4,359 research outputs found

    A model-based approach for detection of objects in low resolution passive millimeter wave images

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    A model-based vision system to assist the pilots in landing maneuvers under restricted visibility conditions is described. The system was designed to analyze image sequences obtained from a Passive Millimeter Wave (PMMW) imaging system mounted on the aircraft to delineate runways/taxiways, buildings, and other objects on or near runways. PMMW sensors have good response in a foggy atmosphere, but their spatial resolution is very low. However, additional data such as airport model and approximate position and orientation of aircraft are available. These data are exploited to guide our model-based system to locate objects in the low resolution image and generate warning signals to alert the pilots. Also analytical expressions were derived from the accuracy of the camera position estimate obtained by detecting the position of known objects in the image

    A multi-scale filament extraction method: getfilaments

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    Far-infrared imaging surveys of Galactic star-forming regions with Herschel have shown that a substantial part of the cold interstellar medium appears as a fascinating web of omnipresent filamentary structures. This highly anisotropic ingredient of the interstellar material further complicates the difficult problem of the systematic detection and measurement of dense cores in the strongly variable but (relatively) isotropic backgrounds. Observational evidence that stars form in dense filaments creates severe problems for automated source extraction methods that must reliably distinguish sources not only from fluctuating backgrounds and noise, but also from the filamentary structures. A previous paper presented the multi-scale, multi-wavelength source extraction method getsources based on a fine spatial scale decomposition and filtering of irrelevant scales from images. In this paper, a multi-scale, multi-wavelength filament extraction method getfilaments is presented that solves this problem, substantially improving the robustness of source extraction with getsources in filamentary backgrounds. The main difference is that the filaments extracted by getfilaments are now subtracted by getsources from detection images during source extraction, greatly reducing the chances of contaminating catalogs with spurious sources. The intimate physical relationship between forming stars and filaments seen in Herschel observations demands that accurate filament extraction methods must remove the contribution of sources and that accurate source extraction methods must be able to remove underlying filamentary structures. Source extraction with getsources now provides researchers also with clean images of filaments, free of sources, noise, and isotropic backgrounds.Comment: 15 pages, 19 figures, to be published in Astronomy & Astrophysics; language polished for better readabilit

    Detection of a branched alkyl molecule in the interstellar medium: iso-propyl cyanide

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    The largest non-cyclic molecules detected in the interstellar medium (ISM) are organic with a straight-chain carbon backbone. We report an interstellar detection of a branched alkyl molecule, iso-propyl cyanide (i-C3H7CN), with an abundance 0.4 times that of its straight-chain structural isomer. This detection suggests that branched carbon-chain molecules may be generally abundant in the ISM. Our astrochemical model indicates that both isomers are produced within or upon dust grain ice mantles through the addition of molecular radicals, albeit via differing reaction pathways. The production of iso-propyl cyanide appears to require the addition of a functional group to a non-terminal carbon in the chain. Its detection therefore bodes well for the presence in the ISM of amino acids, for which such side-chain structure is a key characteristic.Comment: This is the author's version of the work. It is posted here by permission of the AAAS for non-commercial use. The definitive version was published in Science 345, 1584 (2014), doi:10.1126/science.125667

    A model-based approach for detection of runways and other objects in image sequences acquired using an on-board camera

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    This research was initiated as a part of the Advanced Sensor and Imaging System Technology (ASSIST) program at NASA Langley Research Center. The primary goal of this research is the development of image analysis algorithms for the detection of runways and other objects using an on-board camera. Initial effort was concentrated on images acquired using a passive millimeter wave (PMMW) sensor. The images obtained using PMMW sensors under poor visibility conditions due to atmospheric fog are characterized by very low spatial resolution but good image contrast compared to those images obtained using sensors operating in the visible spectrum. Algorithms developed for analyzing these images using a model of the runway and other objects are described in Part 1 of this report. Experimental verification of these algorithms was limited to a sequence of images simulated from a single frame of PMMW image. Subsequent development and evaluation of algorithms was done using video image sequences. These images have better spatial and temporal resolution compared to PMMW images. Algorithms for reliable recognition of runways and accurate estimation of spatial position of stationary objects on the ground have been developed and evaluated using several image sequences. These algorithms are described in Part 2 of this report. A list of all publications resulting from this work is also included

    Development of correction algorithm for pulsed terahertz computed tomography (THz-CT)

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    For last couple of decades, there has been a considerable improvement in Terahertz (THz) science, technology, and imaging. In particular, the technique of 3-D computed tomography has been adapted to the THz range. However, it has been widely recognized that a fundamental limitation to THz computed tomography imaging is the refractive effects of the sample under study. The finite refractive index of materials in the THz range can severally refract THz beams which probe the internal structure of a sample during the acquisition of tomography data. Refractive effects lead to anomalously high local absorption coefficients in the reconstructed image near the material’s boundaries. Three refractive effects are identified: (a) Fresnel reflection power losses at the boundaries, (b) an increase in path length of the probing THz radiation, and (c) steering of the THz beam by the sample such that the emerging THz radiation is no longer collected by the THz detector. In addition, the finite size of the THz beam dominates the measured THz transmission when the edges of the sample are probed using THz tomography. These boundary phenomena can dominate in the reconstructed THz-CT images making it difficult to distinguish any hidden finer structural defect(s) inside the material. In this dissertation, an algorithm has been developed to remove these refractive and finite beam size effects from THz-CT reconstructed images. The algorithm is successfully implemented on cylindrical shaped objects. A longer term goal of the research is to study the internal structure of natural cork wine stoppers by pulsed Terahertz tomography (THz-CT). It has previously been shown that THz imaging can detect the internal structure of natural cork. Moreover, the internal structure of natural cork stoppers dominates the diffusion of gasses and liquids through the cork. By using THz computed tomography, one can recreate a 3D image of the sample’s internal structure which could then be used to predict non-destructively the diffusion properties of the cork. However, refractive and boundary effects which arise in the THz tomographic image masks the presence of the cork’s internal structure. Applying the correction algorithms which are developed in this dissertation to natural cork stoppers suppresses the refractive and boundary anomalies enabling better visualization of the cork’s internal structure

    Detection of Obstacles in Monocular Image Sequences

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    The ability to detect and locate runways/taxiways and obstacles in images captured using on-board sensors is an essential first step in the automation of low-altitude flight, landing, takeoff, and taxiing phase of aircraft navigation. Automation of these functions under different weather and lighting situations, can be facilitated by using sensors of different modalities. An aircraft-based Synthetic Vision System (SVS), with sensors of different modalities mounted on-board, complements the current ground-based systems in functions such as detection and prevention of potential runway collisions, airport surface navigation, and landing and takeoff in all weather conditions. In this report, we address the problem of detection of objects in monocular image sequences obtained from two types of sensors, a Passive Millimeter Wave (PMMW) sensor and a video camera mounted on-board a landing aircraft. Since the sensors differ in their spatial resolution, and the quality of the images obtained using these sensors is not the same, different approaches are used for detecting obstacles depending on the sensor type. These approaches are described separately in two parts of this report. The goal of the first part of the report is to develop a method for detecting runways/taxiways and objects on the runway in a sequence of images obtained from a moving PMMW sensor. Since the sensor resolution is low and the image quality is very poor, we propose a model-based approach for detecting runways/taxiways. We use the approximate runway model and the position information of the camera provided by the Global Positioning System (GPS) to define regions of interest in the image plane to search for the image features corresponding to the runway markers. Once the runway region is identified, we use histogram-based thresholding to detect obstacles on the runway and regions outside the runway. This algorithm is tested using image sequences simulated from a single real PMMW image

    Hardware architectures for compact microwave and millimeter wave cameras

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    Millimeter wave SAR imaging has shown promise as an inspection tool for human skin for characterizing burns and skin cancers. However, the current state-of-the-art in microwave camera technology is not yet suited for developing a millimeter wave camera for human skin inspection. Consequently, the objective of this dissertation has been to build the necessary foundation of research to achieve such a millimeter wave camera. First, frequency uncertainty in signals generated by a practical microwave source, which is prone to drift in output frequency, was studied to determine its effect on SAR-generated images. A direct relationship was found between the level of image distortions caused by frequency uncertainty and the product of frequency uncertainty and distance between the imaging measurement grid and sample under test. The second investigation involved the development of a millimeter wave imaging system that forms the basic building block for a millimeter wave camera. The imaging system, composed of two system-on-chip transmitters and receivers and an antipodal Vivaldi-style antenna, operated in the 58-64 GHz frequency range and employed the ω-k SAR algorithm. Imaging tests on burnt pigskin showed its potential for imaging and characterizing flaws in skin. The final investigation involved the development of a new microwave imaging methodology, named Chaotic Excitation Synthetic Aperture Radar (CESAR), for designing microwave and millimeter wave cameras at a fraction of the size and hardware complexity of previous systems. CESAR is based on transmitting and receiving from all antennas in a planar array simultaneously. A small microwave camera operating in the 23-25 GHz frequency was designed and fabricated based on CESAR. Imaging results with the camera showed it was capable of basic feature detection for various applications --Abstract, page iv

    Polymer-based 3-D printing of G-band metal-pipe rectangular waveguide components

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    The objective of this thesis is to investigate the use of low-cost polymer-based 3-D printing for G-band (140 to 220 GHz) metal-pipe rectangular waveguide (MPRWG) components. First, various preliminary designs are investigated. Then, a successful ‘trough-and-lid’ assembly is demonstrated, which mitigates against the main design challenges for split-block waveguide construction at upper-millimeter-wave frequencies (ca. 100 GHz to 300 GHz), and can be realized using low-cost 3-D printing and conventional metal plating techniques. With this assembly, inexpensive masked stereolithographic apparatus (MSLA) 3-D printers and a standard commercial copper electroplating service are used. The trough-and-lid assembly is expected to provide a standard solution for the low-cost and low loss realization of most MPRWG implementations above 100 GHz; previously, this was infeasible without the use of high-cost, state-of-the-art 3-D printing and/or custom-developed metal plating techniques. Three different component types are successfully demonstrated: (i) straight thru lines; (ii) 90° twists; and (iii) bandpass filters (BPFs). Along with frequency-domain S-parameter measurements, a detailed time-domain reflectometry analysis is also included. For the more accurate characterization of these components, the additional insertion loss due to conductor surface roughness is investigated. Finally, the integration of an MPRWG component into a millimeter-wave subsystem, which is based on the design of a radiometer front-end, is presented.Open Acces

    Road curb and intersection detection using A 2D LMS

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    In most urban roads, and similar environments such as in theme parks, campus sites, industrial estates, science parks and the like, the painted lane markings that exist may not be easily discernible by CCD cameras due to poor lighting, bad weather conditions, and inadequate maintenance. An important feature of roads in such environments is the existence of pavements or curbs on either side defining the road boundaries. These curbs, which are mostly parallel to the road, can be hardnessed to extract useful features of the road for implementing autonomous navigation or driver assistance systems. However, extraction of the curb or road edge feature using vision image data is a very formidable task as the curb is not conspicuous in the vision image. To extract the curb using vision data requires extensive image processing, heuristics and very favorable ambient lighting. In our approach, road curbs are extracted speedily using range data provided by a 2D Laser range Measurement System (LMS). Experimental results are presented to demonstrate the viability, and effectiveness, of the proposed methodology and its robustness to different road configurations including road intersections
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