A new way of gauging the accuracy of radiowave propagation models is presented. The prediction models used are the parabolic equation (PE) and a new slope-uniform theory of diffraction (slope-UTD). The results from these models applied to a terrain database are compared to experimental data from the University of Aalborg, Denmark. This comparison is enabled by using newly defined hit rate metrics. Hit rate metrics are obtained by comparing the predicted and measured availability on a point-by-point basis at a given path loss threshold. The hit rate metric is complementary to first order statistics such as mean and standard deviation of error, in determining the accuracy of a model.

Generalized cylinders provide a compact representation for modeling many components of natural objects as well as a great variety of human-made industrial parts. This paper presents a new approach to modeling generalized cylinders based on cross-sectional curves defined using Fourier descriptors. This modeling is based on contour interpolation and is implemented using a subdivision technique. The definition of generalized cylinders uses a three-dimensional trajectory which provides an adequate control for the smoothness of bend with a small number of parameters and includes the orientation of each cross-section (i.e, the local coordinate system) in the interpolation framework. Fourier representations of cross-sectional curves are obtained from contours in digital images, and corresponding points are identified by considering angular and arc-length parametrizations. Changes in cross-section shape through the trajectory are performed using Fourier morphing. The technique proposed provides a comprehensive definition that allows the modeling of a wide variety of shapes, while maintaining a compact characterization to facilitate the description of shapes and displays.

The generalised Hough transform extracts arbitrary objects by using a non-analytic model shape representation obtained from gradient direction information. The main drawback of this technique is the excessive computational burden because of the four-dimensional parameter space required when orientation and scale are unknown. We present a novel representation of a model shape defined by the geometric relationship given by the position of a collection of edge points. This representation avoids errors due to unreliable gradient direction information and is used to reduce the computational requirements by decomposing the four-dimensional parameter space into two two-dimensional sub-spaces. Experimental results show the efficacy of the new technique for extracting shapes from synthetic and real images.

In this paper we present a novel formulation for the extraction of arbitrary shapes in model-based recognition. The formulation is based on the mapping defined in the Hough transform. We develop this mapping for the analytic representation of a shape characterised by a Fourier parameterisation. Edge direction information is included in the formulation as a way of reducing the computational requirements in the extraction process. The proposed approach extends the analytic formulation of the Hough transform to arbitrary shapes. An analytic representation provides a compact and extensive coverage of a shape which leads to an accurate and efficient evidence accumulation process. Experimental results show that the new approach can handle noise and occlusion in synthetic and real images.

This paper presents how morphological transformations can be related to representations of a set on different lattices. A hierarchical definition of structuring element conveys to a class of multigrid transformations /spl Psi//sub k/ that handle changes on discrete representations of regions. The transformations correspond to upward and downward processes in a hierarchical structure. Based on multigrid transformations, a method to delineate not-perfectly-isolated objects in an nxn image requiring O(log n) time is presented. The approach considers grey level regions as sets and processes through a pyramid to carry out geometric manipulations. Extending the concept of boundary to cope with hierarchical representations of a set, a second method which identifies the boundaries in an image is discussed.>