skimage2.draw.circle_perimeter_aa#

skimage2.draw.circle_perimeter_aa(r, c, radius, shape=None)[source]#

Generate anti-aliased circle perimeter coordinates.

Parameters:

r, cint: Centre coordinate of circle.
radiusint: Radius of circle.
shapetuple, optional: Image shape which is used to determine the maximum extent of output pixel coordinates. This is useful for circles that exceed the image size. If None, the full extent of the circle is used. Must be at least length 2. Only the first two values are used to determine the extent of the input image.

Returns:

rr, cc, val(N,) ndarray (int, int, float): Indices of pixels (rr, cc) and intensity values (val). img[rr, cc] = val.

Notes

Wu’s method draws anti-aliased circle. This implementation doesn’t use lookup table optimization.

Use the function draw.set_color to apply circle_perimeter_aa results to color images.

References

[1]

X. Wu, “An efficient antialiasing technique”, In ACM SIGGRAPH Computer Graphics, 25 (1991) 143-152.

Examples

>>> from _skimage2.draw import circle_perimeter_aa
>>> img = np.zeros((10, 10), dtype=np.uint8)
>>> rr, cc, val = circle_perimeter_aa(4, 4, 3)
>>> img[rr, cc] = val * 255
>>> img
array([[  0,   0,   0,   0,   0,   0,   0,   0,   0,   0],
       [  0,   0,  60, 211, 255, 211,  60,   0,   0,   0],
       [  0,  60, 194,  43,   0,  43, 194,  60,   0,   0],
       [  0, 211,  43,   0,   0,   0,  43, 211,   0,   0],
       [  0, 255,   0,   0,   0,   0,   0, 255,   0,   0],
       [  0, 211,  43,   0,   0,   0,  43, 211,   0,   0],
       [  0,  60, 194,  43,   0,  43, 194,  60,   0,   0],
       [  0,   0,  60, 211, 255, 211,  60,   0,   0,   0],
       [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0],
       [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0]], dtype=uint8)

>>> from _skimage2 import data, draw
>>> image = data.chelsea()
>>> rr, cc, val = draw.circle_perimeter_aa(r=100, c=100, radius=75)
>>> draw.set_color(image, (rr, cc), [1, 0, 0], alpha=val)