Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

We present a novel region based level set algorithm. We first model the image histogram with non-parametric mixture of probability density functions(PDFs). The individual densities are estimated using a recently proposed PDF estimation method which relies on a continuous representation of the discrete signals. Prior probabilities are calculated using an inequality constrained least squares method. The log ratio of the posterior probabilities is used to drive the level set evolution. We also take into account the image artifact called the partial volume effect, which is quite important in medical image analysis. Results are presented on natural as well as medical two dimensional images. Visual inspection of our results show the effectiveness of the proposed algorithm. © 2007 IEEE.

Original publication




Conference paper

Publication Date



618 - 622