Accurate particle position measurement from images

TL;DR

This paper analyzes the sources of error in particle position measurement using the moment method, proposing an optimized algorithm that achieves sub-pixel accuracy and reduces pixel locking artifacts.

Contribution

It introduces an algorithm with optimal parameters for minimizing measurement errors and pixel locking in particle position estimation from images.

Findings

Achieves sub-pixel accuracy of 0.017 pixels or better.

Provides insights into error sources and their dependence on experimental parameters.

Offers improvements applicable to particle tracking in various scientific fields.

Abstract

The moment method is an image analysis technique for sub-pixel estimation of particle positions. The total error in the calculated particle position includes effects of pixel locking and random noise in each pixel. Pixel locking, also known as peak locking, is an artifact where calculated particle positions are concentrated at certain locations relative to pixel edges. We report simulations to gain an understanding of the sources of error and their dependence on parameters the experimenter can control. We suggest an algorithm, and we find optimal parameters an experimenter can use to minimize total error and pixel locking. Simulating a dusty plasma experiment, we find that a sub-pixel accuracy of 0.017 pixel or better can be attained. These results are also useful for improving particle position measurement and particle tracking velocimetry (PTV) using video microscopy, in fields including colloids, biology, and fluid mechanics.