Shape-Independent Methods for Particle Identification

Accurate particle identification from microscopy images and image volumes is critical for computing direct space order parameters and is an important first step for temporal tracking. Original work by Crocker and Grier was undertaken to identify spherical particle centers; this work has been expanded by many scientists on a case-by-base basis to track various types of anisotropic particles as more exotic self-assembling building blocks have been fabricated. We review a number of existing techniques and present a general, shape-agnostic framework for determining the position and orientation of anisotropic particles alongside a suite of particle identification tools written in python and C++. We discuss the accuracy of our method and results from the a study of oblate PMMA spheroids and 3d-printed polygonal air-hockey pucks.