Perfect image segmentation using pulse coupled neural networks

This paper describes a method for segmenting digital images using pulse coupled neural networks (PCNN). The pulse coupled neuron (PCN) model used in PCNN is a modification of the cortical neuron model of Eckhorn et al. (1990). A single layered laterally connected PCNN is capable of perfectly segmenting digital images even when there is a considerable overlap in the intensity ranges of adjacent regions. Conditions for perfect image segmentation are derived. It is also shown that addition of an inhibition receptive field to the neuron model increases the possibility of perfect segmentation. The inhibition input reduces the overlap of intensity ranges of adjacent regions by effectively compressing the intensity range of each region.