OpenCV :: adaptiveThreshold()

Applies an adaptive threshold to an array.

void adaptiveThreshold(InputArray src, OutputArray dst, double maxValue, int adaptiveMethod, int thresholdType, int blockSize, double C)

Parameters:
src – Source 8-bit single-channel image.
dst – Destination image of the same size and the same type as src
maxValue – Non-zero value assigned to the pixels for which the condition is satisfied. See the details below
adaptiveMethod – Adaptive thresholding algorithm to use, ADAPTIVE_THRESH_MEAN_C or ADAPTIVE_THRESH_GAUSSIAN_C, See the details below.
thresholdType – Thresholding type that must be either THRESH_BINARY or THRESH_BINARY_INV
blockSize – Size of a pixel neighborhood that is used to calculate a threshold value for the pixel: 3, 5, 7, and so on
C – Constant subtracted from the mean or weighted mean (see the details below). Normally, it is positive but may be zero or negative as well

The function transforms a grayscale image to a binary image according to the formulae:

where T(x,y)is a threshold calculated individually for each pixel

For the method ADAPTIVE_THRESH_MEAN_C , the threshold value T(x,y) is a mean of the \texttt{blockSize} \times \texttt{blockSize} neighborhood of (x, y) minus C .

ADAPTIVE_THRESH_MEAN_C: 计算（x,y）为中心的方块内的均值 - C = （x,y）的值

For the method ADAPTIVE_THRESH_GAUSSIAN_C , the threshold value T(x, y) is a weighted sum (cross-correlation with a Gaussian window) of the \texttt{blockSize} \times \texttt{blockSize} neighborhood of (x, y) minus C . The default sigma (standard deviation) is used for the specified blockSize . See getGaussianKernel() .

ADAPTIVE_THRESH_GAUSSIAN_C：计算（x,y）为中心的高斯块（方块不同位置权重不一样）内的均值 - C = （x, y）的值