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Automatic Threshold Setting for the Sequential Similarity Detection Algorithm

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2 Author(s)
M. Onoe ; Institute of Industrial Science, University of Tokyo ; M. Saito

This correspondence presents a method for automatic setting of both constant and increasing thresholds to be used with the sequential similarity detection algorithm (SSDA) for a fast registration of digitized images. No a priori knowledge of image statistics is required. The usefulness of the method is proven in the cloud tracking.

Published in:

IEEE Transactions on Computers  (Volume:C-25 ,  Issue: 10 )