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Smoothing an image under the curvature of its level sets (Mean curvature flow), create contour plot of image data were used. To do that, a high level function (evolve2D) was used that can utilize any combination of: 1) a force in ...
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Smoothing an image under the curvature of its level sets (Mean curvature flow), create contour plot of image data were used. To do that, a high level function (evolve2D) was used that can utilize any combination of: 1) a force in the normal direction to the curve, 2) a curvature-based force, and 3) evolution under the influence of an external vector field. This function takes an input, evolves it N iterations and returns the result. So; in this paper, all level sets of the image are smoothed under curvature-based forces and the level sets of the original image are calculated. Then the image was smoothed after 25-50 iterations of smoothing, and then we calculated its corresponding level sets. Also in this paper the Matlab function IMCONTOUR (img) was used to draw a contour plot of the intensity image ( img). The method gives us accurately the level sets of our image before and after smoothing. The processing time for different processed images was calculated. Finally the results were compared with active contour method and levelset without re-initialization method.
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In this paper, we present a fast and simple discrete approach for active contours. It is based on discrete contour evolution, which operates on the boundary of digital shape, by iterative growth processes on the boundary of the sh...
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In this paper, we present a fast and simple discrete approach for active contours. It is based on discrete contour evolution, which operates on the boundary of digital shape, by iterative growth processes on the boundary of the shape. We consider a cure to be the boundary of a discrete shape. We attach at each point of the boundary a cost function and deform this shape according to that cost function. The method presents some advantages. It is a discrete method which takes an implicit representation and uses discrete algorithm with a simple data structure.
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Ultrasonic machining is a practical process for advanced ceramic machining. Usually, ceramics with complex surfaces are machined with two common ultrasonic assisted contour machining methods, which may be classified as surface/poi...
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Ultrasonic machining is a practical process for advanced ceramic machining. Usually, ceramics with complex surfaces are machined with two common ultrasonic assisted contour machining methods, which may be classified as surface/point contact machining mode. While these methods are not suitable to machine some complex surfaces such as blade surface, so an ultrasonic assisted contour machining method using a simple shaped diamond grinding wheel to machine ceramic blade surface is presented, which is named as Numerical Control-Contour Evolution Ultrasonic Assisted Grinding (NC-CEUAG) method. In the NC-CEUAG process, the contour evolution motion of the grinding wheel is controlled by the NC system and the blade surface is the enveloping surface formed by the grinding wheel' cutting edges when they cut into the ceramic specimen. In this paper, the relative motion between the grinding wheel and the specimen in the process of NC-CEUAG ceramic blade surface is analyzed. The mathematical models of ruled surfaces are constructed. The ceramic blades with ruled surface are machined with selected machining parameters on the retrofitting NC-CEUAG machine tool.
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In this paper we prove a well known contour evolution technique can result in inconsistent non-simple or self-intersecting polygons. This technique is used as a pre-processing step to a number of shape matching and part-decomposit...
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In this paper we prove a well known contour evolution technique can result in inconsistent non-simple or self-intersecting polygons. This technique is used as a pre-processing step to a number of shape matching and part-decomposition strategies which are only well-defined for simple polygons. We analyze one such class of shape matching strategies, which use a highly cited method based on turning-functions to determine similarity. We prove that due to the possibility of self-intersecting polygons these methods are not well-defined. A simple alteration to the original contour evolution technique, which ensures the evolution of a consistent simple polygon, is proposed. This technique only alters the result slightly relative to the original evolution technique and therefore maintains the property of suitable shape evolution.
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Depending on implementation, active contours have been classified as geometric or parametric active contours. Parametric contours, irrespective of representation, are known to suffer from the problem of irregular bunching and spa...
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Depending on implementation, active contours have been classified as geometric or parametric active contours. Parametric contours, irrespective of representation, are known to suffer from the problem of irregular bunching and spacing out of curve points during the curve evolution. In a spline-based implementation of active contours, this leads to occasional formation of loops locally, and subsequently the curve blows up due to instabilities. In this paper, we analyze the reason for this problem and propose a solution to alleviate the same. We propose an ordinary differential equation (ODE) for controlling the curve parametrization during evolution by including a tangential force. We show that the solution of the proposed ODE is bounded. We demonstrate the effectiveness of the proposed method for segmentation and tracking tasks on closed as well as open contours.
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Background/PurposeComputer-aided diagnosis of skin cancer requires accurate lesion segmentation, which must overcome noise such as hair, skin color variations, and ambient light variability.
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Though various image segmentation techniques have been developed, it is still a very challenging task to design a robust and efficient algorithm to segment (noisy, blurred or even discontinuous edged) images having high intensity ...
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Though various image segmentation techniques have been developed, it is still a very challenging task to design a robust and efficient algorithm to segment (noisy, blurred or even discontinuous edged) images having high intensity inhomogeneity or non-homogeneity. In this article, a robust fuzzy energy based active contour, using both global and local information, is proposed to detect objects in a given image based on curve evolution. The local energy is generated by considering both local spatial and gray level/color information. The proposed model can better deal with images having high intensity inhomogeneity or non-homogeneity, noise and blurred boundary or discontinuous edges by incorporating local energy term in the proposed active contour energy function. The global energy term is used to avoid unsatisfactory results due to bad initialization. In this article, instead of solving the Euler-Lagrange equation, a level set based optimization is used for the convergence. We show a realization of the proposed method and demonstrate its performance (both qualitatively and quantitatively) with respect to state-of-the-art techniques on several images having such kind of artifacts. Analysis of results concludes that the proposed method can detect objects from given images in a better way than the existing ones. (C) 2016 Elsevier B.V. All rights reserved.
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In this work, we present an approach for implementing an implicit scheme for the numerical solution of the partial differential equation of the evolution of an active contour/surface. The proposed scheme is applicable to any varia...
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In this work, we present an approach for implementing an implicit scheme for the numerical solution of the partial differential equation of the evolution of an active contour/surface. The proposed scheme is applicable to any variant of the traditional active contour (AC), irrespectively of the calculation of the image-based force field and it is readily applicable to explicitly parameterized active surfaces (AS). The proposed approach is formulated as an infinite impulse response (IIR) filtering of the coordinates of the contour/surface points. The poles of the filter are determined by the parameters controlling the shape of the active contour/surface. We show that the proposed IIR-based implicit evolution scheme has very low complexity. Furthermore, the proposed scheme is numerically stable, thus it allows the convergence of the AC/AS with significantly fewer iterations than the explicit evolution scheme. It also possesses the separability property along the two parameters of the AS, thus it may be applied to deformable surfaces, without the need to store and invert large sparse matrices. We implemented the proposed IIR-based implicit evolution scheme in the Vector Field Convolution (VFC) AC/AS using synthetic and clinical volumetric data. We compared the segmentation results with those of the explicit AC/AS evolution, in terms of accuracy and efficiency. Results show that the VFC AC/AS with the proposed IIR-based implicit evolution scheme achieves the same segmentation results with the explicit scheme, with considerably less computation time.
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Polar active contours have proven to be a powerful segmentation method for many medical as well as other computer vision applications, such as interactive image segmentation or tracking. Inspired by recent work on Sobolev active c...
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Polar active contours have proven to be a powerful segmentation method for many medical as well as other computer vision applications, such as interactive image segmentation or tracking. Inspired by recent work on Sobolev active contours we derive a Sobolev-type function space for polar curves, which is endowed with a metric that allows us to favor origin translations and scale changes over smooth deformations of the curve. The resulting translation, scale, and deformation weighted polar active contours inherit the coarse-to-fine behavior of Sobolev active contours as well as their robustness to local minima and are thus very useful for many medical applications, such as cross-sectional vessel segmentation, aneurysm analysis, or cell tracking.
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摘要 :
Polar active contours have proven to be a powerful segmentation method for many medical as well as other computer vision applications, such as interactive image segmentation or tracking. Inspired by recent work on Sobolev active c...
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Polar active contours have proven to be a powerful segmentation method for many medical as well as other computer vision applications, such as interactive image segmentation or tracking. Inspired by recent work on Sobolev active contours we derive a Sobolev-type function space for polar curves, which is endowed with a metric that allows us to favor origin translations and scale changes over smooth deformations of the curve. The resulting translation, scale, and deformation weighted polar active contours inherit the coarse-to-fine behavior of Sobolev active contours as well as their robustness to local minima and are thus very useful for many medical applications, such as cross-sectional vessel segmentation, aneurysm analysis, or cell tracking.
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