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Vighnesh Birodkar
2014-03-11 22:24:08 +05:30
parent 815b0226d4
commit 6e6b27bc86
1 changed files with 7 additions and 5 deletions
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skimage/feature/blob.py
+7 -5
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@@ -99,7 +99,8 @@ def blob_dog(image, min_sigma=1, max_sigma=50, sigma_ratio=1.6, threshold=2.0,
"""Finds blobs in the given grayscale image.
Blobs are found using the Difference of Gaussian (DoG) method[1]_.
For each blob found, its coordinates and area are returned.
For each blob found, the method returns its coordinates and the standard
deviation of the Gaussian kernel that detected the blob.
Parameters
----------
@@ -137,7 +138,7 @@ def blob_dog(image, min_sigma=1, max_sigma=50, sigma_ratio=1.6, threshold=2.0,
Examples
--------
>>> from skimage import data, feature
>>> feature.blob_dog(data.coins(),threshold=.5,max_sigma=40)
>>> feature.blob_dog(data.coins(), threshold=.5, max_sigma=40)
array([[ 45, 336, 16],
[ 52, 155, 16],
[ 52, 216, 16],
@@ -204,7 +205,8 @@ def blob_log(image, min_sigma=1, max_sigma=50, num_sigma=10, threshold=.2,
"""Finds blobs in the given grayscale image.
Blobs are found using the Laplacian of Gaussian (LoG) method[1]_.
For each blob found, its coordinates and area are returned.
For each blob found, the method returns its coordinates and the standard
deviation of the Gaussian kernel that detected the blob.
Parameters
----------
@@ -247,8 +249,8 @@ def blob_log(image, min_sigma=1, max_sigma=50, num_sigma=10, threshold=.2,
--------
>>> from skimage import data, feature, exposure
>>> img = data.coins()
>>> img = exposure.equalize_hist(img) # improves detection
>>> feature.blob_log(img,threshold = .3)
>>> img = exposure.equalize_hist(img)# improves detection
>>> feature.blob_log(img, threshold = .3)
array([[113, 323, 1],
[121, 272, 17],
[124, 336, 11],