MATLAB File Help: cv.adaptiveThreshold | Index |

cv.adaptiveThreshold

Applies an adaptive threshold to an array

```
dst = cv.adaptiveThreshold(src)
dst = cv.adaptiveThreshold(src, 'OptionName',optionValue, ...)
```

**src**Source 8-bit single-channel`uint8`

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. 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).