McKinstry, Jeff
Coauthors(s): Jeffrey L. McKinstry (Point Loma Nazarene University, San Diego) Clark C. Guest (University of California, San Diego)
Point Loma Nazarene University
Math/Computer Science
3900 Lomaland Dr. San Diego, CA 92106
www.mcs.ptloma.edu/mckinstry/integratedv1paper.htm

A model of primary visual cortex applied to edge detection

The primary visual cortex (V1) in primates is known to perform edge analysis. A neural network model of V1 is proposed that integrates three of the most prominent features of the V1 architecture - complex-cells, long-range horizontal connections formed by Hebbian learning, and feature maps. The utility of the model is demonstrated on the problem of extracting edges from gray-scale photographs. This biologically based model outperforms the Canny edge operator with hysteresis when tested on a variety of gray-scale photographs with the local edge coherence metric of Kitchen and Rosenfeld.