Combining Geometric Prior and Statistical Features for Active Contour Segmentation

نویسندگان

  • Muriel Gastaud
  • Michel Barlaud
  • Gilles Aubert
چکیده

This article deals with image and video segmentation using active contours. The proposed variational approachs is based on a criterion combining geometric prior and statistical features computed on the inside region of the contours. The geometric prior involves a free form deformation from a reference contour as opposed to a parametric transformation. Differentiation of this geometric prior criterion is provided. Introducing such a free form deformation has proven to be beneficial for interactive image segmentation. A tracking application where the geometric prior results from the segmentation of the previous frame is presented.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Region-based active contours using geometrical and statistical features for image segmentation

We consider the problem of image segmentation through the minimization of an energy criterion involving both region and boundary functionals. We study the derivation of these functionals using the notion of shape derivative. From the derivative, we deduce the evolution equation of an active contour that will make it evolve towards a minimum of the criterion introduced. We focus on geometric and...

متن کامل

ناحیه‌بندی مرز اندوکارد بطن چپ در تصاویر تشدید مغناطیسی قلبی با شدت روشنایی غیریکنواخت

The stochastic active contour scheme (STACS) is a well-known and frequently-used approach for segmentation of the endocardium boundary in cardiac magnetic resonance (CMR) images. However, it suffers significant difficulties with image inhomogeneity due to using a region-based term based on the global Gaussian probability density functions of the innerouter regions of the active ...

متن کامل

A Variational Model for Object Segmentation Using Boundary Information and Statistical Shape Prior Driven by the Mumford-shah Functional

In this paper, we propose a variational model for object segmentation using the active contour method, a geometric shape prior and the Mumford-Shah functional. We propose an energy functional composed by three terms: the first one is based on image gradient, which detects edges, the second term constrains the active contour to get a shape compatible with a statistical model of the target shape,...

متن کامل

A Variational Model for Object Segmentation Using Boundary Information, Statistical Shape Prior and the Mumford-shah Functional

In this paper, we propose a variational model to segment an object belonging to a given scale space using the active contour method, a geometric shape prior and the Mumford-Shah functional. We define an energy functional composed by three complementary terms. The first one detects object boundaries from image gradients. The second term constrains the active contour to get a shape compatible wit...

متن کامل

Diffusion–Snakes: Combining Statistical Shape Knowledge and Image Information in a Variational Framework

We present a modification of the Mumford–Shah functional and its cartoon limit which allows the incorporation of statistical shape knowledge in a single energy functional. We show segmentation results on artificial and real–world images with and without prior shape information. In the case of occlusion and strongly cluttered background the shape prior significantly improves segmentation. Finall...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2003