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Adds FilterResponse for OctagonFilter
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‎src/censure.jl‎

Lines changed: 128 additions & 62 deletions
Original file line numberDiff line numberDiff line change
@@ -14,11 +14,14 @@ end
1414

1515
type OctagonFilter <: BiFilter
1616

17-
filter :: Array{Float64, 2}
18-
m_out :: UInt8
19-
m_in :: UInt8
20-
n_out :: UInt8
21-
n_in :: UInt8
17+
m_out :: Integer
18+
m_in :: Integer
19+
n_out :: Integer
20+
n_in :: Integer
21+
in_area :: Float64
22+
out_area :: Float64
23+
in_weight :: Float64
24+
out_weight :: Float64
2225

2326
end
2427

@@ -33,33 +36,21 @@ type CENSURE <: Detector
3336

3437
end
3538

36-
function createFilter(OF::OctagonFilter)
37-
area_out = (OF.m_out + 2 * OF.n_out) ^ 2 - 2 * OF.n_out ^ 2
38-
area_in = (OF.m_in + 2 * OF.n_in) ^ 2 - 2 * OF.n_in ^ 2
39-
weight_out = 1.0/(area_out - area_in)
40-
weight_in = 1.0/area_in
41-
OF.filter[:, :] = weight_out
42-
inner_start = Int(0.5 * ((OF.m_out + 2 * OF.n_out) - (OF.m_in + 2 * OF.n_in)))
43-
OF.filter[inner_start + 1 : end - inner_start, inner_start + 1 : end - inner_start] = weight_in
44-
45-
for i in 1:OF.n_in
46-
OF.filter[inner_start + i, inner_start + 1 : inner_start + OF.n_in - i + 1] = weight_out
47-
OF.filter[inner_start + i, inner_start + OF.n_in + OF.m_in + i : inner_start + OF.m_in + 2 * OF.n_in] = weight_out
48-
OF.filter[inner_start + OF.m_in + 2 * OF.n_in - i + 1, inner_start + 1 : inner_start + OF.n_in - i + 1] = weight_out
49-
OF.filter[inner_start + OF.m_in + 2 * OF.n_in - i + 1, inner_start + OF.n_in + OF.m_in + i : inner_start + OF.m_in + 2 * OF.n_in] = weight_out
50-
end
51-
52-
for i in 1:OF.n_out
53-
OF.filter[i, 1 : OF.n_out - i + 1] = 0
54-
OF.filter[i, OF.n_out + OF.m_out + i : OF.m_out + 2 * OF.n_out] = 0
55-
OF.filter[OF.m_out + 2 * OF.n_out - i + 1, 1 : OF.n_out - i + 1] = 0
56-
OF.filter[OF.m_out + 2 * OF.n_out - i + 1, OF.n_out + OF.m_out + i : OF.m_out + 2 * OF.n_out] = 0
57-
end
58-
39+
function OctagonFilter(mo, mi, no, ni)
40+
OF = OctagonFilter(mo, mi, no, ni, 0.0, 0.0, 0.0, 0.0)
41+
OF.out_area = OF.m_out ^ 2 + 2 * OF.n_out ^ 2 + 4 * OF.m_out * OF.n_out
42+
OF.in_area = OF.m_in ^ 2 + 2 * OF.n_in ^ 2 + 4 * OF.m_in * OF.n_in
43+
OF.out_weight = 1.0 / (OF.out_area - OF.in_area)
44+
OF.in_weight = 1.0 / OF.in_area
45+
OF
5946
end
6047

61-
OctagonFilter(mo, mi, no, ni) = (OF = OctagonFilter(ones(Float64, mo + 2 * no, mo + 2 * no), mo, mi, no, ni); createFilter(OF); OF)
62-
BoxFilter(s) = (BF = BoxFilter(s, 2 * s + 1, 4 * s + 1, (2 * s + 1) ^ 2, (4 * s + 1) ^ 2, 0.0, 0.0); BF.in_weight = 1.0 / BF.in_area; BF.out_weight = 1.0 / (BF.out_area - BF.in_area); BF; )
48+
function BoxFilter(s)
49+
BF = BoxFilter(s, 2 * s + 1, 4 * s + 1, (2 * s + 1) ^ 2, (4 * s + 1) ^ 2, 0.0, 0.0)
50+
BF.in_weight = 1.0 / BF.in_area
51+
BF.out_weight = 1.0 / (BF.out_area - BF.in_area)
52+
BF
53+
end
6354

6455
OctagonFilter_Kernels = [
6556
[5, 3, 2, 0],
@@ -80,18 +71,45 @@ function getFilterStack(filter_type::Type, smallest::Integer, largest::Integer)
8071
filter_stack = map(f -> filter_type(f...), k[smallest : largest])
8172
end
8273

83-
function filterResponse{T}(int_img::AbstractArray{T, 2}, filter::BoxFilter)
84-
margin = filter.scale * 2
85-
n = filter.scale
74+
getIntegralImage(img, filter_type::BoxFilter) = integral_image(img)
75+
76+
function getIntegralImage(img, filter_type::OctagonFilter)
77+
img_shape = size(img)
78+
int_img = zeros(img_shape)
79+
right_slant_img = zeros(img_shape)
80+
left_slant_img = zeros(img_shape)
81+
82+
int_img[1, :] = cumsum(img[1, :])
83+
right_slant_img[1, :] = int_img[1, :]
84+
left_slant_img[1, :] = int_img[1, :]
85+
86+
for i in 2:img_shape[1]
87+
sum = 0.0
88+
for j in 1:img_shape[2]
89+
sum += img[i, j]
90+
int_img[i, j] = sum + int_img[i - 1, j]
91+
left_slant_img[i, j] = sum
92+
right_slant_img[i, j] = sum
93+
94+
if j > 1 left_slant_img[i, j] += left_slant_img[i - 1, j - 1] end
95+
right_slant_img[i, j] += j < img_shape[2] ? right_slant_img[i - 1, j + 1] : right_slant_img[i - 1, j]
96+
end
97+
end
98+
int_img, right_slant_img, left_slant_img
99+
end
100+
101+
function filterResponse{T}(int_img::AbstractArray{T, 2}, BF::BoxFilter)
102+
margin = BF.scale * 2
103+
n = BF.scale
86104
img_shape = size(int_img)
87105
response = zeros(img_shape)
88106
R = CartesianRange(CartesianIndex((margin + 1, margin + 1)), CartesianIndex((img_shape[1] - margin, img_shape[2] - margin)))
89107
in_sum = 0.0
90108
out_sum = 0.0
91109
for I in R
92110
topleft = I + CartesianIndex(- n - 1, - n - 1)
93-
topright = I + CartesianIndex(n, - n - 1)
94-
bottomleft = I + CartesianIndex(- n - 1, n)
111+
topright = I + CartesianIndex(- n - 1, n)
112+
bottomleft = I + CartesianIndex(n, - n - 1)
95113
bottomright = I + CartesianIndex(n, n)
96114
A = topleft >= CartesianIndex(1, 1) ? int_img[topleft] : 0.0
97115
B = topright >= CartesianIndex(1, 1) ? int_img[topright] : 0.0
@@ -100,52 +118,100 @@ function filterResponse{T}(int_img::AbstractArray{T, 2}, filter::BoxFilter)
100118
in_sum = A + D - B - C
101119

102120
topleft = I + CartesianIndex(- 2 * n - 1, - 2 * n - 1)
103-
topright = I + CartesianIndex(2 * n, - 2 * n - 1)
104-
bottomleft = I + CartesianIndex(- 2 * n - 1, 2 * n)
121+
topright = I + CartesianIndex(- 2 * n - 1, 2 * n)
122+
bottomleft = I + CartesianIndex(2 * n, - 2 * n - 1)
105123
bottomright = I + CartesianIndex(2 * n, 2 * n)
106124
A = topleft >= CartesianIndex(1, 1) ? int_img[topleft] : 0.0
107125
B = topright >= CartesianIndex(1, 1) ? int_img[topright] : 0.0
108126
C = bottomleft >= CartesianIndex(1, 1) ? int_img[bottomleft] : 0.0
109127
D = bottomright >= CartesianIndex(1, 1) ? int_img[bottomright] : 0.0
110128
out_sum = A + D - B - C - in_sum
111129

112-
response[I] = in_sum * filter.in_weight - out_sum * filer.out_weight
130+
response[I] = in_sum * BF.in_weight - out_sum * BF.out_weight
113131
end
114132

115133
response
116134
end
117135

118-
function filterResponse(int_imgs::Tuple, filter::OctagonFilter)
136+
function filterResponse(int_imgs::Tuple, OF::OctagonFilter)
119137
int_img = int_imgs[1]
120138
rs_img = int_imgs[2]
121139
ls_img = int_imgs[3]
122-
end
123140

124-
getIntegralImage(img, filter_type::BoxFilter) = integral_image(img)
125-
126-
function getIntegralImage(img, filter_type::OctagonFilter)
127-
img_shape = size(img)
128-
int_img = zeros(img_shape)
129-
right_slant_img = zeros(img_shape)
130-
left_slant_img = zeros(img_shape)
141+
margin = Int(floor(OF.m_out / 2 + OF.n_out))
142+
m_in2 = Int(floor(OF.m_in / 2))
143+
m_out2 = Int(floor(OF.m_out / 2))
131144

132-
int_img[1, :] = cumsum(img[1, :])
133-
right_slant_img[1, :] = int_img[1, :]
134-
left_slant_img[1, :] = int_img[1, :]
145+
img_shape = size(int_img)
146+
response = zeros(img_shape)
147+
R = CartesianRange(CartesianIndex((margin + 1, margin + 1)), CartesianIndex((img_shape[1] - margin, img_shape[2] - margin)))
148+
149+
for I in R
150+
topleft = I + CartesianIndex(- m_in2 - 1, - m_in2 - OF.n_in - 1)
151+
topright = I + CartesianIndex(m_in2, - m_in2 - OF.n_in - 1)
152+
bottomleft = I + CartesianIndex(- m_in2 - 1, m_in2 + OF.n_in)
153+
bottomright = I + CartesianIndex(m_in2, m_in2 + OF.n_in)
154+
A = topleft >= CartesianIndex(1, 1) ? int_img[topleft] : 0.0
155+
B = topright >= CartesianIndex(1, 1) ? int_img[topright] : 0.0
156+
C = bottomleft >= CartesianIndex(1, 1) ? int_img[bottomleft] : 0.0
157+
D = bottomright >= CartesianIndex(1, 1) ? int_img[bottomright] : 0.0
158+
in_sum = A + D - B - C
135159

136-
for i in 2:img_shape[1]
137-
sum = 0.0
138-
for j in 1:img_shape[2]
139-
sum += img[i, j]
140-
int_img[i, j] = sum + int_img[i - 1, j]
141-
left_slant_img[i, j] = sum
142-
right_slant_img[i, j] = sum
160+
trap_top_right = bottomright
161+
trap_bot_right = I + CartesianIndex(m_in2 + OF.n_in, m_in2)
162+
trap_top_left = I + CartesianIndex(m_in2, - m_in2 - OF.n_in)
163+
trap_bot_left = I + CartesianIndex(m_in2 + OF.n_in, - m_in2 - 1)
164+
A = trap_top_left >= CartesianIndex(1, 1) ? ls_img[trap_top_left] : 0.0
165+
B = trap_top_right >= CartesianIndex(1, 1) ? rs_img[trap_top_right] : 0.0
166+
C = trap_bot_left >= CartesianIndex(1, 1) ? ls_img[trap_bot_left] : 0.0
167+
D = trap_bot_right >= CartesianIndex(1, 1) ? rs_img[trap_bot_right] : 0.0
168+
in_sum += A + D - B - C
169+
170+
trap_top_right = I + CartesianIndex(- m_in2 - OF.n_in - 1, m_in2 - 1)
171+
trap_top_left = I + CartesianIndex(- m_in2 - OF.n_in - 1, - m_in2)
172+
trap_bot_right = I + CartesianIndex(- m_in2 - 1, m_in2 + OF.n_in - 1)
173+
trap_bot_left = I + CartesianIndex(- m_in2 - 1, - m_in2 - OF.n_in)
174+
A = trap_top_left >= CartesianIndex(1, 1) ? rs_img[trap_top_left] : 0.0
175+
B = trap_top_right >= CartesianIndex(1, 1) ? ls_img[trap_top_right] : 0.0
176+
C = trap_bot_left >= CartesianIndex(1, 1) ? rs_img[trap_bot_left] : 0.0
177+
D = trap_bot_right >= CartesianIndex(1, 1) ? ls_img[trap_bot_right] : 0.0
178+
in_sum += A + D - B - C
179+
180+
topleft = I + CartesianIndex(- m_out2 - 1, - m_out2 - OF.n_out - 1)
181+
topright = I + CartesianIndex(m_out2, - m_out2 - OF.n_out - 1)
182+
bottomleft = I + CartesianIndex(- m_out2 - 1, m_out2 + OF.n_out)
183+
bottomright = I + CartesianIndex(m_out2, m_out2 + OF.n_out)
184+
A = topleft >= CartesianIndex(1, 1) ? int_img[topleft] : 0.0
185+
B = topright >= CartesianIndex(1, 1) ? int_img[topright] : 0.0
186+
C = bottomleft >= CartesianIndex(1, 1) ? int_img[bottomleft] : 0.0
187+
D = bottomright >= CartesianIndex(1, 1) ? int_img[bottomright] : 0.0
188+
out_sum = A + D - B - C
189+
190+
trap_top_right = bottomright
191+
trap_bot_right = I + CartesianIndex(m_out2 + OF.n_out, m_out2)
192+
trap_top_left = I + CartesianIndex(m_out2, - m_out2 - OF.n_out)
193+
trap_bot_left = I + CartesianIndex(m_out2 + OF.n_out, - m_out2 - 1)
194+
A = trap_top_left >= CartesianIndex(1, 1) ? ls_img[trap_top_left] : 0.0
195+
B = trap_top_right >= CartesianIndex(1, 1) ? rs_img[trap_top_right] : 0.0
196+
C = trap_bot_left >= CartesianIndex(1, 1) ? ls_img[trap_bot_left] : 0.0
197+
D = trap_bot_right >= CartesianIndex(1, 1) ? rs_img[trap_bot_right] : 0.0
198+
out_sum += A + D - B - C
199+
200+
trap_top_right = I + CartesianIndex(- m_out2 - OF.n_out - 1, m_out2 - 1)
201+
trap_top_left = I + CartesianIndex(- m_out2 - OF.n_out - 1, - m_out2)
202+
trap_bot_right = I + CartesianIndex(- m_out2 - 1, m_out2 + OF.n_out - 1)
203+
trap_bot_left = I + CartesianIndex(- m_out2 - 1, - m_out2 - OF.n_out)
204+
A = trap_top_left >= CartesianIndex(1, 1) ? rs_img[trap_top_left] : 0.0
205+
B = trap_top_right >= CartesianIndex(1, 1) ? ls_img[trap_top_right] : 0.0
206+
C = trap_bot_left >= CartesianIndex(1, 1) ? rs_img[trap_bot_left] : 0.0
207+
D = trap_bot_right >= CartesianIndex(1, 1) ? ls_img[trap_bot_right] : 0.0
208+
out_sum += A + D - B - C
209+
out_sum = out_sum - in_sum
143210

144-
if j > 1 left_slant_img[i, j] += left_slant_img[i - 1, j - 1] end
145-
right_slant_img[i, j] += j < img_shape[2] ? right_slant_img[i - 1, j + 1] : right_slant_img[i - 1, j]
146-
end
147-
end
148-
int_img, right_slant_img, left_slant_img
211+
response[I] = in_sum * filter.in_weight - out_sum * filer.out_weight
212+
end
213+
response
214+
149215
end
150216

151217
CENSURE(; smallest::Integer = 1, largest::Integer = 7, filter::Type = BoxFilter, responseThreshold::Number = 0.15, lineThreshold::Number = 10) = CENSURE(smallest, largest, filter, getFilterStack(filter, smallest, largest), responseThreshold, lineThreshold)

‎test/runtests.jl‎

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -55,6 +55,7 @@ include("corner.jl")
5555
include("orb.jl")
5656
include("freak.jl")
5757
include("brisk.jl")
58+
include("censure.jl")
5859

5960
isinteractive() || FactCheck.exitstatus()
6061

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