April 2020
Intermediate to advanced
438 pages
12h 2m
English
Content preview from Python Image Processing Cookbook
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Blob detection with morphological watershed
Perform the following steps to use the skimage.morphology module's watershed again, this time for blob detection:
- Implement the segment_with_watershed() function, which will detect the blobs in an image:
def segment_with_watershed(im, cell_thresh, bg_thresh): if np.max(im) != 1.0: im = (im - im.min()) / (im.max() - im.min()) im_mask = im < cell_thresh
- Generate the catchment, basins:
basins = np.zeros_like(im) basins[im < cell_thresh] = 2 basins[im > bg_thresh] = 1
- Run the watershed segmentation by flooding basins:
flood_seg = watershed(im , basins)flood_seg = flood_seg > 1.0
- Now, erode the boundaries and compute the distance transform:
selem = square(3) flood_erode = binary_erosion(flood_seg, ...
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