Detection of Burmese pythons in the near-infrared versus visible band.

Abstract

Human task performance studies are commonly used for detecting and identifying potential military threats. In this work, these principles are applied to detection of an environmental threat: the invasive Burmese python. A qualitative detection of Burmese pythons with a visible light camera and an 850 nm near-infrared (NIR) camera was performed in natural Florida backgrounds. The results showed that the difference in reflectivity between the pythons and native foliage was much greater in NIR, effectively circumventing the python's natural camouflage in the visible band. In this work, a comparison of detection performance in the selected near-infrared band versus the visible band was conducted. Images of foliage backgrounds with and without a python were taken in each band in daylight and at night with illumination. Intensities of these images were then calibrated and prepared for a human perception test. Participants were tasked with detecting pythons, and the human perception data was used to compare performance between the bands. The results show that the enhanced contrast in the NIR enabled participants to detect pythons at 20% longer ranges than the use of visible imagery.