Automatic Face Recognition System Based on Local Fourier-Bessel Features

We present an automatic face verification system inspired by known properties of biological systems. In the proposed algorithm the whole image is converted from the spatial to polar frequency domain by a Fourier-Bessel Transform (FBT). Using the whole image is compared to the case where only face image regions (local analysis) are considered. The resulting representations are embedded in a dissimilarity space, where each image is represented by its distance to all the other images, and a Pseudo-Fisher discriminator is built. Verification test results on the FERET database showed that the local-based algorithm outperforms the global-FBT version. The local-FBT algorithm performed as state-of-the-art methods under different testing conditions, indicating that the proposed system is highly robust for expression, age, and illumination variations. We also evaluated the performance of the proposed system under strong occlusion conditions and found that it is highly robust for up to 50% of face occlusion. Finally, we automated completely the verification system by implementing face and eye detection algorithms. Under this condition, the local approach was only slightly superior to the global approach.Comment: 2005, Brazilian Symposium on Computer Graphics and Image Processing, 18 (SIBGRAPI

Iris Recognition: Robust Processing, Synthesis, Performance Evaluation and Applications

The popularity of iris biometric has grown considerably over the past few years. It has resulted in the development of a large number of new iris processing and encoding algorithms. In this dissertation, we will discuss the following aspects of the iris recognition problem: iris image acquisition, iris quality, iris segmentation, iris encoding, performance enhancement and two novel applications.;The specific claimed novelties of this dissertation include: (1) a method to generate a large scale realistic database of iris images; (2) a crosspectral iris matching method for comparison of images in color range against images in Near-Infrared (NIR) range; (3) a method to evaluate iris image and video quality; (4) a robust quality-based iris segmentation method; (5) several approaches to enhance recognition performance and security of traditional iris encoding techniques; (6) a method to increase iris capture volume for acquisition of iris on the move from a distance and (7) a method to improve performance of biometric systems due to available soft data in the form of links and connections in a relevant social network

Accurate depth from defocus estimation with video-rate implementation

The science of measuring depth from images at video rate using „defocus‟ has been investigated. The method required two differently focussed images acquired from a single view point using a single camera. The relative blur between the images was used to determine the in-focus axial points of each pixel and hence depth. The depth estimation algorithm researched by Watanabe and Nayar was employed to recover the depth estimates, but the broadband filters, referred as the Rational filters were designed using a new procedure: the Two Step Polynomial Approach. The filters designed by the new model were largely insensitive to object texture and were shown to model the blur more precisely than the previous method. Experiments with real planar images demonstrated a maximum RMS depth error of 1.18% for the proposed filters, compared to 1.54% for the previous design. The researched software program required five 2D convolutions to be processed in parallel and these convolutions were effectively implemented on a FPGA using a two channel, five stage pipelined architecture, however the precision of the filter coefficients and the variables had to be limited within the processor. The number of multipliers required for each convolution was reduced from 49 to 10 (79.5% reduction) using a Triangular design procedure. Experimental results suggested that the pipelined processor provided depth estimates comparable in accuracy to the full precision Matlab‟s output, and generated depth maps of size 400 x 400 pixels in 13.06msec, that is faster than the video rate. The defocused images (near and far-focused) were optically registered for magnification using Telecentric optics. A frequency domain approach based on phase correlation was employed to measure the radial shifts due to magnification and also to optimally position the external aperture. The telecentric optics ensured pixel to pixel registration between the defocused images was correct and provided more accurate depth estimates

Optical sorting and manipulation of microscopic particles

Over the last few decades, the use of light to control and manipulate microscopic particles has become widespread. These methods are enabling new areas of research to flourish across the physical and biological sciences. This thesis describes investigations into both optical trapping and the closely related field of optical sorting. It documents the development of a variety of new techniques. The thesis begins with a short review of optical trapping and existing methods for sorting mixtures of microscopic particles. The first half of this chapter highlights some of the reasons behind optical trapping's rapid growth in popularity. By reviewing an array of methods for sorting particles and discussing the relative merits of each, the case for optical sorting is established. The second chapter describes research into using a spatial light modulator to create three-dimensional optically trapped colloidal structures using the time-sharing technique. Limiting factors inherent in the technology are discussed in detail. The third chapter reviews a sophisticated particle-tracking software package that has proved to be a considerable success. It was developed explicitly with colloidal microscopy in mind and experimental plots produced by the software are used throughout the thesis. Experimental studies have been performed into the behaviour of microscopic particles moving under the influence of two classes of propagation-invariant beams: Mathieu beams and Bessel beams. The Bessel beam studies have been complimented by a theoretical model and have led ultimately to a new method for the static optical sorting of both solid particles and biological cells, with particular emphasis on human blood. The fifth and final chapter describes how re-configurable optical devices can be implemented to spatially separate different colloidal species. A new method for creating arbitrary optical landscapes using an acousto-optic modulator is reported. This new technique is then used to optically sort four particle species simultaneously - the first experimental demonstration of polydisperse optical fractionation. Additionally, experiments are reported that demonstrate controlled, static optical sorting using a spatial light modulator

Structural basis of bilayer deformation by membrane-associated scaffolds

The assembly of amphipathic lipids into fluid bilayers that are impermeable to macromolecules is fundamental to the existence of viruses, organelles, and cells. Conversely, membrane compartmentalization poses problems, since essential processes like cell division, cell migration, endo-, exo-, and transcytosis all require cells to remodel and even break their membranes without opening lethal leaks. Evolutionary forces have consequently generated proteins that can reversibly mold membranes into planes, spheres, cylinders, and saddle-shaped surfaces. Principally, the BAR (Bin, Amphiphysin, RVS) domain superfamily of proteins are recruited from the cytoplasm to induce or stabilize states of high membrane curvature, while the Dynamin superfamily of \u27large GTPases\u27 facilitate the fission of various vesicles and organelles. Members of the BAR domain superfamily often work in concert with members of the Dynamin superfamily to form and then fission membrane tubules. Here, we describe the membrane deforming properties of select F-BAR modules and the GTPase dynamin-1 that were discovered though reconstitution and direct visualization of these proteins as they shape and break model membranes

NASA Tech Briefs, May 2008

Topics covered inclde: Deployable Wireless Camera Penetrators; Hand-Held Units for Short-Range Wireless Biotelemetry; Wearable Wireless Telemetry System for Implantable BioMEMS Sensors; Electronic Escape Trails for Firefighters; Architecture for a High-to-Medium-Voltage Power Converter; 24-Way Radial Power Combiner/Divider for 31 to 36 GHz; Three-Stage InP Submillimeter-Wave MMIC Amplifier; Fast Electromechanical Switches Based on Carbon Nanotubes; Solid-State High-Temperature Power Cells; Fast Offset Laser Phase-Locking System; Fabricating High-Resolution X-Ray Collimators; Embossed Teflon AF Laminate Membrane Microfluidic Diaphragm Valves; Flipperons for Improved Aerodynamic Performance; System Estimates Radius of Curvature of a Segmented Mirror; Refractory Ceramic Foams for Novel Applications; Self-Deploying Trusses Containing Shape-Memory Polymers; Fuel-Cell Electrolytes Based on Organosilica Hybrid Proton Conductors; Molecules for Fluorescence Detection of Specific Chemicals; Cell-Detection Technique for Automated Patch Clamping; Redesigned Human Metabolic Simulator; Compact, Highly Stable Ion Atomic Clock; LiGa(OTf)(sub 4) as an Electrolyte Salt for Li-Ion Cells; Compact Dielectric-Rod White-Light Delay Lines; Single-Mode WGM Resonators Fabricated by Diamond Turning; Mitigating Photon Jitter in Optical PPM Communication; MACOS Version 3.31; Fiber-Optic Determination of N2, O2, and Fuel Vapor in the Ullage of Liquid-Fuel Tanks; Spiking Neurons for Analysis of Patterns; Symmetric Phase-Only Filtering in Particle-Image Velocimetry; Efficient Coupler for a Bessel Beam Dispersive Element; and Attitude and Translation Control of a Solar Sail Vehicle

Discrimination Between Child and Adult Forms Using Radar Frequency Signature Analysis

In this thesis we develop a method to discriminate between adult and child radar signatures. In particular, we examine radar data measured from behind a wall, which introduces radar signal attenuation and multipath effects. To investigate the child/adult discrimination problem in a through-wall, multipath scenario, a previously developed free-space human scattering model was expanded to incorporate multiple paths, and the effects of transmission through, and reflections from, walls and ground. The ground was modeled as a perfectly reflecting surface, while the walls were modeled as homogeneous concrete slabs. Twenty-five reflection paths were identified, involving the direct paths, as well as reflected paths between the ground and an adjacent wall. All paths included two-way transmission through an obstructing wall

Fourier Transforms

The 21st century ushered in a new era of technology that has been reshaping everyday life, simplifying outdated processes, and even giving rise to entirely new business sectors. Today, contemporary users of products and services expect more and more personalized products and services that can meet their unique needs. In that sense, it is necessary to further develop existing methods, adapt them to new applications, or even discover new methods. This book provides a thorough review of some methods that have an increasing impact on humanity today and that can solve different types of problems even in specific industries. Upgrading with Fourier Transformation gives a different meaning to these methods that support the development of new technologies and have a good projected acceleration in the future

EEG-induced Fear-type Emotion Classification Through Wavelet Packet Decomposition, Wavelet Entropy, and SVM

Among the most significant characteristics of human beings is their ability to feel emotions. In recent years, human-machine interface (HM) research has centered on ways to empower the classification of emotions. Mainly, human-computer interaction (HCI) research concentrates on methods that enable computers to reveal the emotional states of humans. In this research, an emotion detection system based on visual IAPPS pictures through EMOTIV EPOC EEG signals was proposed. We employed EEG signals acquired from channels (AF3, F7, F3, FC5, T7, P7, O1, O2, P8, T8, FC6, F4, F8, AF4) for individuals in a visual induced setting (IAPS fear and neutral aroused pictures). The wavelet packet transform (WPT) combined with the wavelet entropy algorithm was applied to the EEG signals. The entropy values were extracted for every two classes. Finally, these feature matrices were fed into the SVM (Support Vector Machine) type classifier to generate the classification model. Also, we evaluated the proposed algorithm as area under the ROC (Receiver Operating Characteristic) curve, or simply AUC (Area under the curve) was utilized as an alternative single-number measure. Overall classification accuracy was obtained at 91.0%. For classification, the AUC value given for SVM was 0.97. The calculations confirmed that the proposed approaches are successful for the detection of the emotion of fear stimuli via EMOTIV EPOC EEG signals and that the accuracy of the classification is acceptable