Search NASA⌕ Search

SEARCH · Search NASA

Results for “Shape recognition”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Object Recognition using Feature- and Color-Based Methods

An improved adaptive method of processing image data in an artificial neural network has been developed to enable automated, real-time recognition of possibly moving objects under changing (including suddenly changing) conditions of illumination and perspective. The method involves a combination of two prior object-recognition methods one based on adaptive detection of shape features and one based on adaptive color segmentation to enable recognition in situations in which either prior method by itself may be inadequate. The chosen prior feature-based method is known as adaptive principal-component analysis (APCA); the chosen prior color-based method is known as adaptive color segmentation (ACOSE). These methods are made to interact with each other in a closed-loop system to obtain an optimal solution of the object-recognition problem in a dynamic environment. One of the results of the interaction is to increase, beyond what would otherwise be possible, the accuracy of the determination of a region of interest (containing an object that one seeks to recognize) within an image. Another result is to provide a minimized adaptive step that can be used to update the results obtained by the two component methods when changes of color and apparent shape occur. The net effect is to enable the neural network to update its recognition output and improve its recognition capability via an adaptive learning sequence. In principle, the improved method could readily be implemented in integrated circuitry to make a compact, low-power, real-time object-recognition system. It has been proposed to demonstrate the feasibility of such a system by integrating a 256-by-256 active-pixel sensor with APCA, ACOSE, and neural processing circuitry on a single chip. It has been estimated that such a system on a chip would have a volume no larger than a few cubic centimeters, could operate at a rate as high as 1,000 frames per second, and would consume in the order of milliwatts of power.

Duong, Tuan↗
NASA NTRS2012

Ring Image Analyzer

Ring Image Analyzer software analyzes images to recognize elliptical patterns. It determines the ellipse parameters (axes ratio, centroid coordinate, tilt angle). The program attempts to recognize elliptical fringes (e.g., Newton Rings) on a photograph and determine their centroid position, the short-to-long-axis ratio, and the angle of rotation of the long axis relative to the horizontal direction on the photograph. These capabilities are important in interferometric imaging and control of surfaces. In particular, this program has been developed and applied for determining the rim shape of precision-machined optical whispering gallery mode resonators. The program relies on a unique image recognition algorithm aimed at recognizing elliptical shapes, but can be easily adapted to other geometric shapes. It is robust against non-elliptical details of the image and against noise. Interferometric analysis of precision-machined surfaces remains an important technological instrument in hardware development and quality analysis. This software automates and increases the accuracy of this technique. The software has been developed for the needs of an R&TD-funded project and has become an important asset for the future research proposal to NASA as well as other agencies.

Strekalov, Dmitry V.↗
NASA NTRS1991

Extracellular matrix and cell shape: potential control points for inhibition of angiogenesis

Capillary endothelial (CE) cells require two extracellular signals in order to switch from quiescence to growth and back to differentiation during angiogenesis: soluble angiogenic factors and insoluble extracellular matrix (ECM) molecules. Soluble endothelial mitogens, such as basic fibroblast growth factor (FGF), act over large distances to trigger capillary growth, whereas ECM molecules act locally to modulate cell responsiveness to these soluble cues. Recent studies reveal that ECM molecules regulate CE cell growth and differentiation by modulating cell shape and by activating intracellular chemical signaling pathways inside the cell. Recognition of the importance of ECM and cell shape during capillary morphogenesis has led to the identification of a series of new angiogenesis inhibitors. Elucidation of the molecular mechanism of capillary regulation may result in development of even more potent angiogenesis modulators in the future.

Non-NASA Center↗
DOE OSTI2024

Standardizing experimental approaches to investigate interactions between bacteria and ectomycorrhizal fungi

Bacteria and ectomycorrhizal fungi (EcMF) represent two of the most dominant plant root-associated microbial groups on Earth, and their interactions continue to gain recognition as significant factors that shape forest health and resilience. Yet, we currently lack a focused review that explains the state of bacteria-EcMF interaction research in the context of experimental approaches and technological advancements. To these ends, we illustrate the utility of studying bacteria-EcMF interactions, detail outstanding questions, outline research priorities in the field, and provide a suite of approaches that can be used to promote experimental reproducibility, field advancement, and collaboration. Though this review centers on the ecology of bacteria, EcMF, and trees, it by default offers experimental and conceptual insights that can be adapted to various subfields of microbiology and microbial ecology.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1970

Image resolution: Its significance in a wildland area

The information content of simulated space photos as a function of various levels of image resolution was determined by identifying major vegetation-terrain types in a series of images purposely degraded optically to different levels of ground resolution resolvable distance. Comparison of cumulative interpretation results with actual ground truth data indicates that although there is definite decrease in interpretability as ground resolvable distance increases, some valuable information is gained by using even the poorest aerial photography. Developed is the importance of shape and texture for correct identification of broadleaf or coniferous vegetation types and the relative unimportance of shape and texture for the recognition of grassland, water bodies, and nonvegetated areas. Imagery must have a ground resolvable distance of at least 50 feet to correctly discriminate between primary types of woody vegetation.

Lauer, D. T.↗
NASA NTRS1984

Computer vision for real-time orbital operations. Center directors discretionary fund

Machine vision research is examined as it relates to the NASA Space Station program and its associated Orbital Maneuvering Vehicle (OMV). Initial operation of OMV for orbital assembly, docking, and servicing are manually controlled from the ground by means of an on board TV camera. These orbital operations may be accomplished autonomously by machine vision techniques which use the TV camera as a sensing device. Classical machine vision techniques are described. An alternate method is developed and described which employs a syntactic pattern recognition scheme. It has the potential for substantial reduction of computing and data storage requirements in comparison to the Two-Dimensional Fast Fourier Transform (2D FFT) image analysis. The method embodies powerful heuristic pattern recognition capability by identifying image shapes such as elongation, symmetry, number of appendages, and the relative length of appendages.

Vinz, F. L.↗
NASA NTRS1986

Preliminary geological investigation of AIS data at Mary Kathleen, Queensland, Australia

The Airborne Imaging Spectrometer (AIS) was flown over granitic, volcanic, and calc-silicate terrain around the Mary Kathleen Uranium Mine in Queensland, in a test of its mineralocial mapping capabilities. An analysis strategy and restoration and enhancement techniques were developed to process the 128 band AIS data. A preliminary analysis of one of three AIS flight lines shows that the data contains considerable spectral variation but that it is also contaminated by second-order leakage of radiation from the near-infrared region. This makes the recognition of expected spectral absorption shapes very difficult. The effect appears worst in terrains containing considerable vegetation. Techniques that try to predict this supplementary radiation coupled with the log residual analytical technique show that expected mineral absorption spectra can be derived. The techniques suggest that with additional refinement correction procedures, the Australian AIS data may be revised. Application of the log residual analysis method has proved very successful on the cuprite, Nevada data set, and for highlighting the alunite, linite, and SiOH mineralogy.

Huntington, J. F.↗
NASA NTRS1987

Improved shape-signature and matching methods for model-based robotic vision

Researchers describe new techniques for curve matching and model-based object recognition, which are based on the notion of shape-signature. The signature which researchers use is an approximation of pointwise curvature. Described here is curve matching algorithm which generalizes a previous algorithm which was developed using this signature, allowing improvement and generalization of a previous model-based object recognition scheme. The results and the experiments described relate to 2-D images. However, natural extensions to the 3-D case exist and are being developed.

Schwartz, J. T.↗
NASA NTRS2003

Automated Coronal Loop Identification Using Digital Image Processing Techniques

The results of a master thesis project on a study of computer algorithms for automatic identification of optical-thin, 3-dimensional solar coronal loop centers from extreme ultraviolet and X-ray 2-dimensional images will be presented. These center splines are proxies of associated magnetic field lines. The project is pattern recognition problems in which there are no unique shapes or edges and in which photon and detector noise heavily influence the images. The study explores extraction techniques using: (1) linear feature recognition of local patterns (related to the inertia-tensor concept), (2) parametric space via the Hough transform, and (3) topological adaptive contours (snakes) that constrains curvature and continuity as possible candidates for digital loop detection schemes. We have developed synthesized images for the coronal loops to test the various loop identification algorithms. Since the topology of these solar features is dominated by the magnetic field structure, a first-order magnetic field approximation using multiple dipoles provides a priori information in the identification process. Results from both synthesized and solar images will be presented.

Lee, Jong K.↗
NASA NTRS1982

A study of image quality for radar image processing

Methods developed for image quality metrics are reviewed with focus on basic interpretation or recognition elements including: tone or color; shape; pattern; size; shadow; texture; site; association or context; and resolution. Seven metrics are believed to show promise as a way of characterizing the quality of an image: (1) the dynamic range of intensities in the displayed image; (2) the system signal-to-noise ratio; (3) the system spatial bandwidth or bandpass; (4) the system resolution or acutance; (5) the normalized-mean-square-error as a measure of geometric fidelity; (6) the perceptual mean square error; and (7) the radar threshold quality factor. Selective levels of degradation are being applied to simulated synthetic radar images to test the validity of these metrics.

King, R. W.↗
NASA NTRS2012

NASA Tech Briefs, January 2012

Contents of this issue are: (1) Energy-Based Tetrahedron Sensor for High-Temperature, High-Pressure Environments (2) Handheld Universal Diagnostic Sensor (3) Large-Area Vacuum Ultraviolet Sensors (4) Fiber Bragg Grating Sensor System for Monitoring Smart Composite Aerospace Structures (5) Health-Enabled Smart Sensor Fusion Technology (6) Extended-Range Passive RFID and Sensor Tags (7) Hybrid Collaborative Learning for Classification and Clustering in Sensor Networks (8) Self-Healing, Inflatable, Rigidizable Shelter (9) Improvements in Cold-Plate Fabrication (10) Technique for Radiometer and Antenna Array Calibration - TRAAC (11) Real-Time Cognitive Computing Architecture for Data Fusion in a Dynamic Environment (12) Programmable Digital Controller (13) Use of CCSDS Packets Over SpaceWire to Control Hardware (14) Key Decision Record Creation and Approval Module (15) Enhanced Graphics for Extended Scale Range (16) Debris Examination Using Ballistic and Radar Integrated Software (17) Data Distribution System (DDS) and Solar Dynamic Observatory Ground Station (SDOGS) (18) Integration Manager (19) Eclipse-Free-Time Assessment Tool for IRIS (20) Automated and Manual Rocket Crater Measurement Software (21) MATLAB Stability and Control Toolbox Trim and Static Stability Module (22) Patched Conic Trajectory Code (23) Ring Image Analyzer (24) SureTrak Probability of Impact Display (25) Implementation of a Non-Metallic Barrier in an Electric Motor (26) Multi-Mission Radioisotope Thermoelectric Generator Heat Exchangers for the Mars Science Laboratory Rover (27) Uniform Dust Distributor for Testing Radiative Emittance of Dust-Coated Surfaces (28) MicroProbe Small Unmanned Aerial System (29) Highly Stable and Active Catalyst for Sabatier Reactions (30) Better Proton-Conducting Polymers for Fuel-Cell Membranes (31) CCD Camera Lens Interface for Real-Time Theodolite Alignment (32) Peregrine 100-km Sounding Rocket Project (33) SOFIA Closed- and Open-Door Aerodynamic Analyses (34) Sonic Thermometer for High-Altitude Balloons (35) Near-Infrared Photon-Counting Camera for High-Sensitivity Observations (36) Integrated Optics Achromatic Nuller for Stellar Interferometry (37) High-Speed Digital Interferometry (38) Ultra-Miniature Lidar Scanner for Launch Range Data Collection (39) Shape and Color Features for Object Recognition Search (40) Explanation Capabilities for Behavior-Based Robot Control (41) A DNA-Inspired Encryption Methodology for Secure, Mobile Ad Hoc Networks (42) Quality Control Method for a Micro-Nano-Channel Microfabricated Device (43) Corner-Cube Retroreflector Instrument for Advanced Lunar Laser Ranging (44) Electrospray Collection of Lunar Dust (45) Fabrication of a Kilopixel Array of Superconducting Microcalorimeters with Microstripline Wiring Spacecraft Attitude Tracking and Maneuver Using Combined Magnetic Actuators (46) Coherent Detector for Near-Angle Scattering and Polarization Characterization of Telescope Mirror Coatings

Source record↗
NASA NTRS2006

Biomimetic/Optical Sensors for Detecting Bacterial Species

Biomimetic/optical sensors have been proposed as means of real-time detection of bacteria in liquid samples through real-time detection of compounds secreted by the bacteria. Bacterial species of interest would be identified through detection of signaling compounds unique to those species. The best-characterized examples of quorum-signaling compounds are acyl-homoserine lactones and peptides. Each compound, secreted by each bacterium of an affected species, serves as a signal to other bacteria of the same species to engage in a collective behavior when the population density of that species reaches a threshold level analogous to a quorum. A sensor according to the proposal would include a specially formulated biomimetic film, made of a molecularly imprinted polymer (MIP), that would respond optically to the signaling compound of interest. The MIP film would be integrated directly onto an opticalwaveguide- based ring resonator for optical readout. Optically, the sensor would resemble the one described in Chemical Sensors Based on Optical Ring Resonators (NPO-40601), NASA Tech Briefs, Vol. 29, No. 10 (October 2005), page 32. MIPs have been used before as molecular- recognition compounds, though not in the manner of the present proposal. Molecular imprinting is an approach to making molecularly selective cavities in a polymer matrix. These cavities function much as enzyme receptor sites: the chemical functionality and shape of a cavity in the polymer matrix cause the cavity to bind to specific molecules. An MIP matrix is made by polymerizing monomers in the presence of the compound of interest (template molecule). The polymer forms around the template. After the polymer solidifies, the template molecules are removed from the polymer matrix by decomplexing them from their binding sites and then dissolving them, leaving cavities that are matched to the template molecules in size, shape, and chemical functionality. The cavities thus become molecular-recognition sites that bind only to molecules matched to the sites; other molecules are excluded. In a sensor according to the proposal, the MIP would feature molecular recognition sites that would bind the specific signaling molecules selectively according to their size, shape, and chemical functionality (see figure). As the film took up the signaling molecules in the molecular recognition sites, the index of refraction and thickness of the film would change, causing a wavelength shift of the peak of the resonance spectrum. It has been estimated that by measuring this wavelength shift, it should be possible to detect as little as 10 picomoles of a peptide signaling compound.

Homer, Margie↗
NASA NTRS1988

A survey of visual preprocessing and shape representation techniques

Many recent theories and methods proposed for visual preprocessing and shape representation are summarized. The survey brings together research from the fields of biology, psychology, computer science, electrical engineering, and most recently, neural networks. It was motivated by the need to preprocess images for a sparse distributed memory (SDM), but the techniques presented may also prove useful for applying other associative memories to visual pattern recognition. The material of this survey is divided into three sections: an overview of biological visual processing; methods of preprocessing (extracting parts of shape, texture, motion, and depth); and shape representation and recognition (form invariance, primitives and structural descriptions, and theories of attention).

Olshausen, Bruno A.↗
NASA NTRS1999

The Isothermal Dendritic Growth Experiment (IDGE)

The Isothermal Dendritic Growth Experiment (IDGE) constituted a series of three NASA-supported microgravity experiments, all of which flew aboard the space shuttle, Columbia. This experimental space flight series was designed and operated to grow and record dendrite solidification in the absence of gravity-induced convective heat transfer, and thereby produce a wealth of benchmark-quality data for testing solidification scaling laws. The data and analysis performed on the dendritic growth speed and tip size in Succinontrie (SCN) demonstrates that although the theory yields predictions that are reasonably in agreement with experiment, there are significant discrepancies. However, some of these discrepancies can be explained by accurately describing the diffusion of heat. The key finding involves recognition that the actual three-dimensional shape of dendrites includes time-dependent side-branching and a tip region that is not a paraboloid of revolution. Thus, the role of heat transfer in dendritic growth is validated, with the caveat that a more realistic model of the dendrite then a paraboloid is needed to account for heat flow in an experimentally observed dendrite. We are currently conducting additional analysis to further confirm and demonstrate these conclusions. The data and analyses for the growth selection physics remain much less definitive. From the first flight, the data indicated that the selection parameter, sigma*, is not exactly a constant, but exhibits a slight dependence on the supercooling. Additional data from the second flight are being examined to investigate the selection of a unique dendrite speed, tip size and shape. The IDGE flight series is now complete. We are currently completing analyses and moving towards final data archiving. It is gratifying to see that the IDGE published results and archived data sets are being used actively by other scientists and engineers. In addition, we are also pleased to report that the techniques and IDGE hardware system that the authors developed with NASA, are being currently employed on both designated flight experiments, like EDSE, and on flight definition experiments, like TDSE.

Glicksman, Martin E.↗
NASA NTRS2006

Laboratory Simulation of Impacts upon Aluminum Foils of the Stardust Spacecraft: Calibration of Dust Particle Size from Comet Wild 2

Metallic aluminium alloy foils exposed on the forward, comet-facing surface of the aerogel tray on the Stardust spacecraft are likely to have been impacted by the same cometary particle population as the dedicated impact sensors and the aerogel collector. The ability of soft aluminium alloy to record hypervelocity impacts as bowl-shaped craters offers an opportunistic substrate for recognition of impacts by particles of a wide potential size range. In contrast to impact surveys conducted on samples from low Earth orbit, the simple encounter geometry for Stardust and Wild 2, with a known and constant spacecraft-particle relative velocity and effective surface-perpendicular impact trajectories, permits closely comparable simulation in laboratory experiments. For a detailed calibration programme we have selected a suite of spherical glass projectiles of uniform density and hardness characteristics, with well-documented particle size range from 10 microns to nearly 100 microns. Light gas gun buckshot firings of these particles at approximately 6km s)exp -1) onto samples of the same foil as employed on Stardust have yielded large numbers of craters. Scanning electron microscopy of both projectiles and impact features has allowed construction of a calibration plot, showing a linear relationship between impacting particle size and impact crater diameter. The close match between our experimental conditions and the Stardust mission encounter parameters should provide another opportunity to measure particle size distributions and fluxes close to the nucleus of Wild 2, independent of the active impact detector instruments aboard the Stardust spacecraft.

Kearsley, A. T.↗
DOE OSTI2022

Using dorsal surface for individual identification of dairy calves through 3D deep learning algorithms

Advances in machine learning techniques have allowed the development of computer vision systems (CVS) that can accurately predict several phenotypes of interest for livestock operations. In this context, 3D images taken from a top-down view are particularly useful for estimating body condition score, growth development, and body biometrics in cattle. Frequently, such CVS rely on identification (ID) systems, such as electronic tags, as a way to match animal ID and the predicted phenotype. However, the same 3D images used to predict body weight and other animal biometrics could be adopted for animal recognition as well. Such alternative would optimize CVS to recognize animal ID and monitor growth development simultaneously while leveraging the same hardware infrastructure. Furthermore, this strategy could be used to recognize animals with similar color patterns. Nonetheless, growing animals are continuously changing body shape, which could limit its use as an invariant feature for pattern recognition. Thus, the objectives of this study were: (1) to compare algorithms for different 3D object representations to identify individual animals; and (2) to evaluate how short-term changes in body shape due to animal growth affect the predictive performance of these algorithms. For objective 1, the algorithms were trained (n = 4,558) and tested (n = 1,139) using images from 38 Holstein calves. For objective 2, we designed three different experiments using images (n = 2,347) from five Holstein calves taken over six weeks during their growing period, always training and testing on different weeks. Each experiment evaluated how changing a different parameter of the image capturing procedure affected the predictive ability of the trained algorithms. In the first experiment, we varied the total number of images per animal in the training set; in the second experiment, we varied the number of weeks while keeping a fixed number of images in the training set; and in the third experiment, we skipped weeks between images in the training and test sets. The F 1 score for objective (1) was up to 0.804 when testing with the last frames of each video, and up to 0.959 when using random frames for testing. For objective (2), the F 1 score was up to 0.947 for the first experiment when using 130 images per animal; up to 0.979 for the second experiment when using all five weeks; and up to 0.917 when not skipping weeks between training and testing. In conclusion, these results show that deep learning algorithms can be used to identify individual animals through their dorsal area 3D surfaces, and, from our experiments using calves in their growing period, that they are robust enough to account for changes in body shape and size, making them a promising tool for animal recognition during growth.

3D neural networks↗
DOE OSTI2023

Opiate Sensitivity in Fruit Flies

Substance use disorder is a debilitating clinical condition in which behavioral dependence results from biological, environmental, genetic, and psychosocial factors. An epidemic surrounding the use and abuse of opioids is ravaging the world. While considerable efforts have explored the social drivers of addiction, a deeper understanding of biological causes and genetic vulnerabilities, preventative interventions, and effective treatments, have all proven elusive. This perspective article aims to remind readers that addictive natural compounds such as cocaine, nicotine, cathinone, or morphine, evolved as defensive metabolites to deter insect herbivory. The molecular mechanisms underlying motivational seeking and learning/reward show remarkable conservation since their early emergence in bilateral metazoans. An extended coevolutionary arms race subsequently weaponized these compounds into disruptors of learning, motivation, and incentivized attention. When plant chemical defenses attack insect physiology, humans are rendered susceptible due to strong conservation in the underlying molecular machinery. This perspective addresses the paradox that opiates were shaped to target insect neuropharmacology, even though this taxon appears to lack the recognized opioid receptor clade of mammals. We argue that the link is to be found in the allatostatin receptor, a basal ortholog of opioid receptors. Moreover, preliminary evidence indicates that morphine reduces Drosophila feeding and locomotion, concordant with a purported role as a defensive compound reducing herbivory. An implementation via allatostatin-mediated mechanisms is likely. This research argues for a broader heuristic perspective of substance abuse and a recognition of the evolutionary constraints that have likely shaped the biological drivers of opioid sensitivity and of its behavioral targets.

59 BASIC BIOLOGICAL SCIENCES↗