Collaborative Research: A Visual System for Autonomous Foraminifera Identification

The goal of this project is to develop an automated system for identification of foraminifera (single-celled organisms with shells). Currently undergraduate workers are often employed to hand pick several thousands of specimens from ocean sediments for each study. This is tedious and time consuming work. By automating the bulk of the identification process, user expertise can be focused on verification and identification of subtle differences.

A visual identification system will be developed in order to automate the identification of target microorganisms. The visual system will incorporate a controllable LED lighting ring used to capture images by illuminating the specimens from several directions, mimicking an important step in the traditional identification process. These images will be used to create a 3D model of the organism in real-time within a second. Computer vision and pattern recognition techniques will be tuned to acceptable recognition rates set by feedback from an expert in paleoceanography who will also provide labeled samples for training and validation. The initial proof of concept study will focus on identifying six species of planktonic foraminifera, and their morphotypes, that are widely used by paleoceanographers.