Visual Cortex Inspired Vertex and Corner Detection

Sets of corners and crossings in images characterize the shape and position of visual objects. The detection of these features not only supports, but is also a necessary condition to successful object recognition in human visual perception. Results in cognitive research have shown that the visual cortex has a mechanism for the detection of corners and crosses, and makes use of this in higher-level visual processing. In this paper, we propose an artificial neural architecture as a possible model for corner- and cross-sensitive cells - as an extension to the VFA (visual feature array) module. The model assumes a hierarchical structure of node-, endpoint-, crossand corner-sensitive cells. Through test results, the benefits of such a hierarchical structure is shown in terms of higher-level object recognition