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].
frzn's
texNCUT
f1: 0
f2: 0
f3: 1
f4: 0
Farzaneh Alizadeh, Nader Karimi, Niloofar Gheissari:   Textural image segmentation using Normalized Cut

TexNCUT use from Texture features and a graph based image segmentation method(Ncut) for textural image segmentation. our algorithm employ super-pixels to increase speed and efficiency.

In TexNCUT the number of regions for the evaluated partitions was manually set to the number of regions in the ground truth partitions.

List of uploaded results for 'texNCUT' 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] texNCUT 72.54 10.92 9.61 10.25 9.83 7.33 8.17 80.58 86.89 88.28 13.11 2.36 86.39 80.33 3.69 86.97 11.92 6.85 20.64 15.56 86.89 82.46 81.90 9.18 84.35 4.30 14.49 84.14 6.03 81.48 75.77 85.35 85.50 84.76 86.57 4.49
Colour [large] texNCUT 72.54 10.92 9.61 10.25 9.83 7.33 8.17 80.58 86.89 88.28 13.11 2.36 86.39 80.33 3.69 86.97 11.92 6.85 20.64 15.56 86.89 82.46 81.90 9.18 84.35 4.30 14.49 84.14 6.03 81.48 75.77 85.35 85.50 84.76 86.57 4.49