Colour and texture segmentation using wavelet frame analysis, deterministic relaxation, and fast marching algorithms

Luminance, colour, and/or texture features may be used, either alone or in combination, for segmentation. In this paper luminance and colour classes are described using the corresponding empirical probability distributions. For texture analysis and characterisation a multichannel scale/orientation decomposition is performed using wavelet frame analysis. Knowing only the number of the different classes of the image, regions of homogeneous patterns are identified. On these regions the features characterising and describing the different classes are estimated. Two labelling algorithms are proposed. The first, a deterministic relaxation algorithm using a quadratic distance measure, yields the labelling of pixels to the different colour–texture classes. The second is a new Multi-label Fast Marching algorithm utilising a level set boundary determination.

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