Minimum variance centroid thresholding

Minimum variance centroid thresholding

Image-processing thresholding algorithms are extended segmentation tools that are suitable for tracking applications. The centroid of the tracked image distribution is a good point of reference for the location of the image. We describe a new thresholding technique that is based on the estimation of...

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Veröffentlicht in:Optics letters 2002-04, Vol.27 (7), p.497-499
Hauptverfasser: Arines, J, Ares, J
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Ares, J
description Image-processing thresholding algorithms are extended segmentation tools that are suitable for tracking applications. The centroid of the tracked image distribution is a good point of reference for the location of the image. We describe a new thresholding technique that is based on the estimation of the optimum threshold for achieving minimal variance in the centroid of the processed image. Experimental proofs for evaluating the technique's performance are given. The direct extension of these results to Shack-Hartmann wave-front sensors is also shown.
doi_str_mv 10.1364/OL.27.000497
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title Minimum variance centroid thresholding
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