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This method assesses the similarity between two binary images, while accounting for subtle differences in image alignment and size.
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This yields three binary images consisting of binary blobs that may contain a pupil.
The three binary images are summed to create a new composited image (Fig. 2e).
In this application, we have used six binary images, each described by three abovementioned measures.
The SADs between two binary molds represents the total number of mismatched pixels.
Hamming distance is the number of bits which differ between two binary strings.
(Cf. blue stragglers) A likely scenario is a collision with a binary star system, or between two binary systems containing white dwarfs.
DISCRETE tests for correlated evolution between two binary traits by comparing the fit of two continuous-time Markov models.
The MCC represents a Pearson correlation between two binary vectors.
Correlations between two binary variables were examined using a Pearson χ test.
Tetrachoric correlation provides a measure of agreement between two binary variables in estimating what the Pearson correlation would be if binary ratings were made on a continuous scale.
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