threshold(image, selem, out=None, mask=None, shift_x=False, shift_y=False)

The resulting binary mask is True if the gray value of the center pixel is greater than the local mean.

Parameters

image : 2-D array (integer or float)

Input image.

selem : 2-D array (integer or float)

The neighborhood expressed as a 2-D array of 1's and 0's.

out : 2-D array (integer or float), optional

If None, a new array is allocated.

mask : ndarray (integer or float), optional

Mask array that defines (>0) area of the image included in the local neighborhood. If None, the complete image is used (default).

shift_x, shift_y : int, optional

Offset added to the structuring element center point. Shift is bounded to the structuring element sizes (center must be inside the given structuring element).

Returns

out : 2-D array (same dtype as input image)

Output image.

Local threshold of an image.

Examples

This example is valid syntax, but we were not able to check execution

>>> from skimage.morphology import square
... from skimage.filters.rank import threshold
... img = 255 * np.array([[0, 0, 0, 0, 0],
...                       [0, 1, 1, 1, 0],
...                       [0, 1, 1, 1, 0],
...                       [0, 1, 1, 1, 0],
...                       [0, 0, 0, 0, 0]], dtype=np.uint8)
... threshold(img, square(3))
array([[0, 0, 0, 0, 0],
       [0, 1, 1, 1, 0],
       [0, 1, 0, 1, 0],
       [0, 1, 1, 1, 0],
       [0, 0, 0, 0, 0]], dtype=uint8)

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

skimage.filters.rank.generic.threshold skimage.feature.blob.blob_log skimage.feature.blob.blob_dog skimage.feature.blob.blob_doh

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