Though the mechanism called lateral inhibition exists among the visual cells, visual information can be selectively
detected. By simulating this mechanism among visual cells through a mathematical method, a lateral inhibition neural
network is proposed. A method of image segmentation based on this model with partial reset is presented. The simulation
results show that partial reset may allow a fine control of the irregularity of the spike trains. In image segmentation,
experimental results show that the lateral inhibition neural network with partial reset is more effective than the neural network
with constant threshold by quantificationally evaluating their performance.