  Confocal microscopy of colloids combined with digital image processing has
become a powerful tool in soft matter physics and materials science. Together,
these techniques enable locating and tracking of more than half a million
individual colloidal particles at once. However, despite improvements in
locating algorithms that improve position accuracy, it remains challenging to
locate all particles in a densely-packed, three dimensional colloid without
erroneously identifying the same particle more than once. We present a simple,
iterative algorithm that mitigates both the "missed particle" and "double
counting" problems while simultaneously reducing sensitivity to the specific
choice of input parameters. It is also useful for analyzing images with
spatially-varying brightness in which a single set of input parameters is not
appropriate for all particles. The algorithm is easy to implement and
compatible with existing particle locating software.
