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].
xaos's
MW3AR
BIB
DOC
f1: 0
f2: 0
f3: 0
f4: 0
M. Haindl, S. MikeŇ°, P. Pudil:   Hierarchy 3D autoregressive random field model

An unsupervised multi-spectral, multi-resolution, multiple-segmenter for textured images with unknown number of classes is presented. The segmenter is based on a weighted combination of several unsupervised segmentation results, each in different resolution, using the modified sum rule. Multi-spectral textured image mosaics are locally represented by four causal directional multi-spectral random field models recursively evaluated for each pixel. The single-resolution segmentation part of the algorithm is based on the underlying Gaussian mixture model and starts with an over segmented initial estimation which is adaptively modified until the optimal number of homogeneous texture segments is reached.



List of uploaded results for 'MW3AR' 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 [normal] MW3AR 53.04 59.53 3.20 5.63 6.96 19.32 86.19 71.89 74.66 95.04 25.34 0.74 80.43 71.78 3.09 82.43 8.17 5.78 34.50 32.11 74.66 66.84 72.27 14.78 80.63 7.16 12.59 79.57 8.97 68.82 61.24 73.42 75.65 91.53 64.93 7.12
#Colour [normal] MW3AR w_o pp 49.64 30.02 2.67 16.83 17.98 19.06 29.48 71.58 75.22 92.77 24.78 1.14 80.69 70.49 5.63 82.25 11.55 8.82 33.71 30.98 75.22 67.90 71.97 15.79 80.68 6.47 17.70 79.46 9.34 68.44 60.75 73.41 74.99 87.69 65.83 7.66