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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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NASA NTRS1992

Refining image segmentation by integration of edge and region data

An iterative parallel region growing (IPRG) algorithm previously developed by Tilton (1989) produces hierarchical segmentations of images from finer to coarser resolution. An ideal segmentation does not always correspond to one single iteration but to several different ones, each one producing the 'best' result for a separate part of the image. With the goal of finding this ideal segmentation, the results of the IPRG algorithm are refined by utilizing some additional information, such as edge features, and by interpreting the tree of hierarchical regions.

Le Moigne, Jacqueline↗

NASA NTRS1987

Refining image segmentation by polygon skeletonization

A skeletonization algorithm was encoded and applied to a test data set of land-use polygons taken from a USGS digital land use dataset at 1:250,000. The distance transform produced by this method was instrumental in the description of the shape, size, and level of generalization of the outlines of the polygons. A comparison of the topology of skeletons for forested wetlands and lakes indicated that some distinction based solely upon the shape properties of the areas is possible, and may be of use in an intelligent automated land cover classification system.

Clarke, Keith C.↗

NASA NTRS1990

Image segmentation by background extraction refinements

An image segmentation method refining background extraction in two phases is presented. In the first phase, the method detects homogeneous-background blocks and estimates the local background to be extracted throughout the image. A block is classified homogeneous if its left and right standard deviations are small. The second phase of the method refines background extraction in nonhomogeneous blocks by recomputing the shoulder thresholds. Rules that predict the final background extraction are derived by observing the behavior of successive background statistical measurements in the regions under the presence of dark and/or bright object pixels. Good results are shown for a number of outdoor scenes.

Rodriguez, Arturo A.↗

NASA NTRS1991

Passive range sensor refinement using texture and segmentation

Electrooptical sensors provide a covert way of computing range during helicopter flight. The optical flow-based computation of range provides range information only in certain distinguishable parts of the image. The regions where range information is available can be increased by performing texture analysis and object segmentation in the image. This paper reviews some of the literature on texture segmentation methods with a view towards applying them to images containing both man-made and natural objects at varying ranges. Two algorithmic approaches are given and their application to a real image is demonstrated. Results indicate that it will be necessary to combine several different texture measures and methods in a hierarchical way in order to achieve an object segmentation which is useful in enhancing range information.

Sridhar, Banavar↗

NASA NTRS1988

PIPS: A Procedure for Interactive Pyramid Segmentation

The Procedure for Interactive Pyramid Segementation was designed to identify regions of spatially connected and spectrally homogeneous pixels in multispectral image data, and to allow these regions to be interactively manipulated without the use of processing parameters. The objective is to provide the user with the capability to easily extract and identify regions corresponding to target objects of interest. The approach is to segment a multispectral image into a set of regions and to allow the analyst to interactively refine the segmentation by direct manipulation. The user can elect to: interactively display maps of the spatial distribution of regions for any designated image subset; display the statistics of a given region; and label, merge, or split regions.

Wharton, S. W.↗

NASA NTRS1991

Refinement of ground reference data with segmented image data

One of the ways to determine ground reference data (GRD) for satellite remote sensing data is to photo-interpret low altitude aerial photographs and then digitize the cover types on a digitized tablet and register them to 7.5 minute U.S.G.S. maps (that were themselves digitized). The resulting GRD can be registered to the satellite image or, vice versa. Unfortunately, there are many opportunities for error when using digitizing tablet and the resolution of the edges for the GRD depends on the spacing of the points selected on the digitizing tablet. One of the consequences of this is that when overlaid on the image, errors and missed detail in the GRD become evident. An approach is discussed for correcting these errors and adding detail to the GRD through the use of a highly interactive, visually oriented process. This process involves the use of overlaid visual displays of the satellite image data, the GRD, and a segmentation of the satellite image data. Several prototype programs were implemented which provide means of taking a segmented image and using the edges from the reference data to mask out these segment edges that are beyond a certain distance from the reference data edges. Then using the reference data edges as a guide, those segment edges that remain and that are judged not to be image versions of the reference edges are manually marked and removed. The prototype programs that were developed and the algorithmic refinements that facilitate execution of this task are described.

Robinson, Jon W.↗

NASA NTRS1986

Automated remote sensing of sea ice using synthetic aperture radar

Two techniques for automated sea ice tracking: image pyramids (hierarchical correlation) and feature tracking were applied to a pair of SEASAT SAR sea ice images. The results compare well with each other and manually tracked estimates of the ice velocity field. Refinement of the image pyramid technique should include removal of a small number of erroneous velocity vectors using constraints dependent on correlation coefficient, near neighbor velocities, and velocity gradients. Estimates of sea ice velocity are successfully obtained over limited areas using the boundary segment tracking technique. Refinement of the feature tracking technique should include use of pressure ridge features, constrained search, and relaxation techniques.

Vesecky, J. F.↗

NASA NTRS2003

Sodium Heat Pipe Module Processing For the SAFE-100 Reactor Concept

To support development and hardware-based testing of various space reactor concepts, the Early Flight Fission-Test Facility (EFF-TF) team established a specialized glove box unit with ancillary systems to handle/process alkali metals. Recently, these systems have been commissioned with sodium supporting the fill of stainless steel heat pipe modules for use with a 100 kW thermal heat pipe reactor design. As part of this effort, procedures were developed and refined to govern each segment of the process covering: fill, leak check, vacuum processing, weld closeout, and final "wet in". A series of 316 stainless steel modules, used as precursors to the actual 321 stainless steel modules, were filled with 35 +/- 1 grams of sodium using a known volume canister to control the dispensed mass. Each module was leak checked to less than10(exp -10) std cc/sec helium and vacuum conditioned at 250 C to assist in the removal of trapped gases. A welding procedure was developed to close out the fill stem preventing external gases from entering the evacuated module. Finally the completed modules were vacuum fired at 750 C allowing the sodium to fully wet the internal surface and wick structure of the heat pipe module.

Martin, James↗

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 NTRS1977

Configuration development study of the X-24C hypersonic research airplane, phase 2

The X-24C Hypersonic Research Vehicle, configured with a heat-sink structure, a launch mass limit of 31.75 Mg and powered by an LR-105 Rocket Engine plus 12 LR-101 Sustainer Engines, was found to be the more cost effective of the candidate configurations. In addition, the configuration provides the maximum off design growth potential capability and subsequently, was selected as the candidate configuration to be subjected to the design refinement study in the remaining segment of the study. Selection of this configuration was based on the analytical study conducted on the performance growth capabilities of the candidate configurations selected from the Phase 1 Study.

Combs, H. G.↗

NASA NTRS2012

Best Merge Region Growing Segmentation with Integrated Non-Adjacent Region Object Aggregation

Best merge region growing normally produces segmentations with closed connected region objects. Recognizing that spectrally similar objects often appear in spatially separate locations, we present an approach for tightly integrating best merge region growing with non-adjacent region object aggregation, which we call Hierarchical Segmentation or HSeg. However, the original implementation of non-adjacent region object aggregation in HSeg required excessive computing time even for moderately sized images because of the required intercomparison of each region with all other regions. This problem was previously addressed by a recursive approximation of HSeg, called RHSeg. In this paper we introduce a refined implementation of non-adjacent region object aggregation in HSeg that reduces the computational requirements of HSeg without resorting to the recursive approximation. In this refinement, HSeg s region inter-comparisons among non-adjacent regions are limited to regions of a dynamically determined minimum size. We show that this refined version of HSeg can process moderately sized images in about the same amount of time as RHSeg incorporating the original HSeg. Nonetheless, RHSeg is still required for processing very large images due to its lower computer memory requirements and amenability to parallel processing. We then note a limitation of RHSeg with the original HSeg for high spatial resolution images, and show how incorporating the refined HSeg into RHSeg overcomes this limitation. The quality of the image segmentations produced by the refined HSeg is then compared with other available best merge segmentation approaches. Finally, we comment on the unique nature of the hierarchical segmentations produced by HSeg.

Tilton, James C.↗

NASA NTRS1992

Interactive explorations of hierarchical segmentations

The authors report on the implementation of an interactive tool, called HSEGEXP, to interactively explore the hierarchical segmentation produced by the iterative parallel region growing (IPRG) algorithm to select the best segmentation result. This combination of the HSEGEXP tool with the IPRG algorithm amounts to a computer-assisted image segmentation system guided by human interaction. The initial application of the HSEGEXP tool is in the refinement of ground reference data based on the IPRG/HSEGEXP segmentation of the corresponding remotely sensed image data. The HSEGEXP tool is being used to help evaluate the effectiveness of an automatic 'best' segmentation process under development.

Tilton, James C.↗

NASA NTRS2016

The Segmented Aperture Interferometric Nulling Testbed (SAINT) I: Overview and Air-side System Description

This work presents an overview of the This work presents an overview of the Segmented Aperture Interferometric Nulling Testbed (SAINT), a project that will pair an actively-controlled macro-scale segmented mirror with the Visible Nulling Coronagraph (VNC). SAINT will incorporate the VNCs demonstrated wavefront sensing and control system to refine and quantify the end-to-end system performance for high-contrast starlight suppression. This pathfinder system will be used as a tool to study and refine approaches to mitigating instabilities and complex diffraction expected from future large segmented aperture telescopes., a project that will pair an actively-controlled macro-scale segmented mirror with the Visible Nulling Coronagraph (VNC). SAINT will incorporate the VNCs demonstrated wavefront sensing and control system to refine and quantify the end-to-end system performance for high-contrast starlight suppression. This pathfinder system will be used as a tool to study and refine approaches to mitigating instabilities and complex diffraction expected from future large segmented aperture telescopes.

wavefront sensing↗

NASA NTRS2017

Intelligent multi-spectral IR image segmentation

We present a neural network based multi-‐spectral image segmentation method. A neural network is trained on the selected features of both the objects and background in the longwave (LW) Infrared (IR) images. Multiple iterations of training are performed until the accuracy of the segmentation reaches satisfactory level. The segmentation boundary of the LW image is used to segment the midwave (MW) and shortwave (SW) IR images. A second neural network detects the local discontinuities and refines the accuracy of the local boundaries. The neural net based segmentation method is compared with Wavelet-‐threshold and Grab-‐Cut methods. Test results have shown increased accuracy and robustness of this segmentation scheme for multi-‐spectral IR images.

Torres, Gilbert↗

NASA NTRS2011

Method for Identifying Probable Archaeological Sites from Remotely Sensed Data

Archaeological sites are being compromised or destroyed at a catastrophic rate in most regions of the world. The best solution to this problem is for archaeologists to find and study these sites before they are compromised or destroyed. One way to facilitate the necessary rapid, wide area surveys needed to find these archaeological sites is through the generation of maps of probable archaeological sites from remotely sensed data. We describe an approach for identifying probable locations of archaeological sites over a wide area based on detecting subtle anomalies in vegetative cover through a statistically based analysis of remotely sensed data from multiple sources. We further developed this approach under a recent NASA ROSES Space Archaeology Program project. Under this project we refined and elaborated this statistical analysis to compensate for potential slight miss-registrations between the remote sensing data sources and the archaeological site location data. We also explored data quantization approaches (required by the statistical analysis approach), and we identified a superior data quantization approached based on a unique image segmentation approach. In our presentation we will summarize our refined approach and demonstrate the effectiveness of the overall approach with test data from Santa Catalina Island off the southern California coast. Finally, we discuss our future plans for further improving our approach.

Tilton, James C.↗

NASA NTRS1984

Volumetric representation for object model acquisition

This paper describes a volumetric representation that has been specified for use in a system that derives object models from a sequence of images with viewpoint specifications. This volumetric representation is an enumerative structure referred to here as a volume segment representation. The model acquisition system was designed to form an initial object approximation, then refine that approximation as subsequent information is obtained. The refinement process requires a readily modifiable object representation, while the overall goal of the system demands a representation descriptive of surface detail. The volume segment structure provides both of those capabilities.

Martin, W. N.↗

NASA NTRS1981

Development of a composite geodetic structure for space construction, phase 2

Primary physical and mechanical properties were defined for pultruded hybrid HMS/E-glass P1700 rod material used for the fabrication of geodetic beams. Key properties established were used in the analysis, design, fabrication, instrumentation, and testing of a geodetic parameter cylinder and a lattice cone closeout joined to a short cylindrical geodetic beam segment. Requirements of structural techniques were accomplished. Analytical procedures were refined and extended to include the effect of rod dimensions for the helical and longitudinal members on local buckling, and the effect of different flexural and extensional moduli on general instability buckling.

Source record↗

NASA NTRS1976

Flight evaluation of two-segment approaches using area navigation guidance equipment

A two-segment noise abatement approach procedure for use on DC-8-61 aircraft in air carrier service was developed and evaluated. The approach profile and procedures were developed in a flight simulator. Full guidance is provided throughout the approach by a Collins Radio Company three-dimensional area navigation (RNAV) system which was modified to provide the two-segment approach capabilities. Modifications to the basic RNAV software included safety protection logic considered necessary for an operationally acceptable two-segment system. With an aircraft out of revenue service, the system was refined and extensively flight tested, and the profile and procedures were evaluated by representatives of the airlines, airframe manufacturers, the Air Line Pilots Association, and the Federal Aviation Adminstration. The system was determined to be safe and operationally acceptable. It was then placed into scheduled airline service for an evaluation during which 180 approaches were flown by 48 airline pilots. The approach was determined to be compatible with the airline operational environment, although operation of the RNAV system in the existing terminal area air traffic control environment was difficult.

Schwind, G. K.↗