ARTEMIdE—An Automated Underwater Material Recognition Method for Fluorescence LIDAR Invariant to Environmental Conditions

摘要

This article presents an automated underwater material recognition methodology for fluorescence light detection and ranging (LIDAR) invariant to environmental conditions (ARTEMIdE). Contrary to other state-of-the-art methods for submerged object recognition, ARTEMIdE can be applied when no a priori knowledge about environmental conditions is available and without resorting to any additional data besides the received signal and the fluorescence spectral signatures of the materials of interest. Experimental results over synthetic and real data show that ARTEMIdE is effective at automatically recognizing various object materials submerged at different depths within the water column. The presented approach reveals to provide great potential for many marine and submarine applications.