Edge Detection Algorithm for $Musca-Domestica$ Inspired Vision System

Compound vision sensors, mimicking the compound eye of the common housefly, possess motion hyperacuity, resulting in better motion detection and tracking capabilities as compared to traditional camera systems. Therefore, these sensors have applications requiring near instantaneous obstacle avoidance in its field-of-view. However, the obstacle detection algorithms used by current compound vision systems are insufficient to enable these capabilities due to their ability to only detect horizontal or vertical edges. In this paper, we propose an improved edge detection and location algorithm for fly inspired vision sensors which can correctly classify horizontal, vertical, forward diagonal, and backward diagonal edges.