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].
mevenkamp's
PCA-MS
BIB
WEB
SRC
DOC
f1: 0
f2: 0
f3: 0
f4: 0
Niklas Mevenkamp, Benjamin Berkels:   Variational Multi-Phase Segmentation using High-Dimensional Local Features

A variational multi-phase segmentation framework based on the Mumford-Shah energy, combined with PCA-based dimension reduction is used to segment color or gray-value images into regions of different structure identified by high-dimensional features, such as local spectral histograms (for Texture) and localized Fourier transforms (for Crystals).

List of uploaded results for 'PCA-MS' 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] PCA-MS 72.27 18.33 9.41 4.19 3.92 7.25 6.44 81.13 85.96 91.24 14.04 1.59 87.08 81.84 4.45 87.81 8.33 5.61 21.00 18.28 85.96 81.30 82.16 9.06 85.54 4.31 13.22 84.78 5.88 81.62 75.30 85.25 85.71 88.20 84.18 3.98