Normalized n-dimensional cross-correlation with a mask



Similar to normxcorrn, except takes an additional argument that specifies a figure ground mask for the T. That is T_fg must be of the same dimensions as T, with each entry being 0 or 1, where zero specifies regions to ignore (the ground) and 1 specifies interesting regions (the figure). Essentially T_fg specifies regions in T that are interesting and should be taken into account when doing normalized cross correlation. This allows for templates of arbitrary shape, and not just squares.

Note: this function is approximately 3 times slower then normxcorr2 because it cannot use the trick of precomputing sums.

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SKU: P2018F222_tool1 Category: