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].
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