BILATERAL EDGE DETECTORS

We propose to employ bilateral filters to solve the problem of edge detection. The proposed methodology presents an efficient and noise robust method for detecting edges. Classical bilateral filters smooth images without distorting edges. In this paper, we modify the bilateral filter to perform edge detection, which is the opposite of bilateral smoothing. The Gaussian domain kernel of the bilateral filter is replaced with an edge detection mask, and Gaussian range kernel is replaced with an inverted Gaussian kernel. The modified range kernel serves to emphasize dissimilar regions. The resulting approach effectively adapts the detection mask according as the pixel intensity differences. The results of the proposed algorithm are compared with those of standard edge detection masks. Comparisons of the bilateral edge detector with Canny edge detection algorithm, both after non-maximal suppression, are also provided. The results of our technique are observed to be better and noise-robust than those offered by methods employing masks alone, and are also comparable to the results from Canny edge detector, outperforming it in certain cases.

Local edge detectors: A substrate for fine spatial vision at low temporal frequencies in rabbit retina

Visual acuity is limited by the size and density of the smallest retinal ganglion cells, which correspond to the midget ganglion cells in primate retina and the beta- ganglion cells in cat retina, both of which have concentric receptive fields that respond at either light- On or light- Off. In contrast, the smallest ganglion cells in the rabbit retina are the local edge detectors ( LEDs), which respond to spot illumination at both light- On and light- Off. However, the LEDs do not predominate in the rabbit retina and the question arises, what role do they play in fine spatial vision? We studied the morphology and physiology of LEDs in the isolated rabbit retina and examined how their response properties are shaped by the excitatory and inhibitory inputs. Although the LEDs comprise only similar to 15% of the ganglion cells, neighboring LEDs are separated by 30 - 40 mu m on the visual streak, which is sufficient to account for the grating acuity of the rabbit. The spatial and temporal receptive- field properties of LEDs are generated by distinct inhibitory mechanisms. The strong inhibitory surround acts presynaptically to suppress both the excitation and the inhibition elicited by center stimulation. The temporal properties, characterized by sluggish onset, sustained firing, and low bandwidth, are mediated by the temporal properties of the bipolar cells and by postsynaptic interactions between the excitatory and inhibitory inputs. We propose that the LEDs signal fine spatial detail during visual fixation, when high temporal frequencies are minimal.

Edge detection in digital images using fuzzy numbers

The purpose of this paper is to introduce a new approach for edge detection in grey shaded images. The proposed approach is based on the fuzzy number theory. The idea is to deal with the uncertainties concerning the grey shades making up the image and, thus, calculate the appropriateness of the pixels in relation to a homogeneous region around them. The pixels not belonging to the region are then classified as border pixels. The results have shown that the technique is simple, computationally efficient and with good results when compared with both the traditional border detectors and the fuzzy edge detectors. Copyright © 2009, Inderscience Publishers.

A multi-layered approach for site detection in UAS emergency landing scenarios using geometry-based image segmentation

This paper presents an alternative approach to image segmentation by using the spatial distribution of edge pixels as opposed to pixel intensities. The segmentation is achieved by a multi-layered approach and is intended to find suitable landing areas for an aircraft emergency landing. We combine standard techniques (edge detectors) with novel developed algorithms (line expansion and geometry test) to design an original segmentation algorithm. Our approach removes the dependency on environmental factors that traditionally influence lighting conditions, which in turn have negative impact on pixel-based segmentation techniques. We present test outcomes on realistic visual data collected from an aircraft, reporting on preliminary feedback about the performance of the detection. We demonstrate consistent performances over 97% detection rate.

Enhancement of Calcifications in Mammograms using Volterra Series based Quadratic Filter

The paper summarizes the design and implementation of a quadratic edge detection filter, based on Volterra series, for enhancing calcifications in mammograms. The proposed filter can account for much of the polynomial nonlinearities inherent in the input mammogram image and can replace the conventional edge detectors like Laplacian, gaussian etc. The filter gives rise to improved visualization and early detection of microcalcifications, which if left undetected, can lead to breast cancer. The performance of the filter is analyzed and found superior to conventional spatial edge detectors

Border detection in digital images: An approach by fuzzy numbers

The purpose of this paper is to introduce a new approach for edge detection in gray shaded images. The proposed approach is based on the fuzzy number theory. The idea is to deal with the uncertainties concerning the gray shades making up the image, and thus calculate the appropriateness of the pixels in relation to an homogeneous region around them. The pixels not belonging to the region are then classified as border pixels. The results have shown that the technique is simple, computationally efficient and with good results when compared with both the traditional border detectors and the fuzzy edge detectors. © 2007 IEEE.

Proposição de rotina morfológica para detecção de malha viária em imagens orbitais

The outdating of cartographic products affects planning. It is important to propose methods to help detect changes in surface. Thus, the combined use of remote sensing image and techniques of digital image processing has contributed significantly to minimize such outdating. Mathematical morphology is an image processing technique which describes quantitatively geometric structures presented in the image and provides tools such as edge detectors and morphological filters. Previous studies have shown that the technique has potential on the detection of significant features. Thus, this paper proposes a routine of morphological operators to detect a road network. The test area corresponds to an excerpt Quickbird image and has as a feature of interest an avenue of the city of Presidente Prudente, SP. In the processing, the main morphological operators used were threshad, areaopen, binary and erosion. To estimate the accuracy with which the linear features were detected, it was done the analysis of linear correlation between vectors of the features detected and the corresponding topographical map of the region. The results showed that the mathematical morphology can be used in cartography, aiming to use them in conventional cartographic updating processes.

Algoritmos de detecção de bordas implementados em FPGA

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Perceptual Learning via Modification of Cortical Top-Down Signals

The primary visual cortex (V1) is pre-wired to facilitate the extraction of behaviorally important visual features. Collinear edge detectors in V1, for instance, mutually enhance each other to improve the perception of lines against a noisy background. The same pre-wiring that facilitates line extraction, however, is detrimental when subjects have to discriminate the brightness of different line segments. How is it possible to improve in one task by unsupervised practicing, without getting worse in the other task? The classical view of perceptual learning is that practicing modulates the feedforward input stream through synaptic modifications onto or within V1. However, any rewiring of V1 would deteriorate other perceptual abilities different from the trained one. We propose a general neuronal model showing that perceptual learning can modulate top-down input to V1 in a task-specific way while feedforward and lateral pathways remain intact. Consistent with biological data, the model explains how context-dependent brightness discrimination is improved by a top-down recruitment of recurrent inhibition and a top-down induced increase of the neuronal gain within V1. Both the top-down modulation of inhibition and of neuronal gain are suggested to be universal features of cortical microcircuits which enable perceptual learning.

Mach edges: a key role for 3rd derivative filters in spatial vision

Edges are key points of information in visual scenes. One important class of models supposes that edges correspond to the steepest parts of the luminance profile, implying that they can be found as peaks and troughs in the response of a gradient (first-derivative) filter, or as zero-crossings (ZCs) in the second-derivative. A variety of multi-scale models are based on this idea. We tested this approach by devising a stimulus that has no local peaks of gradient and no ZCs, at any scale. Our stimulus profile is analogous to the classic Mach-band stimulus, but it is the local luminance gradient (not the absolute luminance) that increases as a linear ramp between two plateaux. The luminance profile is a smoothed triangle wave and is obtained by integrating the gradient profile. Subjects used a cursor to mark the position and polarity of perceived edges. For all the ramp-widths tested, observers marked edges at or close to the corner points in the gradient profile, even though these were not gradient maxima. These new Mach edges correspond to peaks and troughs in the third-derivative. They are analogous to Mach bands - light and dark bars are seen where there are no luminance peaks but there are peaks in the second derivative. Here, peaks in the third derivative were seen as light-to-dark edges, troughs as dark-to-light edges. Thus Mach edges are inconsistent with many standard edge detectors, but are nicely predicted by a new model that uses a (nonlinear) third-derivative operator to find edge points.

A methodology for hierarchical image segmentation evaluation

This paper proposes a method to evaluate hierarchical image segmentation procedures, in order to enable comparisons between different hierarchical algorithms and of these with other (non-hierarchical) segmentation techniques (as well as with edge detectors) to be made. The proposed method builds up on the edge-based segmentation evaluation approach by considering a set of reference human segmentations as a sample drawn from the population of different levels of detail that may be used in segmenting an image. Our main point is that, since a hierarchical sequence of segmentations approximates such population, those segmentations in the sequence that best capture each human segmentation level of detail should provide the basis for the evaluation of the hierarchical sequence as a whole. A small computational experiment is carried out to show the feasibility of our approach.

Planar Edgeless Detectors for the TOTEM Experiment at the LHC

The TOTEM experiment at the LHC will measure the total proton-proton cross-section with a precision better than 1%, elastic proton scattering over a wide range in momentum transfer -t= p^2 theta^2 up to 10 GeV^2 and diffractive dissociation, including single, double and central diffraction topologies. The total cross-section will be measured with the luminosity independent method that requires the simultaneous measurements of the total inelastic rate and the elastic proton scattering down to four-momentum transfers of a few 10^-3 GeV^2, corresponding to leading protons scattered in angles of microradians from the interaction point. This will be achieved using silicon microstrip detectors, which offer attractive properties such as good spatial resolution (<20 um), fast response (O(10ns)) to particles and radiation hardness up to 10^14 "n"/cm^2. This work reports about the development of an innovative structure at the detector edge reducing the conventional dead width of 0.5-1 mm to 50-60 um, compatible with the requirements of the experiment.

Search for a Light Higgs Boson in Central Exclusive Diffraction: Method and Detectors

By detecting leading protons produced in the Central Exclusive Diffractive process, p+p → p+X+p, one can measure the missing mass, and scan for possible new particle states such as the Higgs boson. This process augments - in a model independent way - the standard methods for new particle searches at the Large Hadron Collider (LHC) and will allow detailed analyses of the produced central system, such as the spin-parity properties of the Higgs boson. The exclusive central diffractive process makes possible precision studies of gluons at the LHC and complements the physics scenarios foreseen at the next e+e− linear collider. This thesis first presents the conclusions of the first systematic analysis of the expected precision measurement of the leading proton momentum and the accuracy of the reconstructed missing mass. In this initial analysis, the scattered protons are tracked along the LHC beam line and the uncertainties expected in beam transport and detection of the scattered leading protons are accounted for. The main focus of the thesis is in developing the necessary radiation hard precision detector technology for coping with the extremely demanding experimental environment of the LHC. This will be achieved by using a 3D silicon detector design, which in addition to the radiation hardness of up to 5×10^15 neutrons/cm2, offers properties such as a high signal-to- noise ratio, fast signal response to radiation and sensitivity close to the very edge of the detector. This work reports on the development of a novel semi-3D detector design that simplifies the 3D fabrication process, but conserves the necessary properties of the 3D detector design required in the LHC and in other imaging applications.

Structural and photoelectric studies on double barrier quantum well infrared detectors

GaAs/AlAs/GaAlAs double barrier quantum well (DBQW) structures are employed for making 3-5 um photovoltaic infrared (IR) detectors with a peak detectivity of 5 x 10(11) cm Hz(1/2)/W at 80 K. Double crystal X-ray diffraction is combined with synchrotron radiation X-ray analysis to determine successfully the exact thickness of GaAs, AlAs and GaAlAs sublayers. The interband photovoltaic (PV) spectra of the linear array of the detectors are measured directly by edge excitation method, providing the information about spatial separation processes of photogenerated carriers in the multiquantum wells and the distribution of built-in field in the active region. The spectral response of the IR photocurrent of the devices is also measured and compared with the temperature dependent IR absorption of the DBQW samples in order to get a better understanding of the bias-controlled optical and transport behavior of the detector photoresponse and thus to optimize the detector performance. (C) 1999 Elsevier Science Ltd. All rights reserved.

Structural and photoelectric studies on double barrier quantum well infrared detectors

GaAs/AlAs/GaAlAs double barrier quantum well (DBQW) structures are employed for making the 3 similar to 5 mu m photovoltaic infrared (IR) detectors with a peak detectivity of 5x10(11) cmHz(1/2)/W at 80K. The double crystal x-ray diffraction is combined with synchrotron radiation x-ray analysis to determine the exact thickness of GaAs, AlAs and GaAlAs sublayers. The interband photovoltaic (PV) spect ra of the DBQW sample and the spectral response of the IR photocurrent of the devices are measured directly by edge excitation method, providing the information about spatial separation processes of photogenerated carriers in the multiquantum wells and the distribution of built-in field in the active region.