The Prague Texture Segmentation Datagenerator and Benchmark - Results
optimized
for

Results are sorted by criterion 'BCE' (bidirectional consistency error) in ascending order. The sorting criterium or the order can be changed by clicking on the appropriate criterium label. Subset of compared results can be filtered by several filters below. The segmentation details (single mosaics and their corresponding criteria values) are visible by clicking on the order number. Below the criterium labels are mean and standard deviation of the values of displayed results. They are used to compute z-scores which are displayed in brackets. The ranks are displayed in parentheses.

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? 0 1   f1 = classification (supervised segmentation)
? 0 1   f2 = hiearchy result (manual selection)
? 0 1   f3 = known number of regions
? 0 1   f4 = [reserved]
Filter by degradationtype: ? no Gaussian Poisson Salt&pepper Blur (Gaussian) Median
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Algorithm: Version:

   
Benchmark - Colour f1 f2 f3 f4 AVG
RANK
NORM
CS
41.46
±9.02
OS
18.36
±18.96
US
12.04
±7.47
ME
27.94
±2.24
NE
27.76
±2.25
O
24.80
±6.29
C
30.62
±31.56
CA
62.54
±5.02
CO
71.46
±6.36
CC
80.09
±7.00
I
28.54
±6.36
II
4.73
±2.36
EA
71.87
±4.13
MS
60.57
±4.43
RM
7.16
±0.92
CI
73.68
±3.67
GCE
18.41
±2.11
LCE
12.28
±1.23
criterion 'BCE' (bidirectional consistency error) in ascending orderBCE
39.46
±6.73
GBCE
33.34
±7.40
BGM
71.46
±6.36
SC
64.52
±7.50
SSC
64.57
±5.31
VD
19.39
±2.81
L
71.84
±3.07
AVI
7.89
±1.18
NVI
23.29
±1.62
NMI
71.62
±2.86
M
13.75
±2.32
ARI
59.89
±5.62
JC
54.34
±6.48
DC
68.18
±5.67
FMI
69.62
±4.70
WI
70.92
±6.61
WII
71.52
±12.43
NBDE
8.70
±0.96
 1.  scarpa's TFR/KLD   [normal] 0 1 0 0  76.65 
 (2.06) 
 [0.331] 
51.25
(1)
[1.086]
5.84
(2)
[-0.660]
7.16
(2)
[-0.653]
31.64
(4)
[1.654]
31.38
(4)
[1.609]
19.65
(2)
[-0.819]
9.67
(1)
[-0.664]
67.45
(1)
[0.979]
76.40
(1)
[0.778]
81.12
(3)
[0.147]
23.60
(1)
[-0.778]
4.09
(2)
[-0.273]
75.80
(2)
[0.953]
65.19
(1)
[1.043]
7.21
(3)
[0.048]
77.21
(2)
[0.961]
20.36
(3)
[0.928]
14.36
(4)
[1.686]
34.33
(1)
[-0.762]
28.34
(2)
[-0.676]
76.40
(1)
[0.778]
69.58
(1)
[0.674]
69.20
(1)
[0.872]
18.01
(2)
[-0.490]
74.35
(2)
[0.816]
7.63
(2)
[-0.226]
24.48
(3)
[0.736]
71.43
(2)
[-0.068]
12.64
(2)
[-0.478]
63.75
(2)
[0.688]
58.96
(2)
[0.712]
71.77
(2)
[0.632]
72.35
(2)
[0.580]
69.11
(3)
[-0.274]
76.80
(2)
[0.425]
8.38
(3)
[-0.329]
 2.  xiaofang's LocalGlobalGraph color  [normal] 0 1 0 0  76.67 
 (1.86) 
 [0.649] 
41.42
(3)
[-0.005]
15.04
(3)
[-0.175]
12.48
(3)
[0.059]
27.64
(3)
[-0.133]
26.92
(2)
[-0.371]
17.80
(1)
[-1.112]
15.13
(3)
[-0.491]
66.53
(2)
[0.795]
75.75
(2)
[0.676]
82.19
(2)
[0.299]
24.25
(2)
[-0.676]
4.17
(3)
[-0.238]
76.10
(1)
[1.025]
63.63
(2)
[0.690]
6.72
(2)
[-0.478]
77.48
(1)
[1.035]
20.47
(4)
[0.983]
11.25
(1)
[-0.839]
35.25
(2)
[-0.625]
26.03
(1)
[-0.988]
75.75
(2)
[0.676]
68.47
(3)
[0.527]
68.43
(2)
[0.726]
17.13
(1)
[-0.805]
75.42
(1)
[1.165]
6.47
(1)
[-1.208]
21.84
(2)
[-0.894]
76.07
(1)
[1.558]
11.22
(1)
[-1.094]
66.22
(1)
[1.126]
59.42
(1)
[0.784]
73.37
(1)
[0.914]
73.72
(1)
[0.873]
74.33
(2)
[0.516]
73.83
(3)
[0.186]
8.02
(1)
[-0.706]
 3.  scarpa's TFR  [normal] 0 1 0 0  73.61 
 (2.92) 
 [-0.186] 
46.13
(2)
[0.517]
2.37
(1)
[-0.844]
23.99
(4)
[1.600]
26.70
(2)
[-0.550]
25.23
(1)
[-1.123]
28.73
(3)
[0.625]
12.50
(2)
[-0.574]
61.32
(3)
[-0.242]
73.00
(3)
[0.243]
68.91
(4)
[-1.599]
27.00
(3)
[-0.243]
8.56
(4)
[1.623]
68.62
(3)
[-0.786]
59.76
(3)
[-0.183]
8.61
(4)
[1.571]
69.73
(4)
[-1.078]
15.51
(1)
[-1.373]
12.03
(3)
[-0.207]
37.29
(3)
[-0.323]
33.80
(3)
[0.063]
73.00
(3)
[0.243]
68.48
(2)
[0.528]
64.83
(3)
[0.048]
18.21
(3)
[-0.419]
68.54
(4)
[-1.074]
7.73
(3)
[-0.139]
25.28
(4)
[1.230]
68.13
(4)
[-1.224]
17.47
(4)
[1.604]
57.90
(3)
[-0.353]
55.57
(3)
[0.189]
68.82
(3)
[0.112]
70.72
(3)
[0.234]
61.21
(4)
[-1.468]
84.40
(1)
[1.036]
8.05
(2)
[-0.677]
 4.  test's SWA def_par  [normal] 0 1 0 0  66.59 
 (3.17) 
 [-0.794] 
27.06
(4)
[-1.598]
50.21
(4)
[1.680]
4.53
(1)
[-1.006]
25.76
(1)
[-0.971]
27.50
(3)
[-0.115]
33.01
(4)
[1.305]
85.19
(4)
[1.729]
54.84
(4)
[-1.533]
60.67
(4)
[-1.697]
88.17
(1)
[1.154]
39.33
(4)
[1.697]
2.11
(1)
[-1.111]
66.94
(4)
[-1.193]
53.71
(4)
[-1.550]
6.11
(1)
[-1.141]
70.32
(3)
[-0.918]
17.27
(2)
[-0.538]
11.50
(2)
[-0.641]
50.96
(4)
[1.710]
45.18
(4)
[1.601]
60.67
(4)
[-1.697]
51.56
(4)
[-1.729]
55.84
(4)
[-1.646]
24.20
(4)
[1.714]
69.05
(3)
[-0.908]
9.75
(4)
[1.572]
21.56
(1)
[-1.071]
70.86
(3)
[-0.266]
13.68
(3)
[-0.032]
51.67
(4)
[-1.461]
43.43
(4)
[-1.686]
58.77
(4)
[-1.659]
61.69
(4)
[-1.687]
79.03
(1)
[1.226]
51.05
(4)
[-1.647]
10.34
(4)
[1.713]