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).