A proposed normalized B-spline density estimator and it application in unsupervised statistical image segmentation
Atizez Hadrich, Mourad Zribi, Afif Masmoudi · 2012
This paper describes a new density estimation method of distribution mixture based on B-spline density estimator with application to unsupervised statistical image segmentation. The proposed normalized B-spline density estimator overcomes the situation where the orthogonal series density estimator is not a probability density function (pdf). This estimator is competitive and bears a striking resemblance to the orthogonal series density estimator. We introduce the proposed estimator for estimating the mixture density. The application of suggested approach in unsupervised statistical image segmentation does not make heavy assumptions on the shape of the gray level image pixels distribution.