Fast probabilistic snake algorithm

TL;DR

This paper introduces a fast and accurate probabilistic active contour algorithm for image segmentation, inspired by prior probabilistic snake models, and adaptable to various applications.

Contribution

It presents a novel probabilistic snake algorithm that is both computationally efficient and highly accurate, expanding the applicability of active contour models.

Findings

Algorithm is very fast and highly accurate

Easily adaptable to specific applications

Based on probabilistic approach inspired by prior work

Abstract

Few people use the probability theory in order to achieve image segmentation with snake models. In this article, we are presenting an active contour algorithm based on a probability approach inspired by A. Blake work and P. R{\'e}fr{\'e}gier's team research in France. Our algorithm, both very fast and highly accurate as far as contour description is concerned, is easily adaptable to any specific application.