A new active contour model for finding and mapping the outer cortex in brain images is developed. A cross-section of the brain cortex is modeled as a ribbon, and a constant speed mapping of its spine is sought. A variational formulation, an associated force balance condition, and a numerical approach are proposed to achieve this goal. The primary difference between this formulation and that of snakes is in the specification of the external force acting on the active contour. A study of the uniqueness and fidelity of solutions is made through convexity and frequency domain analyses, and a criterion for selection of the regularization coefficient is developed. Examples demonstrating the performance of this method on simulated and real data are provided.

Shape modeling is an important constituent of computer vision as well as computer graphics research. Shape models aid the tasks of object representation and recognition. This paper presents a new approach to shape modeling which retains the most attractive features of existing methods, and overcomes their prominent limitations. Our technique can be applied to model arbitrarily complex shapes, which include shapes with significant protrusions, and to situations where no a priori assumption about the object's topology is made. A single instance of our model, when presented with an image having more than one object of interest, has the ability to split freely to represent each object. This method is based on the ideas developed by Osher & Sethian to model propagating solid/liquid interfaces with curvature-dependent speeds. The interface (front) is a closed, nonintersecting, hypersurface flowing along its gradient field with constant speed or a speed that depends on the curvature...

Abstract. We present anovel technique for the automatic adaptation of a deformable model's elastic parameters within a Kalman lter framework for shape estimation applications. The novelty of the technique is that the model's elastic parameters are not constant, but time varying. The model for the elastic parameter variation depends on the local error of t and the rate of change of the error of t. By augmenting the state equations of an extended Kalman lter to incorporate these additional variables and take into account the noise in the data, we are able to signi cantly improve the quality of the shape estimation. Therefore, the model's elastic parameters are initialized always to the same value and they subsequently modi ed depending on the data and the noise distribution. In addition, we demonstrate how this technique can be parallelized in order to increase its e ciency. We present several experiments to demonstrate the e ectiveness of our method. 1

This paper is an attempt to review the state-of-the-art cortical segmentation techniques in 2-D and 3-D using brain magnetic resonance imaging (MRI), their applications and new challenges

Figure-Ground segmentation is a fundamental problem in computer vision. The main difficulty is the integration of low-level, pixel-based local image features to obtain global objectbased descriptions. Active contours in the form of snakes, balloons, and level-set modeling techniques have been proposed that satisfactorily address this question for certain applications. However, these methods require manual initialization, do not always perform well near sharp protrusions or indentations, or often cross gaps. We propose an approach inspired by these methods and a shock-based representation of shape in terms of parts, protrusions, and bends. In this representation parts are related to fourth order shocks. Since initially it is not clear where the objects or their parts are, parts are hypothesized in the form of fourth order shocks randomly initialized in homogeneous areas of images. These shocks then form evolving contours, or bubbles, which grow, shrink, merge, split and disappear to cap...

1 In this paper we present a method for 3-D reconstruction of human bodies with application in CAD systems for garment design. The reconstruction scheme uses image information from several arbitrary views and deformable superquadrics as the models of the body parts. Two visual cues are used: occluding contours and stereo (possibly aided by projected patterns) . Our preliminary experiments show that the reconstruction is more complete than in purely stereo or structured light based methods and more precise than the reconstruction from occluding contours only. From the reconstructed human body, the body measurements can be taken automatically, and used in garment design. We give an example of draping of virtual garment over the photo-realistic 3D model of the imaged human. One can easily envision the use of the described algorithms in the development of custom-fit garment retail software over the Internet, which would include the possibility of trying the garment on in virtual reality. ...

Monitoring the growth of farmed fish is an important task which is currently difficult to carry out. An underwater stereo image analysis technique offers the potential for estimating key dimensions of free-swimming fish, from which the fish mass can be estimated. This paper describes the development of a three-dimensional point distribution model to capture the typical shape and variability of salmon viewed from the side. The model was fitted to stereo images of test fish by minimizing an energy function, which was based on probability distributions. The minimization was an iterated two-step method in which edges were selected for magnitude, direction, and proximity to the model, and the model was then fitted to the edges. A search strategy for locating the edges in 3D was devised. The model is tested on two image sets. In the first set 19 of the 26 fish are located in spite of their variable appearance and the presence of neighboring fish. In the second set the measurements made on 11 images of fish are compared with manual measurements of the fish dimensions and show an average error in length estimation of 5%. c ○ 2000 Academic Press Key Words: model-based image processing; stereo; measurement; deformable objects.

This paper develops a formalism by which an estimate for the upper and lower bounds on the elasticity parameters for a snake can be obtained. Objects different in size and shape give rise to different bounds. The bounds can be obtained by analysing the shape of the object of interest. Experiments on synthetic images show a good correlation between the estimated behavior of the snake and the behavior actually observed. Experiments on real x-ray images show that parameters for optimal segmentation lie within the estimated bounds. Keywords: snakes, parameters of elasticity, model-based segmentation. 1 Introduction Snakes, introduced by Kass et al.[8], can be characterised as a tool for performing model based segmentation. In resent years snakes have attracted much attention due to several advantages compared to traditional segmentation techniques compared to other techniques to find contours of an object in images [9]. One of them is that the contour can be found even in noisy images and...

In this paper we present a new one-dimensional shape matching technique based on elastic deformation of a model or template. Deformations of the given template are introduced as a way to improve the matching with the image data. A trade-off is made between the amount of deformation and a figure of merit that accounts for the match. This approach yields a new optimization functional so that the optimal match for a given shape is expressed as a solution of a variational problem. Numerical methods are presented to solve the resulting system of ordinary differential equations. This new matching technique can be used for pattern recognition applications where binarizing images s hard or impossible. An illustration of the nre shape matching method is shown for several optical character recognition problems. 1 Introduction In this paper, we present a new shape matching technique based on the deformation of a one-dimensional "sketch" of the shape to be matched. The sketch (or template) can ...

. This paper develops a formalism by which an estimate for the upper and lower bounds for the elasticity parameters for a snake can be obtained. Objects different in size and shape give rise to different bounds. The bounds can be obtained based on an analysis of the shape of the object of interest. Experiments on synthetic images show a good correlation between the estimated behaviour of the snake and the actually observed. Experiments on real X-ray images show that the parameters for optimal segmentation lie within the estimated bounds. Keywords: snakes, elasticity parameters, segmentation. 1 Introduction Snakes, introduced by Kass et al.[2], have several advantages compared to traditional segmentation techniques specially in case of noisy images and partly occluded objects [1, 2]. They are a model-based technique since ways exist to incorporate information about the object of interest into the snake formalism. An initial snake can be defined specifying it in accordance with...