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Single-particle tracking is computationally a challenging problem, and usually solved with local methods. Local methods suffer from defects in the image data or in the detection of particles, such as temporal disappearing of particles. A particle tracking method has to provide a solution also to real disappearing and appearing of particles as a result of merging and splitting. Here, we present an efficient, greedy algorithm as a solution to the particle tracking problem. This improved local method is application independent, as it has high configurability of the function used to solve particle correspondence. To demonstrate the accuracy of the method, we apply it to real microscopy image data with the BioImageXD software, validate it using simulated image data, and compare it to a well-known existing method.