A New Algorithm for Image Segmenting by Using SMC and Prior Probability Model
Yang Ming · Dianzi xuebao · 2007
A new adaptive algorithm is proposed by taken advantage of SMC(Sequential Monte Carlo) which have better predictive results under the condition of nonlinear non-Gaussian.The algorithm uses particle filtering to predict an anticipated foreground district for a coming frame.Moreover,it calculates the probability of pixels to be part of background in the coming frame to guide image segmentation.It is a good method to segment image on the setting where the pixel values of foreground similar to the ones of the background by using prior knowledge.This paper uses the probability of pixels to be part of background which is calculated by the average of the predict results of particle filtering and the calculated results of prior probability model to segment image.Experimental results show that the proposed algorithm can reduce the error of the pixels of foreground to be segmented as pixels of background compared with 3σ rule when changes in background occur quickly.