Lateral inhibition and the area operator in visual pattern processing

The static interaction of the receptor nerves in the lateral eye of the horsesoe crab, Limulus, is called lateral inhibition. It is described by the Hartline equations. A simulator has been built to study lateral inhibition with a view to applying it in a pre-processor for a visual pattern recogniti...

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Bibliographic Details
Main Author: Connor, Denis John
Language:English
Published: University of British Columbia 2011
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Online Access:http://hdl.handle.net/2429/36053
Description
Summary:The static interaction of the receptor nerves in the lateral eye of the horsesoe crab, Limulus, is called lateral inhibition. It is described by the Hartline equations. A simulator has been built to study lateral inhibition with a view to applying it in a pre-processor for a visual pattern recognition system. The activity in a lateral inhibitory receptor network is maximal in regions of non-uniform illumination. This enhancement of intensity contours has been extensively studied for the case of black and white patterns. It is shown that the level of activity near a black-white boundary provides a measure of its local geometric properites. However, the level of activity is dependent on the boundary orientation. A number of methods for reducing this orientation dependence are explored. The activity in a lateral inhibitory network adjacent to a boundary can be modelled by an area operator. It is shown that the value of this operator along an intensity boundary provides a description of the boundary that is related to its intrinsic description — curvature as a function of arc length. Since the operator is maximal on an intensity boundary, this description has been called the ridge function for the boundary. A ridge function can also be obtained using a lateral inhibitory, network. The properties of this function are discussed. It is shown how ridge functions might be incorporated into a pattern recognition algorithm. A novel method for detecting the bilateral and rotational symmetries in a pattern is described. === Applied Science, Faculty of === Electrical and Computer Engineering, Department of === Graduate