Multiscale Texture Segmentation based on Image Spectrum

Texture Segmentation is a multiscale task because both the global and the local information of an image are required. The Multiscale Texture Segmentation (MTS) employs the Boltzmann probability to determine the change of state P (state) of simulated annealing. This paper presents three modifications of MTS: first, the first two items of the Maclaurin series of the Boltzmann probability is used to determine P (state). Second, the energy increment of P (state) is re-defined to provide a more balanced encouragement of the splitting and merging of a leaf node of the quad-tree used to represent the image. Third, the horizontal and the vertical moments of an image spectrum is used to characterise four natural textures.