%ADAPTIVETHRESHOLD  Applies an adaptive threshold to an array
%
%     dst = cv.adaptiveThreshold(src)
%     dst = cv.adaptiveThreshold(src, 'OptionName',optionValue, ...)
%
% ## Input
% * __src__ Source 8-bit single-channel `uint8` image.
%
% ## Output
% * __dst__ Destination image of the same size and the same type as `src`.
%
% ## Options
% * __MaxValue__ Non-zero value assigned to the pixels for which the condition
%   is satisfied. See the details below. default 255
% * __Method__ Adaptive thresholding algorithm to use, default 'Mean'. One of:
%   * __Mean__ the threshold value `T(x,y)` is a mean of the
%     `BlockSize x BlockSize` neighborhood of `(x,y)` minus `C`
%   * __Gaussian__ the threshold value `T(x,y)` is a weighted sum
%     (cross-correlation with a Gaussian window) of the `BlockSize x BlockSize`
%     neighborhood of `(x,y)` minus `C`. The default sigma (standard deviation)
%     is used for the specified `BlockSize`. See cv.getGaussianKernel
% * __Type__ Thresholding type, default 'Binary'. One of:
%   * __Binary__    `dst(x,y) = (src(x,y) > thresh) ? maxValue : 0`
%   * __BinaryInv__ `dst(x,y) = (src(x,y) > thresh) ? 0 : maxValue`
% * __BlockSize__ Size of a pixel neighborhood that is used to calculate a
%   threshold value for the pixel: 3, 5, 7, and so on. Default 3
% * __C__ Constant subtracted from the mean or weighted mean. Normally, it is
%   positive but may be zero or negative as well. Default 5
%
% The function transforms a grayscale image to a binary image according to
% the formulae:
%
% * __Binary__
%
%                  | maxValue, if src(x,y) > T(x,y)
%       dst(x,y) = |
%                  | 0, otherwise
%
% * __BinaryInv__
%
%                  | 0, if src(x,y) > T(x,y)
%       dst(x,y) = |
%                  | maxValue, otherwise
%
% where `T(x,y)` is a threshold calculated individually for each pixel (see
% `Method` parameter).
%
% Note: Internally the options `'BorderType','Replicate', 'Isolated',true` are
% used to process boundaries (see cv.copyMakeBorder).
%
% See also: cv.threshold, cv.blur, cv.GaussianBlur, adaptthresh, imbinarize
%
