Abstract
An ant colony optimization (ACO) based stereoscopic particle matching algorithm has been developed for three-dimensional (3-D) particle tracking velocimetry (PTV). In a stereoscopic particle pairing process, each individual particle in the left camera frame should be uniquely paired with the most probable correct partner in the right camera frame or vice-versa for evaluating the exact 3-D coordinate of the particles. In the present work, a new algorithm based on an ant colony optimization has been proposed for this stereoscopic particle matching. The algorithm is tested with various standard 3-D particle image velocimetry (PIV) images of the Visualization Society of Japan (VSJ) and the matching results show that the performance of the stereoscopic particle pairing is improved by applying proposed ACO techniques in comparison to the conventional nearest-neighbor particle pairing method of 3-D stereoscopic PTV.
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