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Transform corner_fast_orientations for application to arbitrary corner types

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This commit is contained in:
Johannes Schönberger
2013-11-29 20:42:04 +01:00
parent 1aef50ca8f
commit 07623e1965
3 changed files with 70 additions and 36 deletions
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skimage/feature/__init__.py
+2 -2
View File
@@ -5,7 +5,7 @@ from .peak import peak_local_max
from .corner import (corner_kitchen_rosenfeld, corner_harris,
corner_shi_tomasi, corner_foerstner, corner_subpix,
corner_peaks, corner_fast)
from .corner_cy import corner_moravec, corner_fast_orientation
from .corner_cy import corner_moravec, corner_orientations
from .template import match_template
from ._brief import brief, match_keypoints_brief
from .util import pairwise_hamming_distance
@@ -30,4 +30,4 @@ __all__ = ['daisy',
'match_keypoints_brief',
'keypoints_censure',
'corner_fast',
'corner_fast_orientation']
'corner_orientations']
skimage/feature/corner.py
-1
View File
@@ -581,7 +581,6 @@ def corner_fast(image, n=12, threshold=0.15):
Examples
--------
>>> import numpy as np
>>> from skimage.feature import corner_fast, corner_peaks
>>> square = np.zeros((12, 12))
>>> square[3:9, 3:9] = 1
skimage/feature/corner_cy.pyx
+68 -33
View File
@@ -167,25 +167,29 @@ def _corner_fast(double[:, ::1] image, char n, double threshold):
return np.asarray(corner_response)
def corner_fast_orientation(image, Py_ssize_t[:, :] fast_corners):
"""Compute the orientation of FAST corners.
def corner_orientations(image, Py_ssize_t[:, :] corners, mask):
"""Compute the orientation of corners.
The orientation of corners is computed using the first order central
moment i.e. the center of mass approach. The corner orientation is the
angle of the vector from the keypoint to the intensity centroid calculated
using first order central moment.
The orientation of corners is computed using the first order central moment
i.e. the center of mass approach. The corner orientation is the angle of
the vector from the corner coordinate to the intensity centroid in the
local neighborhood around the corner calculated using first order central
moment.
Parameters
----------
image : 2D array
Input grayscale image.
fast_corners : (N, 2) array
FAST corners extracted from the corresponding image.
corners : (N, 2) array
Corner coordinates as ``(row, col)``.
mask : 2D array
Mask defining the local neighborhood of the corner used for the
calculation of the central moment.
Returns
-------
orientation : (N, 1) array
Orientation of the input FAST corners in the range [-pi, pi].
orientations : (N, 1) array
Orientations of corners in the range [-pi, pi].
References
----------
@@ -195,41 +199,72 @@ def corner_fast_orientation(image, Py_ssize_t[:, :] fast_corners):
..[2] Paul L. Rosin, "Measuring Corner Properties"
http://users.cs.cf.ac.uk/Paul.Rosin/corner2.pdf
Examples
--------
>>> from skimage.morphology import octagon
>>> from skimage.feature import corner_fast, corner_peaks, \
... corner_orientations
>>> square = np.zeros((12, 12))
>>> square[3:9, 3:9] = 1
>>> square
array([[ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 1., 1., 1., 1., 1., 1., 0., 0., 0.],
[ 0., 0., 0., 1., 1., 1., 1., 1., 1., 0., 0., 0.],
[ 0., 0., 0., 1., 1., 1., 1., 1., 1., 0., 0., 0.],
[ 0., 0., 0., 1., 1., 1., 1., 1., 1., 0., 0., 0.],
[ 0., 0., 0., 1., 1., 1., 1., 1., 1., 0., 0., 0.],
[ 0., 0., 0., 1., 1., 1., 1., 1., 1., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]])
>>> corner_peaks(corner_fast(square, 9), min_distance=1)
array([[3, 3],
[3, 8],
[8, 3],
[8, 8]])
>>> orientations = corner_orientations(square, corners, octagon(3, 2))
>>> np.rad2deg(orientations)
array([ 45., 135., -45., -135.])
"""
image = np.squeeze(image)
if image.ndim != 2:
raise ValueError("Only 2-D gray-scale images supported.")
cdef double[:, :] cimage = img_as_float(image)
# Essentially skimage.morphology.octagon(3, 2)
cdef char[:, ::1] circular_mask = np.array([[0, 0, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 0, 0]], dtype=np.uint8)
if mask.shape[0] % 2 != 1 or mask.shape[1] % 2 != 1:
raise ValueError("Size of mask must be uneven.")
cdef Py_ssize_t n_fast_corners = fast_corners.shape[0]
cdef Py_ssize_t i, r, c, y_top, x_left
cdef double[:] kp_orientation = np.zeros(fast_corners.shape[0], dtype=np.double)
cdef double[:, :] cimage = img_as_float(image)
cdef char[:, ::1] cmask = np.ascontiguousarray(mask != 0, dtype=np.uint8)
cdef Py_ssize_t i, r, c, r0, c0
cdef Py_ssize_t mrows = mask.shape[0]
cdef Py_ssize_t mcols = mask.shape[1]
cdef Py_ssize_t mrows2 = (mrows - 1) / 2
cdef Py_ssize_t mcols2 = (mcols - 1) / 2
cdef double[:] orientations = np.zeros(corners.shape[0], dtype=np.double)
cdef double curr_pixel
cdef double m00, m01, m10
for i in range(n_fast_corners):
y_top = fast_corners[i, 0] - 3
x_left = fast_corners[i, 1] - 3
for i in range(corners.shape[0]):
r0 = corners[i, 0] - mrows2
c0 = corners[i, 1] - mcols2
m00 = 0
m01 = 0
m10 = 0
for r in range(7):
for c in range(7):
if circular_mask[r, c]:
m00 += cimage[y_top + r, x_left + c]
m01 += cimage[y_top + r, x_left + c] * (c - 3)
m10 += cimage[y_top + r, x_left + c] * (r - 3)
kp_orientation[i] = atan2(m10 / m00, m01 / m00)
for r in range(mrows):
for c in range(mcols):
if cmask[r, c]:
curr_pixel = cimage[r0 + r, c0 + c]
m00 += curr_pixel
m01 += curr_pixel * (c - mcols2)
m10 += curr_pixel * (r - mrows2)
return np.asarray(kp_orientation)
orientations[i] = atan2(m10 / m00, m01 / m00)
return np.asarray(orientations)