In this paper, we propose a new algorithm based on radial symmetry center method to track colloidal particles close to contact, where the optical images of the particles start to overlap in digital video microscopy. This overlapping effect is important to observe the pair interaction potential in colloidal studies and it appears as additional interaction in the measurement of the interaction with conventional tracking analysis. The proposed algorithm in this work is simple, fast and applicable for not only two particles but also three and more particles without any modification. The algorithm uses gradient vectors of the particle intensity distribution, which allows us to use a part of the symmetric intensity distribution in the calculation of the actual particle position. In this study, simulations are performed to see the performance of the proposed algorithm for two and three particles, where the simulation images are generated by using fitted curve to experimental particle image for different sized particles. As a result, the algorithm yields the maximum error smaller than 2nm for 5.53µm silica particles in contact condition.

In this paper, we demonstrated that an optical tweezer setup can be calibrated by using a part of the symmetric intensity distribution of the trapped particle in digital video microscopy. First, we modified the radial symmetry center method, which was a recently proposed position detection algorithm. This algorithm uses gradient vectors of the particle intensity distribution, which allows us to use a part of the symmetric intensity distribution in the calculation of the particle center. We applied the modified algorithm to different camera image configurations, which are obtained by cutting the same experimental video frames. We further calibrated the trap stiffness for each camera configuration. Then we compared the trap stiffness values and the position distributions. As a result, we can conclude that optical tweezer setups can be calibrated by using a part of the intensity distribution of the trapped particle.

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Automated particle tracking algorithms are widely used by soft matter physicists as a research tool to detect and construct the trajectories of micron-sized particles in fluids. Analyzing these trajectories will uncover the physics of the investigated particles mainly on the type of motion they undergo making them suitable for potential applications. A plethora of methods has been proposed and used for detection and tracking. In this work, we examine the performance of two commonly used tracking algorithms in terms of threshold dependencies in digital video images. One of them is the centroid method (CM), a well-known and used algorithm and the other is radial symmetry method (RSM) which is recently proposed. Here, we generate the synthetic digital video images consisting of randomly placed multiple particles and compare the absolute errors on the particle detection by varying threshold values. Our results suggest that both algorithms show dependence on the threshold value and on comparison RSM algorithm performs better than the CM algorithm when the noise level is zero. Moreover, the measured absolute errors show a strong dependence on threshold values when noise levels are increased (up to 20) especially for the RSM algorithm.