The overall objective in defining feature space is to reduce the dimensionality of pattern space yet maintaining discriminatory power for classification and invariant description. To meet this objective, in the context of ear biometrics, a novel force field transformation has been developed in which the image is treated as an array of Gaussian attractors that act as the source of a force field. The directional properties of the force field are exploited to automatically locate the extrema of a small number of potential energy wells and associated potential channels. These form the basis of the ear description. This has been applied to a small database of ears and initial results show that the new approach has suitable performance attributes and shows promising results in automatic ear recognition.

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Active Contour (or Snake) Model is recognized as one of the efficient tools for 2D/3D image segmentation. However, traditional snake models prove to be limited in several aspects. The present paper describes a set of diffusion equations applied to image gradient vectors, yielding a vector field over the image domain. The obtained vector field provides the Snake Model an external force as well as an automatic way to generate the initial contours. Finally a region merging technique is employed to further improve the segmentation results.

In this paper a method for the objective assessment of burn scars is proposed. The quantitative measures developed in this research provide an objective way to calculate elastic properties of burn scars relative to the surrounding areas. The approach combines range data and the mechanics and motion dynamics of human tissues. Active contours are employed to locate regions of interest and to find displacements of feature points using automatically established correspondences. Changes in strain distribution over time are evaluated. Given images at two time instances and their corresponding features, the finite element method is used to synthesize strain distributions of the underlying tissues. This results in a physically based framework for motion and strain analysis. Relative elasticity of the burn scar is then recovered using iterative descent search for the best nonlinear finite element model that approximates stretching behavior of the region containing the burn scar. The results from the skin elasticity experiments illustrate the ability to objectively detect differences in elasticity between normal and abnormal tissue. These estimated differences in elasticity are correlated against the subjective judgments of physicians that are presently the practice.

In recent years, the field of active contour based image segmentation has seen the emergence of two competing approaches. The first and oldest approach represents active contours in an explicit (or parametric) manner corresponding to the Lagrangian formulation. The second approach represents active contours in an implicit manner corresponding to the Eulerian framework. After comparing these two approaches, we describe several new topological and geometrical constraints applied to parametric active contours in order to combine the advantages of these two contour representations. This paper proposes a framework for handling parametric active contours shape and topology in a more intuitive manner. More precisely, the following three algorithms are introduced: 1. Metric and Shape Control: a new internal force expression allows to regularize both vertex spacing and vertex smoothness. The smoothness constraint is enforced without producing any shrinkage. 2. Contour Resolution Control: the to...

analysis of ultrasound images is to develop taskspecific systems, which allows assumptions about the structures under consideration. In this paper, we introduce a new ultrasound contour tracker, tonTrak, for the mid-sagital and coronal ultrasound image sequences of the human tongue. tonTrak makes assumptions about the ultrasound modality and possible positions of the tongue inside the vocal tract. It also provides intuitive and user friendly ways of interaction with the user, a crucial feature for a medical software system. tonTrak is fundamentally di#erent from the previous tongue tracking systems. It is based on the minimization of a deformable dual-mesh energy using a novel gradient descent technique that provides a way of e#ciently imposing both spatial and temporal constraints at the same time. This new energy optimization method does not need contour initialization and it is robust against local minima.

Application of dynamic programming to the deformable contours has many advantages, such as guaranteed optimality and numerical stability. However, long execution times of these methods almost always force researchers to use dynamic programming in combination with multiresolution methods. Multiresolution methods shorten the execution time by subsampling the original images after an application of a smoothing filter. However, this speedup comes at the expense of contour optimality due to the loss of details in the decreased resolution. In this paper, we present a new multi-level framework for deformable contour optimization, which can achieve faster optimization times and performs better than current multiresolution methods. To form the new levels, this method uses a very efficient algorithm to segment the original images with respect to the deformable contour external energy instead of subsampling. An exhaustive search on these segments is carried out by dynamic programming. A novel gr...

In our previous work we used finite element models to determine nonrigid motion parameters and recover unknown local properties of objects given correspondence data recovered with snakes or other tracking models. In this paper we present a novel multiscale approach to recovery of nonrigid motion from sequences of registered intensity and range images. The main idea of our approach is that a finite element (FEM) model incorporating material properties of the object can naturally handle both registration and deformation modeling using a single model-driving strategy. The method includes a multiscale iterative algorithm based on analysis of the undirected Hausdorff distance to recover correspondences. The method is evaluated with respect to speed and accuracy. Noise sensitivity issues are addressed. Advantages of the proposed approach are demonstrated using man-made elastic materials and human skin motion. Experiments with regular grid features are used for performance comparison with a conventional approach (separate snakes and FEM models). It is shown, however, that the new method does not require a sampling/correspondence template and can adapt the model to available object features. Usefulness of the method is presented not only in the context of tracking and motion analysis, but also for a burn scar detection application.

We present results for an active contour that finds the pupil-iris border in slit lamp images of the eye. Preprocessing involves producing a variance image from the original image and then locating the annulus, of a given size, which has the lowest mean variance. The centre of this annulus falls inside the pupil, giving a starting position for a discrete circular active contour (DCAC). The DCAC is moved under the influence of two forces—external and internal. The external force is based on the grey-scales immediately inside and outside of the contour, at each vertex, in both the original and variance images and pushes the vertices inwards. The internal force acts to move the contour towards a perfect polygon, larger than the current polygon. Repeated trials with decreasing values of are performed until equilibrium is reached between the two forces and the pupil/iris border has been found. 1.

In this paper, a new automatic contour tracking system, EdgeTrak, for the ultrasound image sequences of human tongue is presented. The images are produced by a Head and Transducer Support System (HATS) [14]. The noise and unrelated high-contrast edges in ultrasound images make it very difficult to automatically detect the correct tongue surfaces. In our tracking system, a novel active contour model is developed. Unlike the classical active contour models which only use gradient of the image as the image force, the proposed model incorporates the edge gradient and intensity information in local regions around each snake element. Different from other active contour models that use homogeneity of intensity in a region as the constraint and thus are only applied to closed contours [8], the proposed model applies local region information to open contours and can be used to track partial tongue surfaces in ultrasound images. The contour orientation is also taken into account so that any unnecessary edges in ultrasound images will be discarded. Dynamic programming is used as the optimization method in our 1 2 implementation. The proposed active contour model has been applied to human tongue tracking and its robustness and accuracy have been verified by quantitative comparisons analysis to the tracking by speech scientists. 1