic and real imagery, including intensity, range, motion, texture images. The results have been very competitive.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 2000
- Accession Number
- ADA374715
Entities
People
- DeLiang Wang
Organizations
- Ohio State University