Article

Self-Crossing Detection and Location for Parametric Active Contours

Department of Electrical and Computer Engineering, BostonUniversity, Boston, MA 02115, USA.
IEEE Transactions on Image Processing (Impact Factor: 3.11). 02/2012; 21(7):3150-6. DOI: 10.1109/TIP.2012.2188808
Source: PubMed

ABSTRACT Active contours are very popular tools for video tracking and image segmentation. Parameterized contours are used due to their fast evolution and have become the method of choice in the Sobolev context. Unfortunately, these contours are not easily adaptable to topological changes, and they may sometimes develop undesirable loops, resulting in erroneous results. To solve such topological problems, one needs an algorithm for contour self-crossing detection. We propose a simple methodology via simple techniques from differential topology. The detection is accomplished by inspecting the total net change of a given contour's angle, without point sorting and plane sweeping. We discuss the efficient implementation of the algorithm. We also provide algorithms for locating crossings by angle considerations and by plotting the four-connected lines between the discrete contour points. The proposed algorithms can be added to any parametric active-contour model. We show examples of successful tracking in real-world video sequences by Sobolev active contours and the proposed algorithms and provide ideas for further research.

2 Followers
 · 
143 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: Deformable models are mathematical tools, used in image processing to analyze the shape and movement of real objects due to their ability to emulate physical features such as elasticity, stiffness, mass and damping. In the original approach, parametric models are obtained from the minimization of an energy functional by means of the Euler-Lagrange equatioén. Finite element method is used for spatial discretization. The shape and position of the model is governed by a second-order Partial Differential Equation system, which is obtained by applying the calculus of variations. Subsequent work propose a model formulation defined completely in the frequency domain, by translating the PDE system into the Fourier domain. This new approach offers important computational efficiency and an easier generalization to multidimensional models, since each spectral component of the model is ruled by an independent PDE. This paper reviews the frequency based formulation and analyzes the convergence and stability of these multidimensional parametric deformable models. Results show that the accuracy and speed of convergence depend on the dynamic parameters of the system and the spectrum of the data to be characterized, providing a procedure to speed-up the convergence by an appropriate choice of these parameters.
    Computer Vision and Image Understanding 02/2015; DOI:10.1016/j.cviu.2015.01.009 · 1.36 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Gradient vector flow (GVF) is an effective external force for active contours; however, it suffers from heavy computation load. The virtual electric field (VEF) model, which can be implemented in real time using fast Fourier transform (FFT), has been proposed later as a remedy for the GVF model. In this work, we present an extension of the VEF model, which is referred to as CONvolutional Virtual Electric Field, CONVEF for short. This proposed CONVEF model takes the VEF model as a convolution operation and employs a modified distance in the convolution kernel. The CONVEF model is also closely related to the vector field convolution (VFC) model. Compared with the GVF, VEF and VFC models, the CONVEF model possesses not only some desirable properties of these models, such as enlarged capture range, u-shape concavity convergence, subject contour convergence and initialization insensitivity, but also some other interesting properties such as G-shape concavity convergence, neighboring objects separation, and noise suppression and simultaneously weak edge preserving. Meanwhile, the CONVEF model can also be implemented in real-time by using FFT. Experimental results illustrate these advantages of the CONVEF model on both synthetic and natural images.
    PLoS ONE 10/2014; 9(10):e110032. DOI:10.1371/journal.pone.0110032 · 3.53 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Gallbladder function is routinely assessed using ultrasonographic (USG) examinations. In clinical practice, doctors very often analyse the gallbladder shape when diagnosing selected disorders, e.g. if there are turns or folds of the gallbladder, so extracting its shape from USG images using supporting software can simplify a diagnosis that is often difficult to make. The paper describes two active contour models: the edge-based model and the region-based model making use of a morphological approach, both designed for extracting the gallbladder shape from USG images. The active contour models were applied to USG images without lesions and to those showing specific disease units, namely, anatomical changes like folds and turns of the gallbladder as well as polyps and gallstones. This paper also presents modifications of the edge-based model, such as the method for removing self-crossings and loops or the method of dampening the inflation force which moves nodes if they approach the edge being determined. The user is also able to add a fragment of the approximated edge beyond which neither active contour model will move if this edge is incomplete in the USG image. The modifications of the edge-based model presented here allow more precise results to be obtained when extracting the shape of the gallbladder from USG images than if the morphological model is used.
    Computers in biology and medicine 12/2013; 43(12):2238-55. DOI:10.1016/j.compbiomed.2013.10.009 · 1.48 Impact Factor

Full-text

Download
137 Downloads
Available from
May 28, 2014