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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.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Detection of Subsurface Material Separation in Shuttle Orbiter Slip-Side Joggle Region of the Wing Leading Edge using Infrared Imaging Data from Arc Jet Tests

The objective of the present study was to determine whether infrared imaging (IR) surface temperature data obtained during arc-jet tests of Space Shuttle Orbiter s reinforced carbon-carbon (RCC) wing leading edge panel slip-side joggle region could be used to detect presence of subsurface material separation, and if so, to determine when separation occurs during the simulated entry profile. Recent thermostructural studies have indicated thermally induced interlaminar normal stress concentrations at the substrate/coating interface in the curved joggle region can result in local subsurface material separation, with the separation predicted to occur during approach to peak heating during reentry. The present study was an attempt to determine experimentally when subsurface material separations occur. A simplified thermal model of a flat RCC panel with subsurface material separation was developed and used to infer general surface temperature trends due to the presence of subsurface material separation. IR data from previously conducted arc-jet tests on three test specimens were analyzed: one without subsurface material separation either pre or post test, one with pre test separation, and one with separation developing during test. The simplified thermal model trend predictions along with comparison of experimental IR data of the three test specimens were used to successfully infer material separation from the arc-jet test data. Furthermore, for the test specimen that had developed subsurface material separation during the arc-jet tests, the initiation of separation appeared to occur during the ramp up to the peak heating condition, where test specimen temperature went from 2500 to 2800 F.

Daryabeigi, Kamran↗
NASA NTRS1983

Image processing in remote sensing data analysis - The state of the art

Image analysis techniques applicable to remote sensing data and covering image models, feature detection, segmentation and classification, texture analysis, and matching are studied. Model types for characterizing images examined include random-field, mosaic, and facet models. Edge and corner detection as well as global extraction of linear features are discussed. Pixel clustering and classification are covered in addition to the regional approach to segmentation. Autocorrelation, second-order gray level probability density, and the use of primitive element statistics are discussed in relation to texture analysis. Finally, reducing the cost of (sub)imaging matching methods (e.g., pixelwise comparison of gray levels and normalized cross-correlation between two images) as well as improving match sharpness is considered.

Rosenfeld, A.↗
NASA NTRS2005

Thermographic Characterization of Impact Damage in SiC/SiC Composite Materials

SiC/SiC composite materials targeted as turbine components for next-generation aero-engines are being investigated at NASA Glenn Research Center. In order to examine damage mechanisms in these materials, SiC/SiC coupons were impacted with 1.59 mm diameter steel spheres at increasing velocities from 115 m/s to 400 m/s. Pulsed thermography, a nondestructive evaluation technique that monitors the thermal response of a sample over time, was utilized to characterize the impact damage. A thermal standard of similar material was fabricated to aid in the interpretation of the thermographic data and to provide information regarding thermography system detection capabilities in 2.4 mm thick SiC/SiC composite materials. Flat bottom holes at various depths with aspect ratios greater than 2.5 were detectable in the thermal images. In addition, the edges of holes at depths of 1.93 mm into the sample were not as resolvable as flat bottom holes closer to the surface. Finally, cooling behavior was characterized in SiC/SiC materials and used to determine impact damage depth within an 8.5% error of a known depth.

Fox, Dennis S.↗
DOE OSTI2025

Hyper Spectral Anomaly Detection

Anomaly detection is a common machine learning (ML) task with growing importance in the fields of imaging, quality assurance, and multiple security related disciplines. Anomaly detection is more difficult than traditional machine learning methods due to the inherent unlabeled nature of the datasets. Existing anomaly detection architectures commonly face challenges with explainability, retaining information related to the relational structure of the data, and false positive rates. Hyperspectral Imaging Anomaly Detection (HSI) is a statistical model that employs vertex and edge weighted graphs to preserve the data’s relationships on different topographical scales. The model is able to generalize from anomaly detection in 2D images to novel datasets related to cyber-security. Furthermore, the use of multi-spectral and other filtering methods results in fewer false positives and increases the explainability of model predictions. When applying HSI to cyber-security datasets, we are able to successfully detect malicious activity with a relatively high degree of accuracy.

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS2006

Automated, on-board terrain analysis for precision landings

Advances in space robotics technology hinge to a large extent upon the development and deployment of sophisticated new vision-based methods for automated in-space mission operations and scientific survey. To this end, we have developed a new concept for automated terrain analysis that is based upon a generic image enhancement platform|multi-scale retinex (MSR) and visual servo (VS) processing. This pre-conditioning with the MSR and the vs produces a "canonical" visual representation that is largely independent of lighting variations, and exposure errors. Enhanced imagery is then processed with a biologically inspired two-channel edge detection process, followed by a smoothness based criteria for image segmentation. Landing sites can be automatically determined by examining the results of the smoothness-based segmentation which shows those areas in the image that surpass a minimum degree of smoothness. Though the msr has proven to be a very strong enhancement engine, the other elements of the approach|the vs, terrain map generation, and smoothness-based segmentation|are in early stages of development. Experimental results on data from the Mars Global Surveyor show that the imagery can be processed to automatically obtain smooth landing sites. In this paper, we describe the method used to obtain these landing sites, and also examine the smoothness criteria in terms of the imager and scene characteristics. Several examples of applying this method to simulated and real imagery are shown.

Rahman, Zia-ur↗
NASA NTRS2006

Automated On-board Terrain Analysis for Precision Landings

Advances in space robotics technology hinge to a large extent upon the development and deployment of sophisticated new vision-based methods for automated in-space mission operations and scientific survey. To this end, we have developed a new concept for automated terrain analysis that is based upon a generic image enhancement platform-multi-scale Retinex (MSR) and visual servo (VS) processing. This pre-conditioning with the MSR and the VS produces a "canonical" visual representation that is largely independent of lighting variations, and exposure errors. Enhanced imagery is then processed with a biologically inspired two-channel edge detection process, followed by a smoothness based criteria for image segmentation. Landing sites can be automatically determined by examining the results of the smoothness-based segmentation which shows those areas in the image that surpass a minimum degree of smoothness. Though the MSR has proven to be a very strong enhancement engine, the other elements of the approach, the VS, terrain map generation, and smoothness-based segmentation, are in early stages of development. Experimental results on data from the Mars Global Surveyor show that the imagery can be processed to automatically obtain smooth landing sites. In this paper, we describe the method used to obtain these landing sites, and also examine the smoothness criteria in terms of the imager and scene characteristics. Several examples of applying this method to simulated and real imagery are shown.

Rahman, Zia-ur↗
NASA NTRS2007

Hierarchical Segmentation Enhances Diagnostic Imaging

Bartron Medical Imaging LLC (BMI), of New Haven, Connecticut, gained a nonexclusive license from Goddard Space Flight Center to use the RHSEG software in medical imaging. To manage image data, BMI then licensed two pattern-matching software programs from NASA's Jet Propulsion Laboratory that were used in image analysis and three data-mining and edge-detection programs from Kennedy Space Center. More recently, BMI made NASA history by being the first company to partner with the Space Agency through a Cooperative Research and Development Agreement to develop a 3-D version of RHSEG. With U.S. Food and Drug Administration clearance, BMI will sell its Med-Seg imaging system with the 2-D version of the RHSEG software to analyze medical imagery from CAT and PET scans, MRI, ultrasound, digitized X-rays, digitized mammographies, dental X-rays, soft tissue analyses, moving object analyses, and soft-tissue slides such as Pap smears for the diagnoses and management of diseases. Extending the software's capabilities to three dimensions will eventually enable production of pixel-level views of a tumor or lesion, early identification of plaque build-up in arteries, and identification of density levels of microcalcification in mammographies.

Source record↗
NASA NTRS1993

An optical processor for zero-crossing edge detection

An optical processor for zero-crossing edge detection is presented, which consists of two defocused imaging systems to perform the Gaussian convolutions and a VLSI, ferroelectric liquid crystal spatial light modulator (SLM) to determine the zero-crossings. The zero-crossing SLM is a 32 x 32 array of pixels located on 100 microns centers. Each pixels contains a phototransistor, an auto-scaling amplifier, a zero-crossing detection circuit, and a liquid crystal modulating pad. Electrical and optical characteristics of the zero-crossing SLM are presented along with experimental results of the system.

Jared, David A.↗
NASA NTRS1982

X-ray observations to detect hot coronae around galaxies

X-ray observations were made of two nearby edge-on spiral galaxies with the Imaging Proportional Counter (IPC) on the Einstein Observatory in an effort to detect hot (1,000,000 K), gaseous galactic coronae. No diffuse emission from galactic coronae was detected. Upper limits to diffuse emission (0.3-2.9 keV) are 10 to the 39th ergs/sec (NGC 3628) and 2 x 10 to the 38th ergs/sec (NGC 4244). The measurements indicate that less than 1/1000 of the energy supplied by supernovae in these galaxies appears as soft X-rays. The energy from supernovae may be radiated away by cool gas (less than 600,000 K) whose emission is undetectable by the Einstein Observatory, or the energy may be carried away by a hot wind (10,000,000 K) which radiates inefficiently. Serendipitous X-ray sources from the two IPC fields are listed.

Bregman, J. N.↗
NASA NTRS1975

On the quantitative evaluation of edge detection schemes and their comparison with human performance

A technique for the quantitative evaluation of edge detection schemes is presented. It is used to assess the performance of three such schemes using a specially-generated set of images containing noise. The ability of human subjects to distinguish the edges in the presence of noise is also measured and compared with that of the edge detection schemes. The edge detection schemes are used on a high-resolution satellite photograph with varying degrees of noise added in order to relate the quantitative comparison to real-life imagery.

Fram, J. R.↗
NASA NTRS2016

Polarimetry and Flux Distribution in the Debris Disk Around HD 32297

We present high-contrast angular differential imaging (ADI) observations of the debris disk around HD32297 in H-band, as well as the first polarimetric images for this system in polarized differential imaging (PDI) mode with Subaru/HICIAO. In ADI, we detect the nearly edge-on disk at > or = 5(sigma) levels from approx. 0.45" to approx.1.7" (50-192AU) from the star and recover the spine deviation from the midplane already found in previous works. We also find for the first time imaging and surface brightness (SB) indications for the presence of a gapped structure on both sides of the disk at distances of approx. 0.75" (NE side) and approx. 0.65" (SW side). Global forward-modeling work delivers a best-fit model disk and well-fitting parameter intervals that essentially match previous results, with high-forward scattering grains and a ring located at 110AU. However, this single ring model cannot account for the gapped structure seen in our SB profiles. We create simple double ring models and achieve a satisfactory fit with two rings located at 60 and 95AU, respectively, low-forward scattering grains and very sharp inner slopes. In polarized light we retrieve the disk extending from approx. 0.25-1.6", although the central region is quite noisy and high S/N are only found in the range approx. 0.75-1.2". The disk is polarized in the azimuthal direction, as expected, and the departure from the midplane is also clearly observed. Evidence for a gapped scenario is not found in the PDI data. We obtain a linear polarization degree of the grains that increases from approx. 10% at 0.55" to approx. 25% at 1.6". The maximum is found at scattering angles of 90, either from the main components of the disk or from dust grains blown out to larger radii.

high-contrast angular differential imaging (ADI)↗
NASA NTRS1985

Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

Guseman, L. F., Jr.↗
NASA NTRS1992

A new method for recognizing quadric surfaces from range data and its application to telerobotics and automation

Pose and orientation of an object is one of the central issues in 3-D recognition problems. Most of today's available techniques require considerable pre-processing such as detecting edges or joints, fitting curves or surfaces to segment images, and trying to extract higher order features from the input images. We present a method based on analytical geometry, whereby all the rotation parameters of any quadric surface are determined and subsequently eliminated. This procedure is iterative in nature and was found to converge to the desired results in as few as three iterations. The approach enables us to position the quadric surface in a desired coordinate system, and then to utilize the presented shape information to explicitly represent and recognize the 3-D surface. Experiments were conducted with simulated data for objects such as hyperboloid of one and two sheets, elliptic and hyperbolic paraboloid, elliptic and hyperbolic cylinders, ellipsoids, and quadric cones. Real data of quadric cones and cylinders were also utilized. Both of these sets yielded excellent results.

Alvertos, Nicolas↗
NASA NTRS2001

Orientation processing mechanisms revealed by the plaid tilt illusion

The tilt after-effect (TAE) and tilt illusion (TI) have revealed a great deal about the nature of orientation coding of 1-dimensional (1D) lines and gratings. Comparatively little research however has addressed the mechanisms responsible for encoding the orientation of 2-dimensional (2D) plaid stimuli. A multi-stage model of edge detection has recently been proposed [Georgeson, M. A. (1998) Image & Vision Computing, 16(6-7), 389-405] to account for the perceived structure of a plaid stimulus that incorporates extraction of the zero-crossings (ZCs) of the plaid. Data is presented showing that the ZCs of a plaid inducing stimulus can interact with vertical grating test stimulus to induce a standard tilt illusion. However, by considering the second-order structure of a plaid rather than ZCs, it was shown that the perceived orientation of the vertical test grating results from the combination of orientation illusions due to the first- and second-order components of an inducing plaid. The data suggest that the mechanisms encoding the orientation of second-order contours are similar to, and interact directly with, those that encode first-order contours.

Orientation/physiology↗
NASA NTRS1980

Satellite monitoring of vegetation and geology in semi-arid environments

The possibility of mapping various characteristics of the natural environment of Tanzania by various LANDSAT techniques was assessed. Interpretation and mapping were carried out using black and white as well as color infrared images on the scale of 1:250,000. The advantages of several computer techniques were also assessed, including contrast-stretched rationing, differential edge enhancement; supervised classification; multitemporal classification; and change detection. Results Show the most useful image for interpretation comes from band 5, with additional information being obtained from either band 6 or band 7. The advantages of using color infrared images for interpreting vegetation and geology are so great that black and white should be used only to supplement the colored images.

Kihlblom, U.↗
NASA NTRS2003

In-Flight MTF Analysis of ADAR 5500 Aircraft Sensor

The Modulation Transfer Function (MTF) of an imaging system is one parameter that can be used to describe the spatial resolution or the image quality of an imaging system. MTF is the system's frequency response to an input. The MTF at a specific frequency normally ranges from 0-1, where 0 indicates no frequency response and 1 indicates perfect frequency response. The MTF value at Nyquist frequency is calculated because the Nyquist frequency is the maximum sampling frequency of the system. MTF analysis was performed on data acquired with an ADAR 5500 flown by Positive Systems on September 13-14, 2000 over Brookings, SD. Four edges from ground targets were used as inputs to the system. The system's MTF was calculated using a Matlab-based algorithm, which applied edge detection, numerical differentiation, and Fourier transformation methods to the target images.

Zanoni, Vicki↗
NASA NTRS2011

Visual Object Recognition and Tracking of Tools

A method has been created to automatically build an algorithm off-line, using computer-aided design (CAD) models, and to apply this at runtime. The object type is discriminated, and the position and orientation are identified. This system can work with a single image and can provide improved performance using multiple images provided from videos. The spatial processing unit uses three stages: (1) segmentation; (2) initial type, pose, and geometry (ITPG) estimation; and (3) refined type, pose, and geometry (RTPG) calculation. The image segmentation module files all the tools in an image and isolates them from the background. For this, the system uses edge-detection and thresholding to find the pixels that are part of a tool. After the pixels are identified, nearby pixels are grouped into blobs. These blobs represent the potential tools in the image and are the product of the segmentation algorithm. The second module uses matched filtering (or template matching). This approach is used for condensing synthetic images using an image subspace that captures key information. Three degrees of orientation, three degrees of position, and any number of degrees of freedom in geometry change are included. To do this, a template-matching framework is applied. This framework uses an off-line system for calculating template images, measurement images, and the measurements of the template images. These results are used online to match segmented tools against the templates. The final module is the RTPG processor. Its role is to find the exact states of the tools given initial conditions provided by the ITPG module. The requirement that the initial conditions exist allows this module to make use of a local search (whereas the ITPG module had global scope). To perform the local search, 3D model matching is used, where a synthetic image of the object is created and compared to the sensed data. The availability of low-cost PC graphics hardware allows rapid creation of synthetic images. In this approach, a function of orientation, distance, and articulation is defined as a metric on the difference between the captured image and a synthetic image with an object in the given orientation, distance, and articulation. The synthetic image is created using a model that is looked up in an object-model database. A composable software architecture is used for implementation. Video is first preprocessed to remove sensor anomalies (like dead pixels), and then is processed sequentially by a prioritized list of tracker-identifiers.

English, James↗
NASA NTRS1987

Combined optimization of image-gathering and image-processing systems for scene feature detection

The relationship between the image gathering and image processing systems for minimum mean squared error estimation of scene characteristics is investigated. A stochastic optimization problem is formulated where the objective is to determine a spatial characteristic of the scene rather than a feature of the already blurred, sampled and noisy image data. An analytical solution for the optimal characteristic image processor is developed. The Wiener filter for the sampled image case is obtained as a special case, where the desired characteristic is scene restoration. Optimal edge detection is investigated using the Laplacian operator x G as the desired characteristic, where G is a two dimensional Gaussian distribution function. It is shown that the optimal edge detector compensates for the blurring introduced by the image gathering optics, and notably, that it is not circularly symmetric. The lack of circular symmetry is largely due to the geometric effects of the sampling lattice used in image acquisition. The optimal image gathering optical transfer function is also investigated and the results of a sensitivity analysis are shown.

Halyo, Nesim↗