Multi-references shape constraint for snakes

Abstract

In this research, we intend to present a new method of snakes with an invariant shape prior. We consider the general case where different templates are available and we have to choose the most suitable ones to define the shape constraint. A new external force is then proposed which is able to take into account several references at the same time with proportional weighting factors. Both a Fourier based shape alignment method and a complete and stable set of shape descriptors are used to ensure invariance and robustness of the prior knowledge to Euclidean transformations. To illustrate the efficiency of our approach, a set of experiments are applied on synthetic and real data. Promising results are obtained and commented.