Information fusion for unsupervised image segmentation using stochastic watershed and Hessian matrix

International audienceThis study deals with information fusion for image segmentation. The evidence theory (or the Dempster–Shafertheory) allows the modellisation of uncertainty and imprecision in the information as well as the combination of different sources.Here, this approach is used in an unsupervised framework to combine the stochastic watershed segmentation which providesseveral segmentation results, with a Hessian operator in order to obtain a unique and efficient segmentation. The method istested on natural images from the Berkeley dataset and evaluated using several evaluation metrics. The fusion results surpassthose obtained with stochastic watershed alone