Sure - thanks. from skimage.morphology import disk from skimage.feature import canny from scipy import ndimage as ndi import matplotlib.pyplot as plt image = disk(100) for ix in range(200): for iy in range(200): xdel=ix-100 ydel=iy-100 if (xdel*xdel/50 + ydel*ydel/10) < 110: image[iy,ix]=0 elif (xdel*xdel/10 + ydel*ydel/50) < 110: image[iy,ix]=0 edges = canny(image*255.) # canny expect grayscale, i.e. 0-255 ??! fill = ndi.binary_fill_holes(edges) # I don't understand the params; can I seed a region to fill? fig, axes = plt.subplots(ncols=3, figsize=(9, 3)) ax = axes.ravel() ax[0].imshow(image, cmap=plt.cm.gray, interpolation='nearest') #ax[0].imshow(invert_img, cmap=plt.cm.gray) #ax[0].set_title('Inverted image') ax[0].set_title('Original image') ax[1].imshow(edges*1, cmap=plt.cm.gray, interpolation='nearest') ax[1].set_title('Canny edges') ax[2].imshow(fill, cmap=plt.cm.spectral, interpolation='nearest') ax[2].set_title('Fill') plt.show() On Sun, Jan 7, 2018 at 6:57 PM, Juan Nunez-Iglesias <jni.soma@gmail.com> wrote:

Hi Randy, I was going to suggest binary fill holes. Do you mind posting your image and the code you’ve tried so we can troubleshoot?

Thanks,

Juan.

On 8 Jan 2018, 9:48 AM +1100, Randy Heiland <randy.heiland@gmail.com>, wrote:

If I have a binary image with, say, just a contour boundary (simple example: a white background with a black circle, i.e. an "o"), how can I fill the inside of the contour? I've played with both the watershed segmentation and the scipy.ndimage.binary_fill_holes, without success.

thanks, Randy _______________________________________________ scikit-image mailing list scikit-image@python.org https://mail.python.org/mailman/listinfo/scikit-image

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