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Clathrin-coated pits and vesicles are found in all nucleated cells, from yeast to humans. They represent an important means by which proteins and lipids are removed from the plasma membrane and transported to an internal compartment. The biological question is this (Ehrlich, M. et al., Cell, vol.118, no.5, p.591-605, 2004): are there "hot spots" for the formation of clathrin-coated pits, or do pits and arrays form randomly on the plasma membrane? To answer this question we would like to track many hundreds of individual pits as they form, and track whether the pit is successful in forming a vesicle. We propose a novel polynomial fitting based multi-threshold approach for particle image segmentation. Simulated annealing is employed to find the optimal thresholds and an autoregression model is used to reduce the search space. A combined aspect ratio and size of particles method is proposed to isolate touching spots. In the particle tracking, a combined centroid and shape based method is proposed to deal with the ambiguous association problem. The proposed approach has been shown to identify and track many particles successfully.