A robust particle detection algorithm based on symmetry
This addresses the challenge of reliable particle tracking in biophysical, ecological, and micro-fluidic applications under real-world noise and lighting fluctuations.
The paper tackled the problem of particle detection in noisy environmental conditions by proposing the Circular Symmetry algorithm (C-Sym), which achieved the highest accuracy and precision compared to four other methods in synthetic and experimental datasets.
Particle tracking is common in many biophysical, ecological, and micro-fluidic applications. Reliable tracking information is heavily dependent on of the system under study and algorithms that correctly determines particle position between images. However, in a real environmental context with the presence of noise including particular or dissolved matter in water, and low and fluctuating light conditions, many algorithms fail to obtain reliable information. We propose a new algorithm, the Circular Symmetry algorithm (C-Sym), for detecting the position of a circular particle with high accuracy and precision in noisy conditions. The algorithm takes advantage of the spatial symmetry of the particle allowing for subpixel accuracy. We compare the proposed algorithm with four different methods using both synthetic and experimental datasets. The results show that C-Sym is the most accurate and precise algorithm when tracking micro-particles in all tested conditions and it has the potential for use in applications including tracking biota in their environment.