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added full paper desc.

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Vighnesh Birodkar
2014-03-15 02:18:33 +05:30
parent d5f9ebfc8f
commit 630136ae91
2 changed files with 9 additions and 4 deletions
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skimage/feature/_hessian_det_appx.pyx
+3 -1
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@@ -94,7 +94,9 @@ def _hessian_det_appx(np.ndarray[np.int_t, ndim=2] image, float sigma):
References
----------
.. [1] ftp://ftp.vision.ee.ethz.ch/publications/articles/eth_biwi_00517.pdf
.. [1] Herbert Bay, Andreas Ess, Tinne Tuytelaars, Luc Van Gool,
"SURF: Speeded Up Robust Features"
ftp://ftp.vision.ee.ethz.ch/publications/articles/eth_biwi_00517.pdf
Notes
-----
skimage/feature/blob.py
+6 -3
View File
@@ -346,7 +346,10 @@ def blob_doh(image, min_sigma=1, max_sigma=30, num_sigma=10, threshold=500,
References
----------
.. [1] http://en.wikipedia.org/wiki/Blob_detection#The_determinant_of_the_Hessian
.. [2] ftp://ftp.vision.ee.ethz.ch/publications/articles/eth_biwi_00517.pdf
.. [2] Herbert Bay, Andreas Ess, Tinne Tuytelaars, Luc Van Gool,
"SURF: Speeded Up Robust Features"
ftp://ftp.vision.ee.ethz.ch/publications/articles/eth_biwi_00517.pdf
Examples
--------
@@ -377,10 +380,10 @@ def blob_doh(image, min_sigma=1, max_sigma=30, num_sigma=10, threshold=500,
deviation. Therefore detecting larger blobs won't take more time. In
methods line :py:meth:`blob_dog` and :py:meth:`blob_log` the computation
of Gaussians for larger `sigma` takes more time. The downside is that
this method can't be used for detecting blobs of radius less than `3px`
this method can't be used for detecting blobs of radius less than `3px`
due to the box filters used in the approximation of Hessian Determinant.
"""
if image.ndim != 2:
raise ValueError("'image' must be a grayscale ")