Extracting RGB values along the Feret diameter of different particles

Hi everyone,

I’m new to ImageJ and the image analysis I’ve been trying to do for some time has been unsuccessful. I hope somebody will be able to help me out.

My goal is to write a macro that allows to extract all RGB values along the Feret diameter of fluorescent particles on a black background (as in the attached picture).

So far I’ve changed the RGB-image to 8-bit and created a black-white binary overlay. I figured out how to calculate the different Feret diameters through ‘Analyze particles’, but I haven’t been able to proceed much further than this as I am still quite unfamiliar with the program.

I assume the steps I need to perform are something like this:

  • Extract pixel coordinates from the drawn Feret diameters (can I use the getSelectionCoordinates() for this in any way?, e.g. after creating line selections on top of the Feret diameters?)
  • Create line selections (ROI) on the original RGB pictures using the extracted coordinates (Perhaps like was done here: Create a ROI Set using XY coordinates);
  • Use ‘Edit’>’Selection’>’Line to Area’ to be able to extract the selected RGB values via ‘Analyze’>’Tools’>’Save XY coordinates’ (line selection doesn’t seem to allow to extract RGB-values).

I’ve read how to extract grayscale intensities along the Feret diameter of particles on this topic: Drawing Feret and FeretMin as selection , but I haven’t been able to adapt this code so that RGB-values are extracted from RGB-pictures.

Any help, advice or suggestions on how to proceed is highly appreciated! Thanks a lot

a.tif (14.1 MB)

Hello Marine -

After creating your Feret-diameter Line ROI, convert your RGB
image to an “RGB Stack” in order to extract the separate R, G,
and B values.

The lightly-documented Roi.getFeretPoints() IJ Macro
function might be the easiest way to do this.

See this example IJ Macro (that uses the “Clown” sample image):

print (IJ.getFullVersion);
run ("Clown");                          // get sample image
makeEllipse (25, 105, 125, 150, 0.6);   // nose ROI, for example
print ("RGB Feret values");
Roi.getFeretPoints (x, y);              // get nose Feret
makeLine (x[0], y[0], x[1], y[1]);      // max Feret diameter
run ("RGB Stack")                       // convert to stack
colors = newArray ("Red", "Green", "Blue");
for (i = 1; i <= nSlices; i++) {        // get values for each RGB slice
	print (colors[i - 1] + " (" + i + ") Feret values:");
	setSlice (i);
	fvals = getProfile();
	print (fvals.length);
	for (j = 0; j < fvals.length; j++) {
    	print (j, fvals[j]);
	}
}

Here is its output from the Log window:

1.53g05
RGB Feret values
Red (1) Feret values:
111
0 51
1 91.2686
2 131.6116
3 156.5579
4 168.0579
5 171.5248
6 171.2562
7 167.1116
8 164.4298
9 174.8884
10 177.843
11 178.5
12 177.3388
13 167.624
14 177.7686
15 213.9793
16 230.7025
17 224.3223
18 225.0496
19 229.2603
20 233.876
21 236.5
22 236
23 231.1364
24 228.7273
25 225.8058
26 218.4959
27 210.4793
28 205.7273
29 203.781
30 198.6116
31 184.9091
32 166.0331
33 152
34 159.0413
35 155.0207
36 150.5124
37 146.7314
38 143.8678
39 142.5909
40 141.2727
41 140.1818
42 137.9091
43 133.2107
44 130
45 126.1736
46 122.2727
47 118.4091
48 114.0826
49 109.6612
50 105.9339
51 103.2314
52 99.0909
53 94.9091
54 91.0083
55 85
56 80.7273
57 75.8967
58 72.438
59 68.0455
60 61
61 54.7934
62 51.0496
63 47.7397
64 44.9091
65 41.5455
66 39
67 34.5992
68 32.4298
69 29.6364
70 26.8182
71 24.9339
72 23.8843
73 22.2727
74 21.6529
75 20.9545
76 20
77 20
78 20
79 20
80 20.1983
81 20
82 20.5455
83 21
84 20.7686
85 21
86 21.5455
87 24.0909
88 25
89 25.8347
90 26.8182
91 26.876
92 26.3636
93 25.2521
94 22.5207
95 18.1777
96 14.7273
97 14.0579
98 14
99 14
100 14
101 14
102 14
103 14
104 14.5455
105 15
106 15
107 15
108 15
109 15
110 15
Green (2) Feret values:
111
0 3
1 16.4793
2 29.438
3 30.4917
4 26.6777
5 24.0083
6 24.1653
7 21.7645
8 19.7355
9 27.5579
10 26.8347
11 27.5
12 29.6529
13 29.2231
14 52.7851
15 104.343
16 137.405
17 145.5289
18 155.8595
19 166.8347
20 174.3306
21 175.6736
22 173
23 164.6446
24 155.1736
25 142.5041
26 125.314
27 108.3678
28 95.8182
29 86.3182
30 74.9587
31 55.7149
32 32.0083
33 16.5
34 22.0661
35 20.9091
36 18.2975
37 18.1364
38 18.2975
39 19.3843
40 21.0909
41 23.0909
42 24.6033
43 21.8719
44 21
45 20.6281
46 18.5455
47 17.6694
48 16.0909
49 15
50 15.2479
51 14.7727
52 14
53 13.9421
54 14.0909
55 14.5
56 13.0909
57 13.3182
58 13
59 12.814
60 10.5702
61 9.4545
62 9.405
63 8.5785
64 7
65 6.8719
66 6
67 4.6818
68 4.1818
69 4.1653
70 5.2727
71 5.4587
72 5.9091
73 6.5496
74 6.1983
75 6.3182
76 6
77 6
78 6.8264
79 7
80 6.8017
81 7
82 6.4545
83 6
84 6.2314
85 6
86 6
87 6.0909
88 7
89 7.9463
90 8.8182
91 9.062
92 8.3636
93 7.3884
94 6.0909
95 4.7727
96 3.8017
97 3.9421
98 4
99 4
100 4
101 4
102 4
103 4
104 4.5455
105 5
106 5
107 5
108 5
109 5
110 5
Blue (3) Feret values:
111
0 0
1 12.0702
2 24.2893
3 24.4752
4 18.1322
5 12.8017
6 10.8017
7 8.5289
8 8.2645
9 16.0579
10 15.3967
11 13.5
12 13.9174
13 9.0744
14 28.876
15 76.0248
16 104.9752
17 109.7521
18 117
19 125.9132
20 132.5124
21 134.2645
22 132
23 125
24 118.1488
25 108.7645
26 94.4959
27 81.686
28 73.0909
29 66.3223
30 57.3223
31 41.0455
32 21.0165
33 6
34 12.0579
35 10.6694
36 9.6777
37 9.3636
38 8.7521
39 8.9752
40 10.9174
41 13.0455
42 13.6694
43 12.2727
44 14
45 13.1281
46 11.3636
47 9.6529
48 7.2231
49 6.5661
50 7
51 6.3719
52 5
53 4.6157
54 4.1818
55 5.5
56 4.0909
57 3.1818
58 2.4711
59 2.4628
60 1.6612
61 1.9132
62 1.9091
63 0.3926
64 0.2975
65 0.5
66 1
67 1.1281
68 0.8843
69 2.2273
70 2.3636
71 3.0702
72 4
73 4.7273
74 5.9256
75 5.6364
76 4.8182
77 3
78 1.3471
79 1
80 1
81 1
82 1
83 1
84 1
85 1
86 1.1818
87 2.0909
88 3
89 3.9091
90 4.8182
91 5
92 4.3636
93 3.4339
94 3.0413
95 2.2727
96 2.4711
97 3
98 3
99 3
100 3
101 3
102 3
103 3
104 3.5455
105 4
106 4
107 4
108 4
109 4
110 4

Thanks, mm

1 Like

Hi mountain_man,

Thanks a lot for your help! This has helped me considerably. The Roi.getFeretPoints() indeed works fine here. I did encounter some problems though, with creating the Feret-diameter Line ROI in particular.
I’ve tried making a ROI of the particle by specifying a color threshold for a specific particle (Image>Adjust>Color threshold, with ‘Default’ as tresholding method and ‘RGB’ as colour space) (image type = RGB color). Next, I made a selection of the particle based on the chosen threshold, and than ran your macro using this selection. This seems to work fine and I obtained the RGB values that I wanted, great!

However, when I record these steps to obtain the particle selection, add your macro which extracts the RGB values along the Feret diameter of the created ROI, and run the whole macro on the same picture, I get the following error:

No selection in line 45
ROi . <getFeretPoints> (x, y) ;

It seems the selection I created is not recognized by the Roi.getFeretPoints (x, y) macro function. Probably I made some kind of rookie error as I am not familiar with this coding language, apologies if this is the case. Would be great if you can help me solve this, or tell me what exactly I am doing wrong. My goals is to write a macro that allows the completely automated RGB-color analysis along the Feret diameter of a particle.
This is the macro I created by recording the steps I performed + adding your part:

run("Color Threshold...");
// Color Thresholder 2.0.0-rc-69/1.52p
// Autogenerated macro, single images only!
min=newArray(3);
max=newArray(3);
filter=newArray(3);
a=getTitle();
run("RGB Stack");
run("Convert Stack to Images");
selectWindow("Red");
rename("0");
selectWindow("Green");
rename("1");
selectWindow("Blue");
rename("2");
min[0]=43;
max[0]=255;
filter[0]="pass";
min[1]=0;
max[1]=255;
filter[1]="pass";
min[2]=0;
max[2]=255;
filter[2]="pass";
for (i=0;i<3;i++){
  selectWindow(""+i);
  setThreshold(min[i], max[i]);
  run("Convert to Mask");
  if (filter[i]=="stop")  run("Invert");
}
imageCalculator("AND create", "0","1");
imageCalculator("AND create", "Result of 0","2");
for (i=0;i<3;i++){
  selectWindow(""+i);
  close();
}
selectWindow("Result of 0");
close();
selectWindow("Result of Result of 0");
rename(a);
// Colour Thresholding-------------

print ("RGB Feret values");
Roi.getFeretPoints (x, y);              // get nose Feret
makeLine (x[0], y[0], x[1], y[1]);      // max Feret diameter
run ("RGB Stack")                       // convert to stack
colors = newArray ("Red", "Green", "Blue");
for (i = 1; i <= nSlices; i++) {        // get values for each RGB slice
	print (colors[i - 1] + " (" + i + ") Feret values:");
	setSlice (i);
	fvals = getProfile();
	print (fvals.length);
	for (j = 0; j < fvals.length; j++) {
    	print (j, fvals[j]);
	}
}

Another way to obtain the particle ROI needed to create the Feret-diameter line ROI could perhaps be using the getSelectionCoordinates(xpoints, ypoints) and the makeSelection(“polygon”, xpoints, ypoints) macro functions to recreate the particle ROI on a RGB color-image based on the ROI obtained after creating a binary overlay on the image in greyscale. I’ve tried this but it haven’t been able to recreate the ROI on a different image so far. Perhaps there is a more straightforward way to do this that I don’t know of? I appreciate any help or suggestions, thanks again for helping me out.

Hello Marine -

There are multiple ways to do this, but following along with what
you’ve described, here is one approach.

First you need the (ROIs of the) objects whose Feret profiles
you want to extract. We’ll use Analyze Particles... as
you mentioned in your first post. We’ll do this with a grayscale
duplicate of the color image being analyzed.

Analyze Particles... will add the ROIs of the objects to
the ROI Manager. In the example below, we will only have one
object, so you will have to adjust the example Macro to work
with multiple objects, if that is your use case.

We select the object ROI in the ROI Manager to make it active
in the image so that Roi.getFeretPoints() will have an ROI
to work on.

We then create the max-Feret-diameter Line ROI and add it to
the ROI Manager. (In our particular case, we choose to overwrite
the object ROI in the ROI Manager.)

We then close the duplicate image and use the ROI Manager to
transfer the Feret ROI to the original color image. We do this by
selecting the Feret ROI in the ROI Manager. This makes the Feret
ROI active in original RGB image (because it is now the only open
image).

The Macro then proceeds as in the Macro I posted before: We split
the color image into an RGB Stack, and extract the Feret profiles
for each of the R, G, and B stack slices separately,

Here is the updated IJ Macro:

print (IJ.getFullVersion);
run ("Cardio (RGB DICOM)");             // get sample RGB image
run ("Duplicate...", "title=dup");      // duplicate for grayscale processing
run ("8-bit");
setThreshold (20, 255);
run ("Analyze Particles...", "size=200000-300000 add");
roiManager ("select", 0);               // select "particle" ROI
Roi.getFeretPoints (x, y);              // get "particle" Feret
makeLine (x[0], y[0], x[1], y[1]);      // max Feret diameter
roiManager ("update");                  // replace "particle" ROI with Feret Line
close();                                // close dup image
roiManager ("select", 0);               // select Feret Line on RGB image
run ("RGB Stack")                       // convert to stack
colors = newArray ("Red", "Green", "Blue");
for (i = 1; i <= nSlices; i++) {        // get values for each RGB slice
	print (colors[i - 1] + " (" + i + ") Feret values:");
	setSlice (i);
	fvals = getProfile();
	print (fvals.length);
	for (j = 0; j < fvals.length; j++) {
    	print (j, fvals[j]);
	}
}

And here is its output:

1.53g05
Red (1) Feret values:
627
0 29
1 31.7012
2 32.0669
3 32.9014
4 35.8772
5 36.3846
6 35.2716
7 33.346
8 30.66
9 28.9537
10 28.28
11 31.3624
12 44.678
13 55.9789
14 71.157
15 93.1324
16 115.2326
17 128.8027
18 123.1345
19 111.5163
20 101.8479
21 94.9317
22 105.4909
23 130.1692
24 150.8412
25 147.789
26 131.7993
27 109.4572
28 93.4988
29 87.5559
30 90.4308
31 102.9361
32 115.0714
33 117.5851
34 113.2277
35 121.6326
36 126.0792
37 116.0277
38 99.8526
39 84.8284
40 78.1119
41 77.8015
42 66.3881
43 58.078
44 51.8617
45 41.0883
46 32.8599
47 31.8103
48 36.2326
49 54.5754
50 84.0062
51 118.776
52 142.103
53 139.617
54 114.9997
55 75.5317
56 63.7598
57 64.0483
58 71.4056
59 97.1232
60 105.0883
61 100.5151
62 88.2819
63 78.1171
64 76.7783
65 77.7267
66 90.6676
67 105.7375
68 113.1969
69 118.8614
70 116.9528
71 111.57
72 107.5106
73 106.1869
74 107.476
75 111.8357
76 118.2793
77 125.1841
78 128.6779
79 127.2787
80 122.3085
81 111.9212
82 95.0963
83 75.8685
84 55.7555
85 42.432
86 36.089
87 32.2181
88 35.5998
89 47.3206
90 64.4923
91 79.3315
92 97.3061
93 101.061
94 88.7605
95 79.6457
96 71.5139
97 61.8107
98 52.2578
99 44.1131
100 37.5428
101 53.7495
102 72.4488
103 90.4805
104 90.4947
105 81.4393
106 79.6019
107 87.291
108 99.9143
109 112.6871
110 121.5888
111 120.0574
112 116.5144
113 110.69
114 109.3346
115 103.7279
116 96.4877
117 92.5443
118 95.294
119 104.0942
120 110.717
121 107.8054
122 94.7224
123 76.2373
124 59.5373
125 45.5844
126 37.2277
127 31.2504
128 28.769
129 30.0833
130 32.6429
131 34.0256
132 35.3464
133 38.1283
134 42.9909
135 45.1346
136 53.7992
137 76.522
138 101.2353
139 108.943
140 102.4658
141 89.0647
142 77.8505
143 69.8996
144 66.0895
145 52.8626
146 45.097
147 45.6859
148 55.1207
149 60.0153
150 69.6127
151 90.5099
152 118.7718
153 125.1886
154 114.3874
155 74.6941
156 78.3444
157 86.1464
158 89.585
159 96.6198
160 111.0076
161 124.7293
162 128.9597
163 127.4466
164 127.5329
165 129.1074
166 124.0394
167 119.3927
168 116.5596
169 120.9377
170 128.3856
171 133.1227
172 130.7248
173 124.0892
174 119.8558
175 118.8268
176 118.8633
177 119.8403
178 118.5118
179 113.2009
180 107.8247
181 106.9026
182 111.026
183 117.0862
184 121.9479
185 128.1171
186 135.0439
187 139.0329
188 141.9104
189 147.437
190 147.561
191 142.781
192 135.7427
193 132.1925
194 134.0605
195 132.509
196 127.6811
197 126.5632
198 121.067
199 114.98
200 113.8708
201 113.1321
202 111.6688
203 118.9617
204 127.9791
205 131.8858
206 126.7431
207 115.5244
208 104.2167
209 97.7085
210 98.2479
211 97.1648
212 100.2991
213 109.0366
214 115.6552
215 114.3623
216 105.1685
217 100.9628
218 104.7107
219 109.7923
220 108.6625
221 102.7005
222 93.0199
223 85.2574
224 79.0321
225 77.4297
226 80.9448
227 78.8686
228 73.0874
229 72.0303
230 76.0301
231 78.6289
232 81.9403
233 85.5374
234 95.4968
235 105.1322
236 110.7704
237 115.1529
238 119.396
239 127.6772
240 135.5171
241 131.2709
242 131.407
243 127.2777
244 121.6926
245 108.5076
246 93.3387
247 83.4066
248 78.2776
249 76.117
250 76.928
251 79.6006
252 80.6988
253 81.2004
254 81.5383
255 82.312
256 86.2426
257 90.3859
258 98.6033
259 104.0946
260 108.019
261 109.7834
262 108.6141
263 106.38
264 101.0772
265 98.3763
266 100.9061
267 104.47
268 107.9876
269 106.8441
270 102.2556
271 97.2365
272 93.9402
273 90.2257
274 85.5674
275 80.8997
276 81.8642
277 86.2856
278 91.0875
279 98.3046
280 109.3468
281 119.6241
282 125.3246
283 116.9737
284 111.7356
285 114.9095
286 118.941
287 118.3607
288 114.1549
289 110.6046
290 108.7953
291 107.5064
292 107.6083
293 111.1036
294 120.3535
295 128.9578
296 124.7481
297 114.643
298 101.7061
299 95.8025
300 97.7859
301 106.7798
302 116.023
303 125.013
304 132.4194
305 133.7434
306 133.7246
307 131.7204
308 129.9015
309 129.9588
310 128.8842
311 126.9713
312 125.4242
313 124
314 126.6155
315 124.6455
316 120.835
317 118.3444
318 116.5524
319 118.9593
320 123.1053
321 126.0479
322 130.9525
323 135.4199
324 134.1377
325 131.2316
326 126.1753
327 122.0037
328 123.0428
329 126.1982
330 131.0241
331 131.5077
332 129.9423
333 127.4051
334 121.1131
335 114.0826
336 111.1502
337 114.0077
338 117.9712
339 120.1214
340 116.1757
341 116.3994
342 117.3426
343 118.4549
344 123.1898
345 128.0388
346 130.8989
347 132.1482
348 134.7526
349 137.2518
350 135.8791
351 132.4527
352 131.5093
353 134.7204
354 139.6778
355 141.7032
356 138.3304
357 134.7846
358 134.1262
359 134.7737
360 134.4413
361 133.0449
362 131.467
363 128.6181
364 127.5653
365 129.0032
366 131.1338
367 129.7332
368 122.5033
369 122.8529
370 122.1964
371 124.057
372 121.7062
373 123.3617
374 127.8247
375 136.8639
376 146.3494
377 155.8409
378 159.1537
379 154.3898
380 141.62
381 125.7971
382 115.5086
383 113.3914
384 119.1872
385 127.733
386 133.2778
387 135.9021
388 135.7259
389 130.9865
390 126.143
391 125.7297
392 129.0567
393 133.0479
394 131.7878
395 125.6109
396 121.5783
397 119.9594
398 117.5893
399 111.1285
400 111.2892
401 118.8116
402 124.2585
403 128.9327
404 132.8932
405 136.2814
406 142.0206
407 144.5256
408 138.9581
409 131.7846
410 125.7164
411 127.5952
412 135.2085
413 142.3344
414 142.0228
415 136.8064
416 130.9297
417 120.9267
418 108.406
419 105.4385
420 106.9476
421 112.3009
422 119.2317
423 124.0372
424 120.3514
425 115.0213
426 114.23
427 117.9489
428 125.4526
429 132.8448
430 130.1599
431 126.4696
432 124.0636
433 126.155
434 130.8905
435 131.1553
436 129.9513
437 130.128
438 127.4185
439 122.5475
440 121.9109
441 127.2979
442 135.6752
443 132.5314
444 131.5318
445 136.3115
446 139.7606
447 142.606
448 145.5297
449 147.4776
450 149.6077
451 152.3616
452 153.1246
453 151.1596
454 141.7695
455 134.2492
456 125.0534
457 110.677
458 109.8336
459 113.7081
460 118.262
461 126.3907
462 134.2709
463 139.4033
464 142.5516
465 143.4649
466 141.662
467 140.2668
468 133.4089
469 134.5155
470 145.7199
471 154.8817
472 155.556
473 150.7269
474 141.6581
475 133.7163
476 135.7772
477 145.1217
478 146.3618
479 135.8732
480 119.4615
481 106.8954
482 107.6851
483 124.9884
484 148.5361
485 158.9883
486 157.4792
487 149.2056
488 140.9259
489 136.7815
490 138.0292
491 144.7311
492 149.0806
493 145.5194
494 138.6854
495 132.2191
496 126.8012
497 125.021
498 127.9863
499 144.4257
500 147.9667
501 138.4207
502 122.2536
503 105.5693
504 92.8952
505 97.4881
506 113.6997
507 130.1503
508 139.6998
509 139.4896
510 140.0785
511 143.333
512 148.7983
513 144.9808
514 136.952
515 118.6987
516 104.5076
517 103.8359
518 122.1022
519 151.7319
520 177.951
521 187.2701
522 174.7837
523 150.7882
524 129.3103
525 113.47
526 106.3088
527 105.671
528 112.0483
529 121.5656
530 131.1446
531 142.6701
532 152.0541
533 161.7232
534 169.1981
535 170.9815
536 167.5816
537 162.2393
538 160.0597
539 156.7938
540 145.9165
541 129.761
542 119.0713
543 120.9512
544 122.8626
545 119.8288
546 109.5783
547 105.8803
548 107.4702
549 107.0279
550 103.0454
551 99.9842
552 101.1417
553 106.0349
554 110.0881
555 115.9291
556 118.5775
557 122.3185
558 118.8856
559 109.84
560 101.2797
561 95.8485
562 95.3104
563 97.5493
564 104.7847
565 110.8516
566 113.881
567 116.1661
568 125.0521
569 127.7381
570 113.6659
571 98.6984
572 85.5696
573 78.6104
574 78.0949
575 84.1564
576 93.1596
577 103.2147
578 109.6237
579 112.2092
580 113.5395
581 112.0343
582 110.8982
583 108.56
584 107.1803
585 108.8549
586 104.7038
587 91.7859
588 83.9778
589 81.2529
590 80.9087
591 74.5208
592 64.0746
593 53.8627
594 45.1626
595 35.0776
596 23.276
597 12.5548
598 7.5805
599 6.3552
600 9.9257
601 12.8008
602 19.1284
603 29.187
604 40.1449
605 42.917
606 32.3628
607 20.0431
608 14.9974
609 11.8088
610 12.381
611 16.2866
612 16.4584
613 18.5208
614 22.0444
615 32.0076
616 42.8529
617 48.4967
618 42.534
619 31.9595
620 26.473
621 25.402
622 25.5488
623 26.6132
624 26.8115
625 24.2577
626 21
Green (2) Feret values:
627
0 28
1 33.8593
2 34.1707
3 35.6286
4 37.6823
5 36.7904
6 35.2716
7 32.7536
8 29.1725
9 27.5609
10 26.8249
11 31.0899
12 43.8571
13 55.5222
14 72.0095
15 95.049
16 117.2326
17 130.8027
18 124.6626
19 113.1846
20 103.8479
21 96.4078
22 106.9445
23 132.1692
24 152.8412
25 149.8437
26 134.291
27 111.4572
28 95.4882
29 88.8815
30 92.2595
31 104.0364
32 116.6782
33 120.1449
34 115.4045
35 123.1383
36 127.23
37 117.0277
38 100.86
39 86.1185
40 79.1119
41 78.9197
42 68.3881
43 60.078
44 54.0981
45 43.187
46 33.3459
47 31.9146
48 36.6787
49 55.5754
50 85.0062
51 120.2664
52 144.103
53 141.4954
54 116.9263
55 77.3975
56 64.7598
57 65.0483
58 72.4056
59 98.9762
60 106.3056
61 101.5151
62 89.2819
63 79.2231
64 78.2799
65 79.2954
66 91.7957
67 107.2507
68 114.2896
69 118.6828
70 106.3505
71 91.3875
72 88.2863
73 88.8103
74 90.1076
75 92.9591
76 99.9669
77 107.3546
78 109.2377
79 105.3003
80 99.8661
81 90.3043
82 74.6527
83 58.4532
84 46.3245
85 38.8652
86 34.9877
87 33
88 37.4145
89 50.6917
90 69.7671
91 85.3554
92 103.8362
93 106.6479
94 93.0545
95 83.305
96 73.9439
97 63.9928
98 55.0949
99 46.5618
100 39.5456
101 55.5063
102 73.8098
103 92.2409
104 92.2345
105 82.5359
106 81.2032
107 89.059
108 101.759
109 115.5403
110 120.4046
111 105.4968
112 96.2583
113 91.1754
114 86.2481
115 81.2897
116 72.0391
117 66.9335
118 68.8852
119 77.0704
120 81.7362
121 77.4555
122 66.0105
123 52.2917
124 43.6356
125 36.3911
126 31.1461
127 28.1881
128 27.2404
129 30.0299
130 32.6429
131 34.3658
132 35.5435
133 38.1556
134 43.3123
135 45.3184
136 54.3218
137 78.2415
138 103.2353
139 110.943
140 104.4658
141 90.9752
142 78.8582
143 71.6287
144 68.0895
145 54.4636
146 46.3263
147 46.6859
148 55.7542
149 60.5508
150 70.4218
151 91.8965
152 120.7106
153 127.1886
154 116.3874
155 76.4129
156 79.3444
157 87.1464
158 90.617
159 98.4441
160 112.9974
161 126.7293
162 130.9597
163 129.4466
164 130.0058
165 131.7962
166 126.3716
167 121.7373
168 117.5633
169 118.5458
170 117.1661
171 110.4261
172 100.6053
173 87.6945
174 77.6388
175 72.8083
176 70.8946
177 68.5335
178 65.6332
179 64.3065
180 66.144
181 72.5795
182 82.9022
183 91.1588
184 96.7786
185 101.8544
186 106.8926
187 114.3003
188 117.1782
189 118.8447
190 118.5478
191 111.9735
192 107.743
193 108.3203
194 108.0063
195 103.9389
196 96.0134
197 89.9749
198 86.0692
199 86.8237
200 83.4514
201 82.4079
202 83.4546
203 90.838
204 100.5532
205 107.012
206 100.6378
207 87.2855
208 74.6434
209 67.0232
210 68.0198
211 66.9416
212 67.8266
213 72.6875
214 80.643
215 81.6898
216 74.7724
217 69.4203
218 66.0498
219 66.5925
220 65.1629
221 57.3645
222 47.2579
223 40.8357
224 36.5455
225 37.8298
226 37.3117
227 33.6365
228 29.7225
229 27.8396
230 29.1323
231 29.9347
232 33.3136
233 40.9204
234 51.5008
235 61.4377
236 70.4321
237 80.3241
238 88.2328
239 98.0046
240 105.5369
241 106.4846
242 103.8141
243 98.6422
244 97.8767
245 87.8112
246 72.0767
247 59.2919
248 51.3497
249 48.0589
250 51.0372
251 56.9377
252 59.6865
253 59.4906
254 56.4106
255 52.5889
256 46.3546
257 40.9537
258 39.016
259 39.9428
260 40.0834
261 38.0671
262 35.8675
263 33.8722
264 32.1629
265 32.7613
266 35.74
267 39.3597
268 43.9042
269 46.6198
270 48.2958
271 49.949
272 48.7038
273 46.6374
274 42.4831
275 36.2674
276 32.1368
277 32.2917
278 36.1789
279 41.7636
280 49.0688
281 55.8391
282 59.6102
283 61.9248
284 66.9164
285 77.432
286 81.9431
287 82.0025
288 78.0211
289 72.7889
290 67.4854
291 61.7853
292 58.0224
293 58.6919
294 63.2354
295 69.6815
296 73.779
297 69.7611
298 61.4472
299 52.5272
300 49.1436
301 50.8757
302 60.478
303 73.3107
304 84.1255
305 87.6689
306 86.5891
307 82.6286
308 78.7952
309 74.5808
310 69.8375
311 67.0927
312 66.7576
313 70
314 69.1582
315 68.0145
316 66.7408
317 66.7151
318 69.3705
319 71.691
320 75.7137
321 80.2746
322 82.5422
323 81.3145
324 77.1291
325 74.8084
326 72.3867
327 76.3946
328 81.8901
329 86.3603
330 86.5586
331 84.0898
332 80.2034
333 77.1212
334 73.7225
335 69.0253
336 65.6185
337 64.4675
338 66.2887
339 69.4372
340 68.4557
341 69.4329
342 68.4792
343 65.9581
344 64.5463
345 63.2083
346 64.1191
347 66.4228
348 69.8441
349 73.4604
350 77.2588
351 79.238
352 79.3591
353 80.8946
354 82.7243
355 82.845
356 80.4345
357 77.107
358 78.5148
359 81.9242
360 83.8247
361 80.2058
362 73.2992
363 64.8468
364 62.6245
365 65.4432
366 67.0891
367 67.3444
368 64.3007
369 59.0992
370 59.0841
371 67.2817
372 73.8163
373 79.0493
374 80.9776
375 82.4422
376 81.2036
377 80.174
378 77.7891
379 74.0623
380 71.8107
381 72.9706
382 73.7757
383 76.8057
384 80.5099
385 82.2873
386 81.7407
387 78.9206
388 76.3674
389 71.806
390 68.5847
391 70.2572
392 75.4272
393 80.6308
394 76.2311
395 64.4679
396 56.8373
397 51.624
398 50.0347
399 51.647
400 57.9627
401 66.1995
402 71.0764
403 75.6547
404 81.8648
405 88.0048
406 93.9248
407 92.6871
408 84.922
409 74.4297
410 58.4728
411 50.5524
412 49.1981
413 53.2859
414 58.482
415 63.3833
416 70.4502
417 68.3921
418 61.5198
419 60.2927
420 60.4358
421 65.9185
422 72.8368
423 77.3254
424 77.7269
425 78.3003
426 80.3341
427 81.2659
428 85.5761
429 92.8916
430 91.6953
431 85.989
432 80.0352
433 80.262
434 84.2962
435 86.6626
436 85.9788
437 84.4862
438 79.1242
439 71.8177
440 68.4281
441 66.4716
442 66.5368
443 69.0561
444 72.3966
445 76.764
446 79.0068
447 81.2929
448 87.6632
449 94.8227
450 104.9172
451 113.8059
452 112.2917
453 110.2537
454 105.7166
455 96.5645
456 87.1697
457 74.9606
458 77.8471
459 82.9596
460 86.6874
461 90.3206
462 93.0096
463 90.0111
464 90.6049
465 100.2446
466 99.3157
467 91.7619
468 89.0801
469 94.4853
470 106.907
471 120.9296
472 126.1263
473 122.8687
474 107.7928
475 93.9475
476 93.7118
477 96.5463
478 90.9794
479 82.7037
480 71.4313
481 60.8954
482 60.99
483 71.4213
484 85.6863
485 98.6099
486 101.5723
487 95.2954
488 89.471
489 87.8348
490 92.162
491 102.5924
492 108.3866
493 101.3612
494 90.4317
495 81.7995
496 75.4217
497 71.7227
498 73.7587
499 87.8318
500 94.032
501 91.7196
502 79.9654
503 61.5472
504 40.6187
505 38.5623
506 51.3954
507 64.1262
508 73.2491
509 79.6264
510 91.8656
511 107.2675
512 117.8662
513 112.506
514 100.2678
515 82.1127
516 70.3798
517 70.2462
518 87.598
519 113.3671
520 132.1888
521 134.8278
522 123.2752
523 107.2179
524 91.1099
525 80.1816
526 74.9567
527 66.4739
528 64.4377
529 74.333
530 83.3259
531 88.2712
532 92.9438
533 99.6015
534 107.636
535 115.3014
536 115.5911
537 110.8826
538 107.5659
539 104.0934
540 100.2414
541 91.2001
542 84.6793
543 85.8346
544 85.3094
545 80.6422
546 72.7866
547 73.4297
548 80.8178
549 82.9265
550 75.9534
551 65.136
552 59.9521
553 61.1974
554 65.3131
555 73.5032
556 79.8666
557 82.9147
558 80.6447
559 71.3676
560 59.8046
561 52.1546
562 50.3475
563 50.4123
564 48.6083
565 47.0818
566 52.5037
567 67.1741
568 85.1053
569 91.6078
570 68.0337
571 44.2016
572 29.6431
573 25.6329
574 23.722
575 22.8195
576 23.7619
577 26.2961
578 27.4461
579 26.7915
580 27.3159
581 29.0252
582 27.1981
583 28.0399
584 35.2716
585 42.0468
586 43.1502
587 33.9048
588 27.2444
589 25.0687
590 24.9655
591 23.9952
592 22.5463
593 22.4402
594 21.7631
595 18.5875
596 14.2077
597 10.0072
598 5.8595
599 5.2162
600 7.6924
601 9.6849
602 13.3357
603 18.1869
604 22.7207
605 23.9285
606 19.6942
607 14.016
608 11.0169
609 8.7945
610 9.2396
611 12.1911
612 12.3056
613 12.8962
614 12.1565
615 11.2725
616 12.4058
617 13.8589
618 14.6623
619 16.2965
620 17.4474
621 17.498
622 17.891
623 18.3798
624 18.476
625 17.6418
626 16
Blue (3) Feret values:
627
0 8
1 9.9113
2 12.1692
3 15.3087
4 19.7625
5 21.7075
6 23.0927
7 23.7588
8 23.5605
9 23.7252
10 24.2141
11 29.2576
12 42.496
13 54.4535
14 70.0255
15 93.9947
16 116.3165
17 129.8027
18 124.3974
19 113.1846
20 103.8479
21 96.4078
22 106.9445
23 132.1692
24 153.1092
25 150.789
26 134.6268
27 111.4572
28 95.8205
29 89.5827
30 92.4308
31 104.5754
32 117.4768
33 120.5284
34 115.9509
35 124.0537
36 128.23
37 118.0277
38 101.8526
39 86.8284
40 79.7801
41 77.6944
42 64.695
43 52.3165
44 44.7398
45 36.5008
46 30.413
47 31.3075
48 36.6787
49 55.6207
50 85.7236
51 121.1914
52 144.823
53 141.8997
54 116.9263
55 77.4371
56 65.3818
57 65.088
58 72.4365
59 98.9762
60 107.0883
61 102.5151
62 90.2039
63 79.5452
64 78.2799
65 79.7205
66 92.6676
67 107.7375
68 113.889
69 111.0227
70 87.1558
71 66.3914
72 64.3546
73 65.8481
74 67.476
75 69.6504
76 75.9528
77 82.5963
78 84.2377
79 80.8315
80 76.4551
81 70.4734
82 59.362
83 45.515
84 33.4233
85 26.4993
86 22.2529
87 18.0224
88 21.1278
89 32.247
90 49.1759
91 63.1631
92 78.7361
93 84.3019
94 78.4075
95 74.8048
96 68.7608
97 58.464
98 46.2665
99 36.8336
100 34.1594
101 51.6505
102 72.41
103 91.239
104 91.9246
105 82.5359
106 81.1514
107 89.5383
108 101.1833
109 108.4124
110 101.9786
111 76.8085
112 63.7385
113 61.4947
114 56.2481
115 49.9728
116 40.9156
117 36.8061
118 38.3388
119 43.0032
120 46.6228
121 45.7338
122 39.8089
123 30.1407
124 23.3149
125 20.0654
126 20.7732
127 23.7396
128 26.2404
129 29.0299
130 32.5055
131 34.3658
132 35.5435
133 38.1556
134 43.3123
135 45.3184
136 54.3218
137 78.2415
138 103.2353
139 110.943
140 104.4658
141 91.062
142 79.4588
143 71.8604
144 68.0895
145 54.4636
146 46.3263
147 46.6859
148 56.1207
149 61.0153
150 70.7732
151 92.4465
152 120.9986
153 127.8429
154 117.2117
155 76.4129
156 79.3597
157 87.2096
158 90.8885
159 98.8322
160 113.7201
161 127.3188
162 131.1802
163 129.9898
164 130.0767
165 130.0877
166 121.402
167 112.0813
168 101.437
169 91.9049
170 85.8044
171 78.6792
172 70.0275
173 59.6203
174 52.5588
175 50.2234
176 49.3163
177 48.5815
178 47.398
179 47.0737
180 50.7671
181 56.9654
182 65.52
183 72.2107
184 75.3797
185 77.864
186 82.3035
187 86.7439
188 89.2199
189 87.7932
190 87.735
191 86.424
192 83.3802
193 82.6884
194 82.4089
195 80.1704
196 75.1833
197 71.1034
198 67.7944
199 66.536
200 63.5573
201 62.0224
202 62.5028
203 68.1945
204 74.4033
205 77.7298
206 74.2875
207 66.4389
208 59.6439
209 54.4441
210 52.6585
211 50.9249
212 53.3095
213 59.3408
214 63.7548
215 60.923
216 52.6925
217 50.9621
218 53.3327
219 54.6996
220 53.3994
221 47.8271
222 39.7668
223 31.4825
224 25.2153
225 23.9183
226 23.5895
227 20.7442
228 19.6168
229 21.9054
230 25.5486
231 25.8158
232 25.66
233 26.3005
234 33.2109
235 42.4278
236 51.7732
237 61.5691
238 69.3608
239 78.5334
240 85.5916
241 84.4042
242 84.3955
243 82.1253
244 80.1444
245 68.6243
246 55.1374
247 47.1257
248 43.0557
249 42.0557
250 45.7848
251 50.9585
252 52.9808
253 52.4904
254 49.3547
255 47.6523
256 43.361
257 38.8898
258 37.8544
259 38.9428
260 39.0834
261 37.518
262 35.187
263 32.8722
264 30.7188
265 30.0137
266 31.593
267 34.6521
268 38.8159
269 41.6198
270 43.2816
271 43.9985
272 43.9562
273 42.377
274 39.2243
275 33.5879
276 29.9835
277 29.3169
278 30.5048
279 32.7332
280 35.8164
281 39.0733
282 41.6211
283 44.1219
284 48.1286
285 55.4197
286 60.3131
287 62.6709
288 60.3945
289 56.0764
290 51.4854
291 46.8779
292 43.5463
293 42.5719
294 44.8712
295 48.1843
296 49.5783
297 47.8819
298 42.8358
299 38.4191
300 37.4184
301 40.5288
302 47.2939
303 55.4112
304 61.7567
305 63.0251
306 61.8223
307 58.0272
308 54.5209
309 51.2652
310 45.5815
311 42.7572
312 44.0895
313 48
314 51.667
315 52.7668
316 52.2198
317 52.0067
318 53.3769
319 55.6374
320 57.2013
321 56.9902
322 56.7512
323 56.5502
324 53.8968
325 52.1088
326 50.5463
327 52.7178
328 56.9834
329 61.9322
330 64.0181
331 64.2275
332 61.6964
333 58.6693
334 55.4162
335 51.7403
336 49.4138
337 48.6435
338 49.0462
339 51.7335
340 51.0111
341 50.7737
342 48.8754
343 47.9214
344 47.2211
345 46.4971
346 44.7197
347 45.3482
348 46.9335
349 48.155
350 50.8429
351 54.3377
352 56.2026
353 57.7812
354 58.6079
355 57.8498
356 55.4181
357 54.1609
358 56.4401
359 58.4621
360 59.0096
361 55.6308
362 51.4531
363 47.6167
364 46.6439
365 47.8925
366 47.7985
367 46.7435
368 42.2343
369 38.526
370 39.0038
371 43.7066
372 46.5208
373 48.7045
374 50.0411
375 52.3125
376 54.3558
377 54.7668
378 52.7348
379 49.8772
380 49.5508
381 52.0195
382 51.7521
383 52.0989
384 53.7342
385 56.8262
386 59.7153
387 60.984
388 58.5435
389 54.1645
390 50.9105
391 50.5581
392 52.0063
393 53.9714
394 51.2606
395 44.892
396 40.2419
397 36.4195
398 34.4281
399 34.4961
400 36.9817
401 39.427
402 39.7645
403 40.3162
404 42.86
405 45.3291
406 50.0097
407 52.8723
408 51.2392
409 48.0924
410 39.2548
411 35.253
412 34.0511
413 35.5415
414 38.8339
415 41.4685
416 44.2933
417 42.3884
418 37.2712
419 34.9818
420 33.9904
421 37.3093
422 41.6326
423 44.3302
424 44.6951
425 45.2119
426 46.8019
427 46.4329
428 47.0394
429 51.5851
430 53.1975
431 53.3802
432 52.0287
433 51.6893
434 52.467
435 50.5543
436 47.7551
437 47.4123
438 46.0607
439 43.1162
440 39.6138
441 37.0049
442 37.6742
443 37.9546
444 38.6215
445 40.7476
446 41.7701
447 42.9332
448 47.6044
449 52.2873
450 55.7585
451 58.4117
452 60.5946
453 62.7372
454 59.6997
455 56.345
456 51.2748
457 45.1882
458 47.2268
459 49.1006
460 48.0759
461 48.7786
462 49.7105
463 49.0734
464 49.4068
465 50.7855
466 47.3304
467 41.861
468 39.7478
469 42.2112
470 49.1026
471 56.4919
472 61.8164
473 61.8259
474 53.8567
475 45.9415
476 44.7596
477 46
478 44.1428
479 39.0974
480 32.6773
481 28.7009
482 28.7291
483 35.3307
484 45.1885
485 53.2529
486 55.5589
487 51.7971
488 47.0479
489 43.501
490 43.6554
491 48.6013
492 53.1054
493 52.1022
494 47.7393
495 42.6466
496 39.5631
497 37
498 37
499 43.3898
500 44.7754
501 41.7954
502 35.9776
503 28.3964
504 21.0238
505 22.5431
506 29.607
507 34.5767
508 38.2077
509 41.2951
510 48.9455
511 59.2419
512 70.7041
513 68.8852
514 62.2577
515 49.8519
516 40.0487
517 38.4731
518 46.6236
519 59.7949
520 70.3362
521 73.1599
522 66.471
523 57.1208
524 48.0036
525 40.8929
526 37.0717
527 32.3078
528 32.2141
529 38
530 43.6202
531 48.9305
532 54.3306
533 58.2881
534 60.551
535 61.7432
536 59.8483
537 58.4969
538 61.8398
539 65.4831
540 62.0461
541 53.2232
542 46.6799
543 46.38
544 47.1177
545 45.2375
546 42.9669
547 45.1565
548 50.0422
549 49.6266
550 42.7412
551 36.5721
552 35.542
553 38.3615
554 42.338
555 47.1498
556 49.5775
557 52.0763
558 51.1316
559 44.8521
560 38.2839
561 33.7664
562 32.9993
563 33.3514
564 33.2
565 30.9482
566 29.6702
567 34.1726
568 41.8722
569 44.7633
570 35.1026
571 26.5581
572 21.8763
573 21.5259
574 20.657
575 19.639
576 20.2124
577 22.7855
578 23.7636
579 21.5184
580 20.2588
581 20.9058
582 18.7417
583 19.4649
584 23.361
585 26.9149
586 27.5299
587 23.9837
588 20.9875
589 20.9931
590 22.4959
591 22.8764
592 22.0927
593 21.8803
594 21.7631
595 18.5875
596 14.2077
597 10.0072
598 5.8595
599 5.2162
600 7.6924
601 9.6849
602 13.3357
603 17.5703
604 22.267
605 23.9285
606 19.6942
607 14.016
608 11.0169
609 8.6528
610 8.3355
611 11.685
612 12.303
613 11.965
614 11.1565
615 11
616 12.4058
617 13.8589
618 14.6623
619 16.2965
620 17.4474
621 17.498
622 17.891
623 18.3798
624 18.3723
625 17.2728
626 16

Thanks, mm