Image Edge Extraction by Artificial Intelligence Schemes for UAV Autonomous Navigation

Abstract

We present here the application of an image processing strategy for autonomous navigation in order to estimate the position of an Unmanned Aerial Vehicle (UAV) equipped with Synthetic Aperture Radar (SAR) sensors. Patches of the SAR images are compared to georeferenced satellite optical images, by first applying an image edge detection algorithm on all the images, and the UAV position is determined from the correlation matrix obtained from resulting segmented images. The performance of three edge detectors are compared: the Canny approach, an artificial neural network (radial base function), and a fuzzy system.