Parametric Control in a Region-Based Coupled MRF Model with Phase Dynamics for Coarse Image Region Segmentation

Abstract

Towards hardware implementation of real-time visual image processing, we propose a piecewise linear (PWL) approximation of a coupled region-based Markov Random Field (MRF) model with hidden phase variables for coarse image region segmentation. We introduce PWL functions into update equations of the region-based model, in order to make it easy to control parameters that determine the balance between image segmentation and smoothing, as well as to make it efficient for hardware implementation. We can tune filtering properties of our model by controlling the parameters of the PWL functions in applications to a task of coarse image region segmentation. Finally, we demonstrate that closed regions in input images can be represented by phase variables in multi-scale.