DocumentCode :
1383725
Title :
The EM/MPM algorithm for segmentation of textured images: analysis and further experimental results
Author :
Comer, Mary L. ; Delp, Edward J.
Author_Institution :
Thomson Consumer Electron., Indianapolis, IN, USA
Volume :
9
Issue :
10
fYear :
2000
fDate :
10/1/2000 12:00:00 AM
Firstpage :
1731
Lastpage :
1744
Abstract :
In this paper we present new results relative to the “expectation-maximization/maximization of the posterior marginals” (EM/MPM) algorithm for simultaneous parameter estimation and segmentation of textured images. The EM/MPM algorithm uses a Markov random field model for the pixel class labels and alternately approximates the MPM estimate of the pixel class labels and estimates parameters of the observed image model. The goal of the EM/MPM algorithm is to minimize the expected value of the number of misclassified pixels. We present new theoretical results in this paper which show that the algorithm can be expected to achieve this goal, to the extent that the EM estimates of the model parameters are close to the true values of the model parameters. We also present new experimental results demonstrating the performance of the EM/MPM algorithm
Keywords :
Markov processes; image segmentation; image texture; iterative methods; parameter estimation; EM/MPM algorithm; MPM estimate; Markov random field model; expectation-maximization/maximization of the posterior marginals algorithm; misclassified pixels; parameter estimation; performance; pixel class labels; segmentation; textured images; Algorithm design and analysis; Costs; Image analysis; Image segmentation; Image texture analysis; Markov random fields; Parameter estimation; Pixel; Stochastic processes; Two dimensional displays;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/83.869185
Filename :
869185
Link To Document :
بازگشت