Table 2 FCM border error, precision, and recall measures for each image in the dataset
Img. ID | Border Error | Precision | Recall | Â | Img. ID | Border Error | Precision | Recall |
|---|---|---|---|---|---|---|---|---|
1 | 99% | 1 | 0.635 | Â | 51 | 99.9% | 0.99 | 0.66 |
2 | 99.98% | 1 | 0.65 | Â | 52 | 132.5% | 1 | 0.5 |
3 | 100% | 1 | 0.62 | Â | 53 | 69.93% | 1 | 0.45 |
4 | 101% | 1 | 0.54 | Â | 54 | 100% | 1 | 0.56 |
5 | 98% | 1 | 0.66 | Â | 55 | 89.47% | 1 | 0.45 |
6 | 96% | 1 | 0.55 | Â | 56 | 108.13% | 1 | 0.52 |
7 | 105% | 1 | 0.645 | Â | 57 | 96% | 0.99 | 0.65 |
8 | 100% | 1 | 0.66 | Â | 58 | 105% | 1 | 0.62 |
9 | 89% | 1 | 0.7 | Â | 59 | 100% | 1 | 0.56 |
10 | 106% | 1 | 0.7 | Â | 60 | 78.32% | 1 | 0.51 |
11 | 100% | 1 | 0.79 | Â | 61 | 96.82% | 1 | 0.53 |
12 | 98% | 1 | 0.35 | Â | 62 | 106.83% | 1 | 0.34 |
13 | 97% | 1 | 0.45 | Â | 63 | 100% | 1 | 0.71 |
14 | 99% | 1 | 0.76 | Â | 64 | 103.33% | 0.98 | 0.56 |
15 | 103% | 1 | 0.23 | Â | 65 | 101% | 1 | 0.47 |
16 | 98% | 1 | 0.63 | Â | 66 | 96.86% | 0.95 | 0.52 |
17 | 100% | 1 | 0.2 | Â | 67 | 100% | 1 | 0.65 |
18 | 89% | 1 | 0.54 | Â | 68 | 106.83% | 1 | 0.62 |
19 | 99% | 1 | 0.33 | Â | 69 | 99% | 1 | 0.34 |
20 | 99.9% | 1 | 0.67 | Â | 70 | 106.67% | 1 | 0.49 |
21 | 92.9% | 1 | 0.65 | Â | 71 | 102.3% | 1 | 0.65 |
22 | 98% | 1 | 0.71 | Â | 72 | 99.9% | 1 | 0.71 |
23 | 78.3% | 1 | 0.56 | Â | 73 | 123% | 1 | 0.48 |
24 | 96.8% | 1 | 0.45 | Â | 74 | 105.3% | 1 | 0.53 |
25 | 106% | 1 | 0.5 | Â | 75 | 103.6% | 1 | 0.5 |
26 | 123% | 1 | 0.65 | Â | 76 | 98% | 1 | 0.58 |
27 | 105.4% | 1 | 0.56 | Â | 77 | 106.8% | 1 | 0.45 |
28 | 104.7% | 1 | 0.59 | Â | 78 | 107% | 1 | 0.76 |
29 | 98% | 0.99 | 0.501 | Â | 79 | 89.3% | 1 | 0.69 |
30 | 95% | 1 | 0.63 | Â | 80 | 96.8% | 1 | 0.59 |
31 | 93.7% | 1 | 0.34 | Â | 81 | 100% | 1 | 0.63 |
32 | 96.8% | 1 | 0.49 | Â | 82 | 102.3% | 1 | 0.34 |
33 | 100% | 1 | 0.53 | Â | 83 | 103.3% | 1 | 0.56 |
34 | 101% | 1 | 0.43 | Â | 84 | 100% | 1 | 0.32 |
35 | 98% | 1 | 0.39 | Â | 85 | 100% | 1 | 0.67 |
36 | 103% | 1 | 0.65 | Â | 86 | 89% | 1 | 0.65 |
37 | 98% | 1 | 0.62 | Â | 87 | 106.6% | 1 | 0.71 |
38 | 100% | 1 | 0.6 | Â | 88 | 99% | 1 | 0.56 |
39 | 89% | 1 | 0.46 | Â | 89 | 106.8% | 0.97 | 0.5 |
40 | 106.6% | 1 | 0.48 | Â | 90 | 118.4% | 1 | 0.48 |
41 | 93.6% | 1 | 0.54 | Â | 91 | 98.3% | 1 | 0.65 |
42 | 96.8% | 1 | 0.59 | Â | 92 | 99.6% | 1 | 0.62 |
43 | 100% | 1 | 0.57 | Â | 93 | 122.4% | 1 | 0.45 |
44 | 89% | 1 | 0.63 | Â | 94 | 100% | 1 | 0.48 |
45 | 107% | 1 | 0.76 | Â | 95 | 106.6% | 1 | 0.56 |
46 | 89.3% | 1 | 0.64 | Â | 96 | 93.6% | 1 | 0.43 |
47 | 96.8% | 1 | 0.45 | Â | 97 | 96.8% | 0.99 | 0.51 |
48 | 106.7% | 1 | 0.48 | Â | 98 | 100% | 1 | 0.53 |
49 | 99% | 1 | 0.56 | Â | 99 | 89% | 1 | 0.49 |
50 | 99.9% | 1 | 0.59 | Â | 100 | 107% | 1 | 0.53 |