Generalized antisymmetric filters for edge detection

A large number of filters has been proposed to compute local gradients in grayscale images, usually having as goal the adequate characterization of edges. A significant portion of such filters are antisymmetric with respect to the origin. In this work we propose to generalize those filters by incorporating an explicit evaluation of the tonal difference. More specifically, we propose to apply restricted dissimilarity functions to appropriately measure the tonal differences. We present the mathematical developments, as well as quantitative experiments that indicate that our proposal offers a clear option to improve the performance of classical edge detection filters

Modeling edges at subpixel accuracy using the local energy approach

In this paper we described new technique for 1-D and 2-D edge feature extraction to subpixel accuracy using edge models and the local energy approach. A candidate edge is modeled as one of a number of parametric edge models, and the fit is refined by a least-squared error fitting technique

Final design and fabrication of an active control system for flutter suppression on a supercritical aeroelastic research wing

The final design and hardware fabrication was completed for an active control system capable of the required flutter suppression, compatible with and ready for installation in the NASA aeroelastic research wing number 1 (ARW-1) on Firebee II drone flight test vehicle. The flutter suppression system uses vertical acceleration at win buttock line 1.930 (76), with fuselage vertical and roll accelerations subtracted out, to drive wing outboard aileron control surfaces through appropriate symmetric and antisymmetric shaping filters. The goal of providing an increase of 20 percent above the unaugmented vehicle flutter velocity but below the maximum operating condition at Mach 0.98 is exceeded by the final flutter suppression system. Results indicate that the flutter suppression system mechanical and electronic components are ready for installation on the DAST ARW-1 wing and BQM-34E/F drone fuselage

Gradient extraction operators for discrete interval-valued data

Digital images are generally created as discrete measurements of light, as performed by dedicated sensors. Consequently, each pixel contains a discrete approximation of the light inciding in a sensor element. The nature of this measurement implies certain uncertainty due to discretization matters. In this work we propose to model such uncertainty using intervals, further leading to the generation of so-called interval-valued images. Then, we study the partial differentiation of such images, putting a spotlight on antisymmetric convolution operators for such task. Finally, we illustrate the utility of the interval-valued images by studying the behaviour of an extended version of the well-known Canny edges detection method

Finite element method analysis of band gap and transmission of two-dimensional metallic photonic crystals at terahertz frequencies

Photonic band gap and transmission characteristics of 2D metallic photonic crystals at THz frequencies have been investigated using finite element method (FEM). Photonic crystals composed of metallic rods in air, in square and triangular lattice arrangements, are considered for transverse electric and transverse magnetic polarizations. The modes and band gap characteristics of metallic photonic crystal structure are investigated by solving the eigenvalue problem over a unit cell of the lattice using periodic boundary conditions. A photonic band gap diagram of dielectric photonic crystal in square lattice array is also considered and compared with well-known plane wave expansion results verifying our FEM approach. The photonic band gap designs for both dielectric and metallic photonic crystals are consistent with previous studies obtained by different methods. Perfect match is obtained between photonic band gap diagrams and transmission spectra of corresponding lattice structure

Detecting and localizing edges composed of steps, peaks and roofs

Caption title.Includes bibliographical references (p. 17-18).Research supported by the U.S. Army Research Office. DAAL01-86-K-0171Pietro Perona and Jitendra Malik

The role of high-order phase correlations in texture processing

AbstractIsodipole textures are pairs of texture ensembles whose autocorrelations, and hence power spectra, are equal. Examples of readily discriminable isodipole textures are well known. Such discriminations appear to require feature extraction, since the isodipole condition eliminates ensemble differences in spatial frequency content. We studied the effects of phase decorrelation on VEP indices of discrimination of isodipole texture pairs. Phase decorrelation, which ranged from 0.125π radians (slight randomization) to π radians (complete randomization), was introduced in two ways: by independent jittering of each spatial Fourier component, and by a product method, which preserved correlations among certain quadruples of spatial Fourier components, despite pairwise decorrelation. For the even/random isodipole texture pair, independent phase decorrelation greater than 0.5π radians markedly reduced VEP indices of texture discrimination for all check sizes, and eliminated them entirely for check sizes of 8 min or greater. However, the product method preserved texture discrimination signals even with complete pairwise randomization of spatial phases. For the triangle/random isodipole texture pair, both kinds of phase decorrelation eliminated VEP indices of texture discrimination. These results imply that isodipole texture discrimination is based on fundamentally local processing, and not on global Fourier amplitudes—since the phase manipulations which eliminate texture discrimination preserve the Fourier amplitudes. The dependence of the antisymmetric response component (the odd harmonics) on phase decorrelation and texture type is consistent with a previously proposed model for feature extraction, and leads to constraints on how texture processing is modulated by contrast. The limited contribution of global spectral characteristics for small checks is consistent with a previously identified breakdown in scale-invariant processing