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].
test's HGS version E/W/C |
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f1: 0 f2: 0 f3: 0 f4: 0 |
HGS algorithm The HGS unsupervised segmenter is based on the integration of the Gabor filters with the measurement of color. Single versions of the method differ in their photometric invariance power (HGS-E no invariance, HGS-W low, HGS-C full invariance). The spatial frequency is measured by sampling the incoming image with a shifted Gaussian in the spatial frequency domain, and the color is measured by sampling the signal with Gaussian in wavelength domain. The method implies that the color-texture is measured in the wavelength-Fourier domain. The measurement filter in this domain boils down to a 3D Gaussian, representing a Gabor-Gaussian in the spatial-color domain. List of uploaded results for 'HGS' algorithm
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