SEGMENTATION OF IMAGES BY GRAPH CUT USING KERNEL K_MEANS
Shanmugasundaram Singaravelan, Dhanushkodi Murugan · Asian Journal of Advances in Research · 2021
Introducing a multiregion graph cut image partitioning through kernel mapping of the image data. The proposed function consists of two terms: an original kernel-induced term which evaluates the deviation of the mapped image data within each region from the piecewise constant model and a regularization term expressed as a function of the region indices. Using a common kernel function, the objective functional minimization is carried out by iterations of two consecutive steps: Minimization with respect to the image segmentation by graph cuts. Minimization with respect to the regions parameter through fixed point computation.