1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
|
// Copyright (C) 2006 Davis E. King (davis@dlib.net)
// License: Boost Software License See LICENSE.txt for the full license.
#ifndef DLIB_THRESHOLDINg_
#define DLIB_THRESHOLDINg_
#include "../pixel.h"
#include "thresholding_abstract.h"
#include "equalize_histogram.h"
namespace dlib
{
// ----------------------------------------------------------------------------------------
const unsigned char on_pixel = 255;
const unsigned char off_pixel = 0;
// ----------------------------------------------------------------------------------------
template <
typename in_image_type,
typename out_image_type
>
void threshold_image (
const in_image_type& in_img_,
out_image_type& out_img_,
typename pixel_traits<typename image_traits<in_image_type>::pixel_type>::basic_pixel_type thresh
)
{
COMPILE_TIME_ASSERT( pixel_traits<typename image_traits<in_image_type>::pixel_type>::has_alpha == false );
COMPILE_TIME_ASSERT( pixel_traits<typename image_traits<out_image_type>::pixel_type>::has_alpha == false );
COMPILE_TIME_ASSERT(pixel_traits<typename image_traits<out_image_type>::pixel_type>::grayscale);
const_image_view<in_image_type> in_img(in_img_);
image_view<out_image_type> out_img(out_img_);
// if there isn't any input image then don't do anything
if (in_img.size() == 0)
{
out_img.clear();
return;
}
out_img.set_size(in_img.nr(),in_img.nc());
for (long r = 0; r < in_img.nr(); ++r)
{
for (long c = 0; c < in_img.nc(); ++c)
{
if (get_pixel_intensity(in_img[r][c]) >= thresh)
assign_pixel(out_img[r][c], on_pixel);
else
assign_pixel(out_img[r][c], off_pixel);
}
}
}
// ----------------------------------------------------------------------------------------
template <
typename image_type
>
void threshold_image (
image_type& img,
typename pixel_traits<typename image_traits<image_type>::pixel_type>::basic_pixel_type thresh
)
{
threshold_image(img,img,thresh);
}
// ----------------------------------------------------------------------------------------
template <
typename in_image_type,
typename out_image_type
>
void auto_threshold_image (
const in_image_type& in_img_,
out_image_type& out_img_
)
{
COMPILE_TIME_ASSERT( pixel_traits<typename image_traits<in_image_type>::pixel_type>::has_alpha == false );
COMPILE_TIME_ASSERT( pixel_traits<typename image_traits<out_image_type>::pixel_type>::has_alpha == false );
COMPILE_TIME_ASSERT( pixel_traits<typename image_traits<in_image_type>::pixel_type>::is_unsigned == true );
COMPILE_TIME_ASSERT( pixel_traits<typename image_traits<out_image_type>::pixel_type>::is_unsigned == true );
COMPILE_TIME_ASSERT(pixel_traits<typename image_traits<out_image_type>::pixel_type>::grayscale);
image_view<out_image_type> out_img(out_img_);
// if there isn't any input image then don't do anything
if (image_size(in_img_) == 0)
{
out_img.clear();
return;
}
unsigned long thresh;
// find the threshold we should use
matrix<unsigned long,1> hist;
get_histogram(in_img_,hist);
const_image_view<in_image_type> in_img(in_img_);
// Start our two means (a and b) out at the ends of the histogram
long a = 0;
long b = hist.size()-1;
bool moved_a = true;
bool moved_b = true;
while (moved_a || moved_b)
{
moved_a = false;
moved_b = false;
// catch the degenerate case where the histogram is empty
if (a >= b)
break;
if (hist(a) == 0)
{
++a;
moved_a = true;
}
if (hist(b) == 0)
{
--b;
moved_b = true;
}
}
// now do k-means clustering with k = 2 on the histogram.
moved_a = true;
moved_b = true;
while (moved_a || moved_b)
{
moved_a = false;
moved_b = false;
int64 a_hits = 0;
int64 b_hits = 0;
int64 a_mass = 0;
int64 b_mass = 0;
for (long i = 0; i < hist.size(); ++i)
{
// if i is closer to a
if (std::abs(i-a) < std::abs(i-b))
{
a_mass += hist(i)*i;
a_hits += hist(i);
}
else // if i is closer to b
{
b_mass += hist(i)*i;
b_hits += hist(i);
}
}
long new_a = (a_mass + a_hits/2)/a_hits;
long new_b = (b_mass + b_hits/2)/b_hits;
if (new_a != a)
{
moved_a = true;
a = new_a;
}
if (new_b != b)
{
moved_b = true;
b = new_b;
}
}
// put the threshold between the two means we found
thresh = (a + b)/2;
// now actually apply the threshold
threshold_image(in_img_,out_img_,thresh);
}
template <
typename image_type
>
void auto_threshold_image (
image_type& img
)
{
auto_threshold_image(img,img);
}
// ----------------------------------------------------------------------------------------
template <
typename in_image_type,
typename out_image_type
>
void hysteresis_threshold (
const in_image_type& in_img_,
out_image_type& out_img_,
typename pixel_traits<typename image_traits<in_image_type>::pixel_type>::basic_pixel_type lower_thresh,
typename pixel_traits<typename image_traits<in_image_type>::pixel_type>::basic_pixel_type upper_thresh
)
{
COMPILE_TIME_ASSERT( pixel_traits<typename image_traits<in_image_type>::pixel_type>::has_alpha == false );
COMPILE_TIME_ASSERT( pixel_traits<typename image_traits<out_image_type>::pixel_type>::has_alpha == false );
COMPILE_TIME_ASSERT(pixel_traits<typename image_traits<out_image_type>::pixel_type>::grayscale);
DLIB_ASSERT( lower_thresh <= upper_thresh && is_same_object(in_img_, out_img_) == false,
"\tvoid hysteresis_threshold(in_img_, out_img_, lower_thresh, upper_thresh)"
<< "\n\tYou can't use an upper_thresh that is less than your lower_thresh"
<< "\n\tlower_thresh: " << lower_thresh
<< "\n\tupper_thresh: " << upper_thresh
<< "\n\tis_same_object(in_img_,out_img_): " << is_same_object(in_img_,out_img_)
);
const_image_view<in_image_type> in_img(in_img_);
image_view<out_image_type> out_img(out_img_);
// if there isn't any input image then don't do anything
if (in_img.size() == 0)
{
out_img.clear();
return;
}
out_img.set_size(in_img.nr(),in_img.nc());
assign_all_pixels(out_img, off_pixel);
const long size = 1000;
long rstack[size];
long cstack[size];
// now do the thresholding
for (long r = 0; r < in_img.nr(); ++r)
{
for (long c = 0; c < in_img.nc(); ++c)
{
typename pixel_traits<typename image_traits<in_image_type>::pixel_type>::basic_pixel_type p;
assign_pixel(p,in_img[r][c]);
if (p >= upper_thresh)
{
// now do line following for pixels >= lower_thresh.
// set the stack position to 0.
long pos = 1;
rstack[0] = r;
cstack[0] = c;
while (pos > 0)
{
--pos;
const long r = rstack[pos];
const long c = cstack[pos];
// This is the base case of our recursion. We want to stop if we hit a
// pixel we have already visited.
if (out_img[r][c] == on_pixel)
continue;
out_img[r][c] = on_pixel;
// put the neighbors of this pixel on the stack if they are bright enough
if (r-1 >= 0)
{
if (pos < size && get_pixel_intensity(in_img[r-1][c]) >= lower_thresh)
{
rstack[pos] = r-1;
cstack[pos] = c;
++pos;
}
if (pos < size && c-1 >= 0 && get_pixel_intensity(in_img[r-1][c-1]) >= lower_thresh)
{
rstack[pos] = r-1;
cstack[pos] = c-1;
++pos;
}
if (pos < size && c+1 < in_img.nc() && get_pixel_intensity(in_img[r-1][c+1]) >= lower_thresh)
{
rstack[pos] = r-1;
cstack[pos] = c+1;
++pos;
}
}
if (pos < size && c-1 >= 0 && get_pixel_intensity(in_img[r][c-1]) >= lower_thresh)
{
rstack[pos] = r;
cstack[pos] = c-1;
++pos;
}
if (pos < size && c+1 < in_img.nc() && get_pixel_intensity(in_img[r][c+1]) >= lower_thresh)
{
rstack[pos] = r;
cstack[pos] = c+1;
++pos;
}
if (r+1 < in_img.nr())
{
if (pos < size && get_pixel_intensity(in_img[r+1][c]) >= lower_thresh)
{
rstack[pos] = r+1;
cstack[pos] = c;
++pos;
}
if (pos < size && c-1 >= 0 && get_pixel_intensity(in_img[r+1][c-1]) >= lower_thresh)
{
rstack[pos] = r+1;
cstack[pos] = c-1;
++pos;
}
if (pos < size && c+1 < in_img.nc() && get_pixel_intensity(in_img[r+1][c+1]) >= lower_thresh)
{
rstack[pos] = r+1;
cstack[pos] = c+1;
++pos;
}
}
} // end while (pos >= 0)
}
else
{
out_img[r][c] = off_pixel;
}
}
}
}
// ----------------------------------------------------------------------------------------
}
#endif // DLIB_THRESHOLDINg_
|
