Reference Free Framework for Bio-Inspired Real-Time Motion Detector

This work proposes a framework for identification of moving objects by incorporating primary response channels of the retina in patients suffering from degenerative defects. The goal is to significantly revive the primary visual sensations such as directional movement detection and differentiation of static and moving objects. A biological neural network (BNN) is proposed that can identify the direction of moving object based on the concepts of neural coding and mean firing rate (MFR). Our model is based on spiking neuron models (SNM), that is close to leaky integrate and fire principle and the Hodgkin-Huxley principle. Proposed neural network architecture performs directional movement detection depending on spiking behavior of neuron groups. It is capable of identifying movements in any direction depending on the delay profile of identical spiking behavior observed between two distant neuron colonies. Our results show that, proposed network model resembles the actual motion processing visual path way of the human retina.