Title :
An Unsupervised Image Segmentation Using B-Splines Functions
Author :
Hadrich, Atizez ; Zribi, Mourad ; Masmoudi, Afif
Author_Institution :
Lab. of Probability & Stat., Fac. of Sci. of Sfax, Sfax, Tunisia
Abstract :
We propose in this paper an unsupervised Bayesian image segmentation based on non-parametric expectation-maximization (EM) algorithm. The non-parametric aspect comes from the use of the B-spline probability density function (pdf) estimation, which is reduced to the estimation of the parameters of B-splines of the pdf.
Keywords :
Bayes methods; expectation-maximisation algorithm; image segmentation; probability; B-spline functions; B-spline parameter estimation; B-spline probability density function estimation; nonparametric EM algorithm; nonparametric expectation-maximization algorithm; unsupervised Bayesian image segmentation; Bayesian methods; Estimation; Histograms; Image segmentation; Kernel; Probability density function; Splines (mathematics);
Conference_Titel :
Engineering and Technology (S-CET), 2012 Spring Congress on
Conference_Location :
Xian
Print_ISBN :
978-1-4577-1965-3
DOI :
10.1109/SCET.2012.6342064
