Cellular Automata as a Means for Detecting Infrared Objects

The goal of the present work is to propose a novel cellular automata algorithm for infrared object detection.The algorithm's application is aimed towards computationally limited edge computing sensory modules.Performed is a statistical evaluation of the algorithm's noise resilience through a 3D histogram method.Proposed is a methodology for the optimal choice of the algorithm's fine-tuning parameter values.Proposed is the synthesis of a thermogram dataset based on Perlin/Simplex noise.The algorithm's resilience to apparent temperature modulation was evaluated, with this effect being resultant from physical, optical, and external environmental factorscausing objects to appear hotter or cooler than they actually are.