Tracking deformable objects in the plane using an active contour model

Leymarie, Frederic Fol; Levine, Martin D.

doi:10.1109/34.216733

Cited by 500 publications

(244 citation statements)

References 27 publications

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“…The internal and external forces are defined so that the snake will conform to an object boundary or other desired features within an image. Snakes are widely used in many applications, including edge detection [9], shape modeling [7,12,13], segmentation [2,6,10] and motion tracking [10,14].…”

Section: Introductionmentioning

confidence: 99%

Generalized gradient vector flow external forces for active contours

1998

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Active contours, or snakes, are used extensively in computer vision and image processing applications, particularly to locate object boundaries. A new type of external force for active contours, called gradient vector flow (GVF) was introduced recently to address problems associated with initialization and poor convergence to boundary concavities. GVF is computed as a diffusion of the gradient vectors of a gray-level or binary edge map derived from the image. In this paper, we generalize the GVF formulation to include two spatially varying weighting functions. This improves active contour convergence to long, thin boundary indentations, while maintaining other desirable properties of GVF, such as an extended capture range. The original GVF is a special case of this new generalized GVF (GGVF) model. An error analysis for active contour results on simulated test images is also presented.1998 Elsevier Science B.V. All rights reserved. ZusammenfassungAktive Umrisse, oder Schlangen, werden vielfach in Computervision-und Bildverarbeitungs-Anwendungen benutzt, um insbesondere Objektgrenzen zu lokalisieren. Ein neuer Typ a¨u{erer Kra¨fte fu¨r aktive Umrisse, Gradient »ector Flow (GVF) genannt, wurde ku¨rzlich eingefu¨hrt, um Probleme anzusprechen, die mit Initialisierung und schlechter Konvergenz zu Grenzkonkavita¨ten zusammenha¨ngen. GVF wird als eine Diffusion des Gradientenvektors einer Graustufen-oder 'Binary Edge'-Karte berechnet, die aus dem Bild gewonnen werden. In diesem Artikel verallgemeinern wir die GVF Formulierung, so da{ zwei ra¨umlich variierende Gewichtsfunktionen eingeschlossen werden. Dies verbessert die Konvergenz aktiver Umrisse zu langen, du¨nnen Grenzmarkierungen, wa¨hrend andere wu¨nschenswerte Eigenschaften des GVF, wie erweiterter Einfangbereich, erhalten bleiben. Das urspru¨ngliche GVF ist ein Spezialfall dieses neuen verallgemeinerten GVF (GGVF) Modells. Eins Fehleranalyse von Ergebnissen aktiver Umrisse mit simulierten Testbildern wird ebenfalls pra¨sentiert.1998 Elsevier Science B.V. All rights reserved. contours actifs, appele`flux de vecteurs gradients (FVG) a e´te´introduit re´cemment pour traiter les proble´mes associe´s a`l'initialisation et la faible convergence vers des concavite´s dans les contours. Le FVG est calcule´comme une diffusion des vecteurs gradients d'une carte des contours d'une image en niveaux de gris ou binaire. Dans cet article, nous ge´ne´ralisons la formulation du FVG pour y inclure deux fonctions de poids a`variation spatiale. Ceci ame´liore la convergence des contours actifs vers les indentations de contours fines et longues, tout en maintenant les autres proprie´te´s inte´ressantes des FVG comme la plage de capture e´tendue. Les FVG originaux sont un cas particulier des mode`les de FVG ge´ne´ralise´s. Une analyse de l'erreur des re´sultats de contours actifs sur des images de test synthe´tiques est aussi pre´sente´e.

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Section: Introductionmentioning

confidence: 99%

Generalized gradient vector flow external forces for active contours

1998

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“…However, they manifest certain well known limitations that significantly restrict the scope of their applications. One limitation is the lack of appropriate long range forces [4]. The commonly used gradient force operates over a short range.…”

Section: Introductionmentioning

confidence: 99%

Smoothness-based forces for deformable models: a long-range force and a corner fitting force

Zhang

Braun

2003

Computers in Biology and Medicine

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Deformable models, originally proposed by , have been widely used in medical image segmentation. However, they manifest two well known limitations: the lack of an appropriate long range force to drive the model surface towards the object boundary and poor performance at high curvature boundaries (such as corners) due to the models' intrinsic smoothness constraint. In this paper, a new smoothness force with local control is proposed. The local control is used to devise a long range force, referred to as the self-zoom force, and a corner fitting force. The self-zoom force enables the model surface to expand and shrink without a limit in range. The corner fitting force propels the model surface to fit high curvature boundaries. Experiments demonstrate that the model surface is driven to the object boundary by the new forces even if the initial estimate is not close and the object is nonconvex or has a high local curvature.

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“…Here, we will demonstrate most of the properties of GVF using (12). When necessary to contrast their performance, we will refer to the GVF using (12) and (13) as GVF-I and GVF-II respectively.…”

Section: B ¡ Q ¥ As the Equilibrium Solution To The Following Vector mentioning

confidence: 99%

“…The internal and external forces are defined so that the model will conform to an object boundary or other desired features within an image. Deformable models are widely used in many applications, including edge detection [10,5], shape modeling [18,15], segmentation [12,8], and motion tracking [19,12].…”

Section: Introductionmentioning

confidence: 99%

Gradient Vector Flow Deformable Models

2009

Handbook of Medical Image Processing and Analysis

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-Deformable models are used extensively in image processing, computer vision, and medical imaging applications, particularly to delineate object boundaries. Problems associated with initialization and poor convergence to boundary concavities, however, have limited their utility. This chapter presents an external force for deformable models, largely solving both problems. This external force, which we call gradient vector flow (GVF), is computed as a diffusion of the gradient vectors of a gray-level or binary edge map derived from the image. It differs fundamentally from traditional deformable model external forces in that it cannot be written as the negative gradient of a potential function, and the corresponding deformable model is formulated directly from a dynamic force equation rather than a energy minimization formulation.Using several two-dimensional examples and two three-dimensional examples, we show that GVF has a large capture range and is able to move deformable models into boundary concavities.

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Tracking deformable objects in the plane using an active contour model

Cited by 500 publications

References 27 publications

Generalized gradient vector flow external forces for active contours

Generalized gradient vector flow external forces for active contours

Smoothness-based forces for deformable models: a long-range force and a corner fitting force

Gradient Vector Flow Deformable Models

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