The Prague Texture Segmentation Datagenerator and Benchmark - Algorithms
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The concise description of algorithms contains hyperlinks to further information (author, algorithms details, BIB entry, WWW external page).
The algorithm features are: f1 = classification (supervised segmentation), f2 = hiearchy result (manual selection), f3 = known number of regions, f4 = [reserved].
cpanag@csd.uoc.gr's
Results_vote_Class_merge
WEB
f1: 0
f2: 0
f3: 0
f4: 0
Costas Panagiotakis, Ilias Grinias and Georgios Tziritas:   Texture Segmentation Based on Voting of Blocks, Bayesian Flooding and Region Merging

We propose an unsupervised texture image segmentation framework with unknown number of regions, which involves feature extraction and classification in feature space, followed by flooding and merging in spatial domain. The distribution of the features for the different classes are obtained by a block-wise unsupervised voting framework using the blocks grid graph or its minimum spanning tree and the Mallows distance. The final clustering is obtained by using the k-centroids algorithm. An efficient flooding algorithm is used, namely, Priority Multi-Class Flooding Algorithm (PMCFA), that assign pixels to labels using Bayesian dissimilarity criteria. Finally, a region merging method, which incorporates boundary information, is introduced for obtaining the final segmentation map. The proposed scheme is executed for several number of regions, we select the number of regions that minimize a criterion that takes into account the average likelihood per pixel of the classification map and penalizes the complexity of the regions boundaries. Segmentation results on the Prague benchmark data set demonstrate the high performance of the proposed scheme.

List of uploaded results for 'Results_vote_Class_merge' algorithm
   benchmark label version CS OS US ME NE O C CA CO CC I II EA MS RM CI GCE LCE BCE GBCE BGM SC SSC VD L AVI NVI NMI M ARI JC DC FMI WI WII NBDE
#Colour [large] Results_vote_Class_merge 2.0 (full distance) 67.42 15.50 14.77 5.78 5.14 9.95 14.79 78.13 84.20 85.72 15.80 2.46 83.37 78.69 5.35 84.14 6.32 4.09 22.14 19.91 84.20 80.79 80.43 9.51 83.06 3.91 12.09 85.54 6.88 80.31 74.80 84.59 85.32 85.13 87.04 4.65
#Colour [large] Results_vote_Class_merge VFB-2 70.19 16.31 13.54 5.18 4.74 7.47 13.58 80.58 85.81 88.94 14.19 2.03 85.64 80.99 4.56 86.44 6.39 3.75 20.10 17.46 85.81 82.12 82.51 8.61 85.12 3.56 10.75 87.07 6.01 82.31 77.05 86.01 86.58 86.85 87.52 4.05
#Colour [large] Results_vote_Class_merge VFB 3.0 69.84 17.44 11.60 5.57 5.30 6.17 13.01 81.17 86.00 89.91 14.00 1.89 86.34 81.59 4.39 87.10 6.51 3.76 19.98 17.24 86.00 82.21 82.85 8.49 86.00 3.55 10.60 87.39 5.82 82.46 77.02 86.02 86.58 87.77 86.57 3.95
#Colour [large] Results_vote_Class_merge 30_12_2013 73.70 11.35 12.79 5.25 5.18 6.20 7.30 81.89 87.21 88.61 12.79 1.81 86.48 82.34 4.20 87.16 6.42 3.85 18.62 16.05 87.21 83.99 83.58 8.03 84.95 3.40 10.49 87.79 5.38 83.52 78.11 86.78 87.34 86.25 89.61 3.52
#Colour [large] Results_vote_Class_merge 22 71.98 15.29 10.71 5.61 5.62 5.02 9.27 82.35 87.20 90.31 12.80 1.58 87.26 82.86 3.96 87.97 6.76 3.92 18.78 15.94 87.20 83.53 83.86 8.06 86.39 3.42 10.33 87.88 5.04 84.21 78.74 87.30 87.73 88.40 87.96 3.49
#Colour [large] Results_vote_Class_merge 28 74.14 12.98 10.23 5.52 5.47 4.63 8.92 83.19 87.99 90.38 12.01 1.54 87.84 83.74 3.76 88.48 6.64 3.97 17.72 15.04 87.99 84.58 84.66 7.68 86.81 3.28 10.02 88.30 4.82 84.98 79.77 87.94 88.33 88.63 88.86 3.35
#Colour [large] Results_vote_Class_merge 30 74.45 12.98 9.22 6.22 6.19 4.03 8.55 83.50 88.18 90.92 11.82 1.46 88.17 84.02 3.70 88.83 6.85 4.06 17.60 14.80 88.18 84.64 84.82 7.68 87.15 3.28 10.00 88.36 4.76 85.01 79.77 87.94 88.30 88.76 88.58 3.38
#Colour [large] Results_vote_Class_merge 0209 73.85 11.77 12.88 5.48 5.08 6.37 7.96 81.87 87.20 88.56 12.80 2.07 86.42 82.20 4.39 87.10 6.24 3.84 18.56 16.16 87.20 83.86 83.63 7.99 85.71 3.40 10.61 87.53 5.84 83.21 78.13 86.71 87.29 86.08 89.75 3.55
#Colour [large] Results_vote_Class_merge 0211 73.97 12.67 10.11 6.85 6.44 3.93 6.07 83.12 87.95 90.66 12.05 1.67 87.90 83.61 3.95 88.56 6.66 4.06 18.01 15.41 87.95 84.27 84.57 7.81 87.21 3.31 10.22 88.17 5.03 84.37 79.08 87.47 87.87 88.42 88.16 3.34
#Colour [large] Results_vote_Class_merge 0213 74.12 12.49 10.40 4.43 4.24 4.73 9.20 82.85 87.68 90.03 12.32 1.53 87.53 83.33 3.90 88.16 6.42 3.91 17.93 15.41 87.68 84.29 84.49 7.79 86.94 3.29 10.04 88.34 4.86 84.65 79.25 87.62 88.04 88.65 88.31 3.48
Colour [large] VRA-PMCFA 75.14 12.13 9.85 4.38 4.37 4.51 8.89 83.45 88.12 90.73 11.88 1.48 88.07 83.92 3.75 88.72 6.55 3.90 17.51 14.86 88.12 84.63 84.95 7.59 87.58 3.25 9.89 88.52 4.76 84.94 79.62 87.84 88.25 88.92 88.43 3.40
Colour [large] VRA-PMCFA 75.14 12.13 9.85 4.38 4.37 4.51 8.89 83.45 88.12 90.73 11.88 1.48 88.07 83.92 3.75 88.72 6.55 3.90 17.51 14.86 88.12 84.63 84.95 7.59 87.58 3.25 9.89 88.52 4.76 84.94 79.62 87.84 88.25 88.92 88.43 3.40
#Colour [large] Results_vote_Class_merge test 64 bit 75.32 11.95 9.65 4.57 4.63 4.51 8.87 83.49 88.16 90.73 11.84 1.47 88.10 83.98 3.76 88.74 6.52 3.92 17.47 14.87 88.16 84.67 84.99 7.58 87.59 3.24 9.88 88.53 4.75 84.96 79.65 87.87 88.28 88.93 88.48 3.38
#Colour [large] Results_vote_Class_merge Init mean 75.20 12.13 10.30 3.86 3.85 4.18 8.79 83.50 88.17 90.59 11.83 1.51 88.08 84.00 3.74 88.70 6.35 3.80 17.41 14.86 88.17 84.74 85.06 7.51 87.70 3.22 9.82 88.59 4.75 85.05 79.74 87.94 88.37 88.90 88.72 3.35
BTF wood [exp.] [normal] VRA-PMCFA 59.55 16.10 29.22 6.00 6.33 16.15 16.98 72.28 80.25 81.30 19.75 2.78 78.35 73.17 6.37 79.51 6.27 3.77 26.54 24.04 80.25 76.79 75.94 11.45 78.52 3.92 12.70 84.72 7.75 77.16 70.69 81.82 82.87 80.74 87.23 4.52