Line-Integral Approach to Computing Impedance Matrix Elements

We present a line-integral approach for computing the impedance-matrix elements in the traditional Rao-Wilton-Glisson formulation of the moment method for electromagnetic problems. The line integral extends over the perimeter of a triangle and can be computed numerically using a Gauss-Legendre quadrature. We present the conversion of the surface integral to a line integral, and we perform calculations where we compare the present method to a surface quadrature approach.     

Scattering by an indentation satisfying a dyadic impedance boundarycondition

We derive a pair of boundary integral equations for the problem of scattering of an electromagnetic wave by an indentation in a perfectly conducting screen. The wall of the indentation obeys a dyadic impedance boundary condition. The unknowns are the electric current density on the wall of the indentation and the total tangential magnetic field in the opening of the indentation. We also derive integral representations for the fields everywhere in free space, including the far-field region. In all cases, the integrals involved extend over finite surfaces only     

Calculation of the Impedance Matrix Inner Integral to Prescribed Precision

We present a new method for evaluating the inner integral of the impedance matrix element in the traditional Rao-Wilton-Glisson formulation of the method of moments for perfect conductors. In this method we replace the original integrand (modified by a constant phase factor) by its Taylor series and keep enough terms to guarantee a number of significant digits in the integration outcome. We develop criteria that relate the number of Taylor terms to the number of required significant digits. We integrate the leading Taylor terms analytically and the rest through iteration formulas. We show that the iteration formulas converge for all observation points within a sphere with a radius of half-a-wavelength and center the triangle's centroid. We compare results of our method with existing ones and find them in excellent agreement. We also outline a procedure for using cubatures outside the region of convergence.      

The physical optics fields of an aperture on a perfectly conducting screen in terms of line integrals

The physical optics fields due to an aperture on a perfectly conducting screen are expressed in terms of line integrals over the boundary of the aperture. These line-integral representations have the same properties as the ones in terms of surface integrals over the aperture; in particular, they admit arbitrary, source distributions, and are continuous everywhere in the source-free half-space, including the geometric optics shadow boundary.     

Electromagnetic scattering by indented screens

The problem of three dimensional electromagnetic scattering from a perfectly conducting screen with a bounded indentation is formulated as a system of boundary integral equations for the electric current density on the cavity wall and the interface between the cavity and free space. It is shown how the fictitious current density on the interface may be eliminated resulting in an integral equation of the second kind for the current density on the cavity wall only, with no integration over the infinite screen. In addition, integral representations are derived that represent the field everywhere in space in terms of the current density on the cavity wall only. Furthermore, asymptotic expressions for the far field are also presented. The equations and representations simplify considerably in the two-dimensional scalar case and results are presented for both TE and TM polarization     

Image registration based on lifting process: an application to digital subtraction radiography.

In this paper, a digital subtraction radiology scheme is presented based on a new method for the automatic registration of dental radiographs acquired with or without rigorous a priori standardization. The scheme is comprised of an automatic registration method and a subtraction process. The proposed registration method can be considered as an object-based registration method without imposing the prerequisite of image segmentation in order to detect the boundary of the objects of interest or the automatic detection of matching landmarks. This is achieved by augmenting the dimensionality of the problem from two-dimensional gray-level matching to three-dimensional surface matching using the process of lifting in combination with a surface-matching technique. The pseudo three-dimensional affine transformation that matches the lifted images incorporates advantageous characteristics including spatial alignment of the surfaces, anisotropic correction of brightness/contrast differences, and stable convergence of the similarity function to its optimal value. The performance of the proposed automatic registration method is assessed against a manual method based on the projective transformation. The qualitative and quantitative assessments of the experiments have shown advantageous performance of the proposed automatic registration method against the manual one. Finally, the proposed registration method has been further improved in terms of execution time by the implementation of a surface decimation process.     

Multimodal registration of retinal images using self organizing maps

In this paper, an automatic method for registering multimodal retinal images is presented. The method consists of three steps: the vessel centerline detection and extraction of bifurcation points only in the reference image, the automatic correspondence of bifurcation points in the two images using a novel implementation of the self organizing maps and the extraction of the parameters of the affine transform using the previously obtained correspondences. The proposed registration algorithm was tested on 24 multimodal retinal pairs and the obtained results show an advantageous performance in terms of accuracy with respect to the manual registration.     

A Power Differentiation Method of Fractal Dimension Estimation for 2-D Signals

Fractal dimension has been used for texture analysis as it is highly correlated with the human perception of surface roughness. Several methods have been proposed for the estimation of the fractal dimension of an image. One of the most popular is via its power spectrum density, provided that it is modeled as a fractional Brownian function. In this paper, a new method, called the power differentiation method (PDM), for estimating the fractal dimension of a two-variable signal from its power spectrum density is presented. The method is first applied to noise-free data of known fractal dimension. It is also tested with noise-corrupted and quantized data. Particularly, in the case of noise-corrupted data, the modified power differentiation method (MPDM) is developed, resulting in more accurate estimation of the fractal dimension. The results obtained by the PDM and the MPDM are compared directly to those obtained using four other well-known methods of fractal dimension. Finally, preliminary results for the classification of ultrasonic liver images, obtained by applying the new method, are presented.     

An iterative point correspondence algorithm for automatic image registration: an application to dental subtraction radiography

In this paper, an Automatic Iterative Point Correspondence (AIPC) algorithm towards image registration is presented. Given an image pair, distinctive points are extracted only in one of the images (reference image), and the corresponding points in the other image are obtained automatically by maximizing a similarity measure between regions of the two images with respect to the parameters of a local transformation. The maximization is accomplished by means of an iterative procedure, in which candidate solutions for the transformation parameters are tested at each iteration; these solutions are evaluated by the similarity measure between image regions. The detected point pairs by the application of the AIPC algorithm are then used to estimate the parameters of a global projective transformation for the registration of the image pair. The proposed AIPC algorithm was applied on 113 in vitro and in vivo dental image pairs providing improved registration accuracy against three widely used registration methods.