Unsupervised textured image segmentation using 2-D quarter plane autoregressive model with four prediction supports

In a former work, Akaike IC (AIC) and a 2-D first quarter plane autoregressive model with fixed (1, 1) order were used. In order to estimate the number of textures and the model orders, we propose to use Bayesian IC (BIC) and ϕβIC. Moreover, during the two stages of the algorithm, the four quarter planes prediction supports have been used in order to solve problems at image and region boundaries. The results are given on images containing synthetic and natural textures.