Robotic platform for real-time tracking of a single fast swimming bacterium

Abstract

In this paper we present a hardware architecture with software implementation able to track free swimming single 2μm in diameter MC-1 bacterium. The computer vision system operates at up to 77 fps at full speed and up to 24 fps when recording full 512×512 pixels frame from coupled-charge device (CCD) array. Closed-loop control with lock-in tracking is achieved using the Otsu Segmentation Method (OSM) with a cubic spline model-based predictive algorithm. Using the system, speed distribution of MC-1 cells has been recorded showing a m ean speed of 200μm/s. Tracking is demonstrated over a range of a few millimeters during 30 sec.