bwlabel
result =bwlabel(binary_img, [connectivity=8])(alias oflabel_blobs)
Input: binary_img, connectivity · Output: result
What it is
binary_img is a binary (0/255) Image. connectivity is an optional named number, 4 or 8 (default 8), the neighbor rule used for flood-fill labeling. Connected-component labeling.
Overloads
One call shape — this function is not overloaded.
| Code | Input | Output | Description |
result = bwlabel(binary_img, [connectivity=8]) (alias of label_blobs) | binary_img Imagebinary_img is a binary (0/255) Image.connectivity number, optional (default 8)connectivity is an optional named number, 4 or 8 (default 8), the neighbor rule used for flood-fill labeling. | Model —kind "blobs" | Returns a Model (kind "blobs") with fields .labels (a Mat of the same height/width as binary_img, integer label ids, background = 0), .count (a number, the blob count), .width, .height (the source image's own dimensions). |
Examples
From the documentation, and run by the build -- the output and the figure below are what the engine actually produced. Simplest first.
# Three bright discs on a dark field, written out and read back. The blob
# count printed below is then checkable against an image the reader can
# see being built, rather than asserted about a file nobody has.
n = 60
field = zeros(n, n)
centres = [15, 15; 42, 20; 30, 45]
for i in 0 to n - 1
for j in 0 to n - 1
for k in 0 to 2
dy = i - centres[k, 0]
dx = j - centres[k, 1]
if dy * dy + dx * dx < 64
field[i, j] = 230
end if
end for
end for
end for
save_image("cells.bmp", image_from_matrix(field))
img = load_image("cells.bmp")
level = otsu_threshold(img)
mask = threshold(img, level)
clean = bwareaopen(mask, 20) # drop specks smaller than 20 px
imshow(clean)
labeled = bwlabel(clean)
print(labeled.count) # number of detected blobs
stats = regionprops(labeled)
for i = 1 to labeled.count
r = stats[i - 1]
print(r.label, r.area, r.centroid_x, r.centroid_y)
end for
3 1 193 15 15 2 193 45 30 3 193 20 42
from images
How it works
label_blobs(binary_img, [connectivity=8]) (alias bwlabel) — connected-component labeling (see image::Image::label_components's doc comment for the flood-fill algorithm). Returns a Value::Model (kind "blobs", the multi-result-in-one-handle protocol this codebase's model values already use) rather than a tuple: .labels (a Value::Mat of integer label ids, background = 0), .count (blob count), plus .width/.height (the source image's own dimensions).
From the note above this builtin in the interpreter, where the reasoning was written down as it was built.