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Implemented FAST corner detector

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Ankit Agrawal
2013-08-20 00:57:12 +05:30
committed by Johannes Schönberger
parent 03980b10ee
commit 5f1976ace2
5 changed files with 110 additions and 27 deletions
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bento.info
+3
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@@ -102,6 +102,9 @@ Library:
Extension: skimage.feature.corner_cy
Sources:
skimage/feature/corner_cy.pyx
Extension: skimage.feature.fast_cy
Sources:
skimage/feature/fast_cy.pyx
Extension: skimage.feature._texture
Sources:
skimage/feature/_texture.pyx
skimage/feature/__init__.py
+10 -2
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@@ -7,7 +7,10 @@ from .corner import (corner_kitchen_rosenfeld, corner_harris,
corner_peaks)
from .corner_cy import corner_moravec
from .template import match_template
from ._brief import brief, match_keypoints_brief
from .util import pairwise_hamming_distance
from .censure import keypoints_censure
from .fast import corner_fast
__all__ = ['daisy',
'hog',
@@ -22,4 +25,9 @@ __all__ = ['daisy',
'corner_subpix',
'corner_peaks',
'corner_moravec',
'match_template']
'match_template',
'brief',
'pairwise_hamming_distance',
'match_keypoints_brief',
'keypoints_censure',
'corner_fast']
skimage/feature/fast.py
+12 -25
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@@ -1,35 +1,22 @@
import numpy as np
from ..util import img_as_float
from scipy.ndimage.filters import maximum_filter
from fast_cy import _corner_fast
def corner_fast(image, n=9, threshold=0.15):
def corner_fast(image, n=12, threshold=0.15):
image = np.squeeze(image)
if image.ndim != 2:
raise ValueError("Only 2-D gray-scale images supported.")
image = img_as_float(image)
corner_mask = np.zeros(image.shape, dtype=bool)
image = np.ascontiguousarray(image, dtype=np.double)
corner = _corner_fast(image, n, threshold)
test_pixels = np.asarray([[-3, 0], [-3, 1], [-2, 2], [-1, 3], [0, 3],
[1, 3], [2, 2], [3, 1], [3, 0], [3, -1],
[2, -2], [1, -3], [0, -3], [-1, -3],
[-2, -2], [-1, -3]])
corner_zero_mask = corner != 0
c, d = np.nonzero(corner)
# TODO : Outsource to Cython
for i in range(3, image.shape[0] - 3):
for j in range(3, image.shape[1] - 3):
test_x = i + test_pixels[:, 0]
test_y = j + test_pixels[:, 1]
intensities = image[test_x, test_y]
low = intensities < image[i, j] - threshold
high = intensities > image[i, j] + threshold
low = np.concatenate(low, low)
high = np.concatenate(high, high)
# How to check if a sequence n * [True] exists in low/high ?
# if n * [True] in low or n * True in high:
# corner_mask[i, j] = True
corner_x, corner_y = np.where(corner_mask == True)
corners = np.dstack(corner_x, corner_y)
return corners
maximas = (maximum_filter(corner, (3, 3)) == corner) & corner_zero_mask
x, y = np.where(maximas == True)
return np.squeeze(np.dstack((x, y)))
skimage/feature/fast_cy.pyx
+82
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@@ -0,0 +1,82 @@
#cython: cdivision=True
#cython: boundscheck=False
#cython: nonecheck=False
#cython: wraparound=False
import numpy as np
from ..util import img_as_float
def _corner_fast(double[:, ::1] image, int n, double threshold):
cdef int[:] rp = (np.round(3 * np.sin(2 * np.pi * np.arange(16, dtype=np.double) / 16))).astype(np.int32)
cdef int[:] cp = (np.round(3 * np.cos(2 * np.pi * np.arange(16, dtype=np.double) / 16))).astype(np.int32)
cdef Py_ssize_t rows = image.shape[0]
cdef Py_ssize_t cols = image.shape[1]
cdef Py_ssize_t i, j, k, l, m
cdef char[:] bins
cdef int consecutive_count = 0
cdef double sum_b
cdef double sum_d
cdef double[:, ::1] corner = np.zeros((rows, cols), dtype=np.double)
cdef double circle_intensity
for i in range(3, rows - 3):
for j in range(3, cols - 3):
bins = np.zeros(16, dtype='S1')
sum_b = 0
sum_d = 0
for k in range(16):
circle_intensity = image[i + rp[k], j + cp[k]]
if circle_intensity > image[i, j] + threshold:
bins[k] = 'b'
elif circle_intensity < image[i, j] - threshold:
bins[k] = 'd'
else:
bins[k] = 's'
consecutive_count = 0
for l in range(15 + n):
if bins[l % 16] == 'b':
consecutive_count += 1
if consecutive_count == n:
for m in range(16):
if bins[m] == 'b':
sum_b += image[i + rp[m], j + cp[m]] - image[i, j] - threshold
elif bins[m] == 'd':
sum_d += image[i, j] - image[i + rp[m], j + cp[m]] - threshold
if sum_d > sum_b:
corner[i, j] = sum_d
else:
corner[i, j] = sum_b
break
else:
consecutive_count = 0
if corner[i, j] == 0:
consecutive_count = 0
for l in range(15 + n):
if bins[l % 16] == 'd':
consecutive_count += 1
if consecutive_count == n:
for m in range(16):
if bins[m] == 'b':
sum_b += image[i + rp[m], j + cp[m]] - image[i, j] - threshold
elif bins[m] == 'd':
sum_d += image[i, j] - image[i + rp[m], j + cp[m]] - threshold
if sum_d > sum_b:
corner[i, j] = sum_d
else:
corner[i, j] = sum_b
break
else:
consecutive_count = 0
return np.asarray(corner)
skimage/feature/setup.py
+3
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@@ -14,6 +14,7 @@ def configuration(parent_package='', top_path=None):
cython(['corner_cy.pyx'], working_path=base_path)
cython(['censure_cy.pyx'], working_path=base_path)
cython(['fast_cy.pyx'], working_path=base_path)
cython(['_brief_cy.pyx'], working_path=base_path)
cython(['_texture.pyx'], working_path=base_path)
cython(['_template.pyx'], working_path=base_path)
@@ -22,6 +23,8 @@ def configuration(parent_package='', top_path=None):
include_dirs=[get_numpy_include_dirs()])
config.add_extension('censure_cy', sources=['censure_cy.c'],
include_dirs=[get_numpy_include_dirs()])
config.add_extension('fast_cy', sources=['fast_cy.c'],
include_dirs=[get_numpy_include_dirs()])
config.add_extension('_brief_cy', sources=['_brief_cy.c'],
include_dirs=[get_numpy_include_dirs()])
config.add_extension('_texture', sources=['_texture.c'],