A Continuous Shape Prior for MRF-Based Segmentation
نویسنده
چکیده
The competition between discrete (MRF based) and continuous (PDE based) formulations has a very long history, especially in context of segmentation. Obviously, both have their advantages and drawbacks. Therefore the choice of a discrete or continuous framework is often driven by a particular application or (even more often) by personal preferences of a particular researcher. In this work we present a model for binary segmentation, where discrete and continuous parts are combined in a well founded and simple way. We discuss the properties of the proposed model, give a basic inference algorithm and validate it on a benchmark database.
منابع مشابه
Cluster-Based Image Segmentation Using Fuzzy Markov Random Field
Image segmentation is an important task in image processing and computer vision which attract many researchers attention. There are a couple of information sets pixels in an image: statistical and structural information which refer to the feature value of pixel data and local correlation of pixel data, respectively. Markov random field (MRF) is a tool for modeling statistical and structural inf...
متن کاملA shape prior-based MRF model for 3D masseter muscle segmentation
Medical image segmentation is generally an ill-posed problem that can only be solved by incorporating prior knowledge. The ambiguities arise due to the presence of noise, weak edges, imaging artifacts, inhomogeneous interior and adjacent anatomical structures having similar intensity profile as the target structure. In this paper we propose a novel approach to segment the masseter muscle using ...
متن کاملCombining Shape Priors and MRF-Segmentation
Wepropose a combination of shape prior models with Markov Random Fields. The model allows to integrate multiple shape priors and appearance models into MRF-models for segmentation. We discuss a recognition task and introduce a general learning scheme. Both tasks are solved in the scope of the model and verified experimentally.
متن کاملTum Technische Universität München
We propose a general class of label configuration priors for continuous multi-label optimization problems. In contrast to MRF-based approaches, the proposed framework unifies label configuration energies such as minimum description length priors, co-occurrence priors and hierarchical label cost priors. Moreover, it does not require any preprocessing in terms of super-pixel estimation. All probl...
متن کاملCurvature Prior for MRF-Based Segmentation and Shape Inpainting
Most image labeling problems such as segmentation and image reconstruction are fundamentally ill-posed and suffer from ambiguities and noise. Higher order image priors encode high level structural dependencies between pixels and are key to overcoming these problems. However, these priors in general lead to computationally intractable models. This paper addresses the problem of discovering compa...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2013