Abstract
Template matching algorithms represent a viable tool to locate particles in optical images. A crucial factor of the performance of these methods is the choice of the similarity measure. Recently, it was shown in [Gao and Helgeson, Opt. Express 22 (2014)] that the correlation coefficient (CC) leads to good results. Here, we introduce the mutual information (MI) as a nonlinear similarity measure and compare the performance of the MI and the CC for different noise scenarios. It turns out that the mutual information leads to superior results in the case of signal dependent noise. We propose a novel approach to estimate the velocity of particles which is applicable in imaging scenarios where the particles appear elongated due to their movement. By designing a bank of anisotropic templates supposed to fit the elongation of the particles we are able to reliably estimate their velocity and direction of motion out of a single image.
Highlights
To gain information about the dynamics of a many particle system, which can in general be any system containing three or more particles, is of great interest in a wide range of research fields and especially in statistical physics
In this work we extended the method of particle detection by template matching introduced by [19] by the nonlinear similarity measure mutual information (MI) and a new template design
We show the difference in performance of the MI and the CC for particle detection depending on the type of noise applied to synthetic images
Summary
To gain information about the dynamics of a many particle system, which can in general be any system containing three or more particles, is of great interest in a wide range of research fields and especially in statistical physics. If one could estimate the velocity of a particle out of a single image one could overcome the problem related to the identification process or at least supply the tracking algorithm with additional information to improve its results At this point our second extension of the template matching technique of [19], which lies in the template itself, comes into play. We can take advantage of the information about the elongation of a particle to estimate its position, velocity and direction of motion simultaneously To achieve this simultaneous estimation we use a new set of anisotropic templates, with which we are able to measure the distance a particle traveled during exposure time. For example estimating the velocities of the particles for all time steps out of a series of images enables one to estimate important parameters such as the viscosity in a complex plasma [41, 42]
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