Full field measurement methods require digital image processing algorithms to accomplish centroid identification of components of the image of a deforming structure and track them through subsequent video frames in order to establish displacement and strain measurements. Unfortunately, these image processing algorithms are the most computationally expensive tasks performed in such methods. In this work we present a set of new algorithms that can be used to identify centroids of image features that are shown to be orders of magnitude faster than conventional algorithms. These algorithms are based on employing efficient data structures and algorithmic flows tailored to optimally fit in shared memory parallel architectures.

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