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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

1st- and 2nd-order motion and texture resolution in central and peripheral vision

STIMULI. The 1st-order stimuli are moving sine gratings. The 2nd-order stimuli are fields of static visual texture, whose contrasts are modulated by moving sine gratings. Neither the spatial slant (orientation) nor the direction of motion of these 2nd-order (microbalanced) stimuli can be detected by a Fourier analysis; they are invisible to Reichardt and motion-energy detectors. METHOD. For these dynamic stimuli, when presented both centrally and in an annular window extending from 8 to 10 deg in eccentricity, we measured the highest spatial frequency for which discrimination between +/- 45 deg texture slants and discrimination between opposite directions of motion were each possible. RESULTS. For sufficiently low spatial frequencies, slant and direction can be discriminated in both central and peripheral vision, for both 1st- and for 2nd-order stimuli. For both 1st- and 2nd-order stimuli, at both retinal locations, slant discrimination is possible at higher spatial frequencies than direction discrimination. For both 1st- and 2nd-order stimuli, motion resolution decreases 2-3 times more rapidly with eccentricity than does texture resolution. CONCLUSIONS. (1) 1st- and 2nd-order motion scale similarly with eccentricity. (2) 1st- and 2nd-order texture scale similarly with eccentricity. (3) The central/peripheral resolution fall-off is 2-3 times greater for motion than for texture.

Pattern Recognition, Visual/physiology↗
NASA NTRS1975

Spectrum analysis of acoustic emissions from boron-aluminum composites

Acoustic emissions were monitored from unidirectional tension specimens of boron-aluminum composites. It is shown that a sudden increase in count rate presages final failure. This sudden increase, however, occurs at a variable point relative to final failure load. Spectrum analysis in the range from 1 to 100 kHz was performed on the emissions with the result that no immediately obvious recognition pattern exists to distinguish between types of failure mechanisms. It is suggested that either acoustic emissions cannot be used to distinguish different failure modes in boron-aluminum composites in the frequency range studied or the specimens used had only one failure mode operating with sufficient energy release to be detected. The spectrum analysis did show, however, that the acoustic emissions had frequency components much higher than the frequencies for the fundamental modes of natural vibration of the specimen.

Henneke, E. G., II↗
NASA NTRS1972

Detailed interpretation and analysis of selected corn blight watch data sets

A detailed interpretation and analysis of selected corn blight data set was undertaken in order to better define the present capabilities and limitations of agricultural remote multispectral sensing and automatic processing techniques and to establish the areas of investigation needing futher attention in the development of operational survey systems. While the emphasis of this effort was directed toward the detection of various corn blight levels, problems related to the more general task of crop identification were also investigated. Since the analog recognition computer (SPARC) was fully committed to the more routine aspects of processing and since the detailed interpretation and analysis required more in the way of quantitative information, the CDC 1604 digital computer was employed.

Nalepka, R. F.↗
NASA NTRS1998

Analysis of Land-Use Effects on Landscape Patterns and Biological Diversity in Pacific North Forests: 1972-1991

While there is widespread recognition of the importance of preserving biological diversity there is considerable uncertainty about how to map current patterns of diversity and monitor changes through time. Ground-based approaches are impractical for examining regional patterns of biological diversity, for monitoring change, and they may actually overlook important higher-order phenomena. Thus, there is a critical need for innovative techniques to examine land-use effects on biological diversity at the landscape and regional scales. In this project, we have used satellite-based remote sensing to examine land-use effects on forest ecosystems in the Pacific NorthWest region (PNW) of the U.S.A. Rates and patterns of forest change throughout the region were quantified for the period from 1972 to 1993. This information was then used to map changes in the abundance and distribution of potential habitat for selected vertebrate species. The results of this project will be useful for identifying "keystone" stands that are important in maintaining habitat connectivity at the regional scale and for evaluating the impact of future land-use on vertebrate diversity throughout the region. The approaches developed here will also be useful in other forested regions throughout the world.

Wallin, David O.↗
NASA NTRS1992

Some distinguishing characteristics of contour and texture phenomena in images

The development of generalized contour/texture discrimination techniques is a central element necessary for machine vision recognition and interpretation of arbitrary images. Here, the visual perception of texture, selected studies of texture analysis in machine vision, and diverse small samples of contour and texture are all used to provide insights into the fundamental characteristics of contour and texture. From these, an experimental discrimination scheme is developed and tested on a battery of natural images. The visual perception of texture defined fine texture as a subclass which is interpreted as shading and is distinct from coarse figural similarity textures. Also, perception defined the smallest scale for contour/texture discrimination as eight to nine visual acuity units. Three contour/texture discrimination parameters were found to be moderately successful for this scale discrimination: (1) lightness change in a blurred version of the image, (2) change in lightness change in the original image, and (3) percent change in edge counts relative to local maximum.

Jobson, Daniel J.↗
NASA NTRS1991

Optical implementation of neocognitron and its applications to radar signature discrimination

A feature-extraction-based optoelectronic neural network is introduced. The system implementation approach applies the principle of the neocognitron paradigm first introduced by Fukushima et al. (1983). A multichannel correlator is used as a building block of a generic single layer of the neocognitron for shift-invariant feature correlation. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator. Successful pattern recognition with intraclass fault tolerance and interclass discrimination is achieved using this optoelectronic neocognitron. Detailed system analysis is described. Experimental demonstration of radar signature processing is also provided.

Chao, Tien-Hsin↗
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 NTRS1976

MIDAS prototype Multispectral Interactive Digital Analysis System for large area earth resources surveys. Volume 2: Charge coupled device investigation

MIDAS is a third-generation, fast, low cost, multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from large regions with present and projected sensors. MIDAS, for example, can process a complete ERTS frame in forty seconds and provide a color map of sixteen constituent categories in a few minutes. A principal objective of the MIDAS Program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughput. The need for advanced onboard spacecraft processing of remotely sensed data is stated and approaches to this problem are described which are feasible through the use of charge coupled devices. Tentative mechanizations for the required processing operations are given in large block form. These initial designs can serve as a guide to circuit/system designers.

Kriegler, F.↗
NASA NTRS1991

Sensor fusion III: 3-D perception and recognition; Proceedings of the Meeting, Boston, MA, Nov. 5-8, 1990

The volume on data fusion from multiple sources discusses fusing multiple views, temporal analysis and 3D motion interpretation, sensor fusion and eye-to-hand coordination, and integration in human shape perception. Attention is given to surface reconstruction, statistical methods in sensor fusion, fusing sensor data with environmental knowledge, computational models for sensor fusion, and evaluation and selection of sensor fusion techniques. Topics addressed include the structure of a scene from two and three projections, optical flow techniques for moving target detection, tactical sensor-based exploration in a robotic environment, and the fusion of human and machine skills for remote robotic operations. Also discussed are K-nearest-neighbor concepts for sensor fusion, surface reconstruction with discontinuities, a sensor-knowledge-command fusion paradigm for man-machine systems, coordinating sensing and local navigation, and terrain map matching using multisensing techniques for applications to autonomous vehicle navigation.

Schenker, Paul S.↗
NASA NTRS1973

Optical instrumentation engineering in science, technology and society; Proceedings of the Sixteenth Annual Technical Meeting, San Mateo, Calif., October 16-18, 1972

Visual tracking performance in instrumentation is discussed together with photographic pyrometry in an aeroballistic range, optical characteristics of spherical vapor bubbles in liquids, and the automatic detection and control of surface roughness by coherent diffraction patterns. Other subjects explored are related to instruments, sensors, systems, holography, and pattern recognition. Questions of data handling are also investigated, taking into account minicomputer image storage for holographic interferometry analysis, the design of a video amplifier for a 90 MHz bandwidth, and autostereoscopic screens. Individual items are announced in this issue.

Katz, Y. H.↗
NASA NTRS1980

Fracture trace expression and analysis in radar imagery of rain forest terrain (Peru)

Mapping of minor lineaments from radar imagery of the rain forest in southeast Peru is biased due to the selective suppression of some topography which results from the observation geometry of the imaging radar system and the varied perception of lineaments on the imagery by different interpreters. Team analysis of the imagery compensates for several of the sources of bias, and results in the clear recognition of differing regimes within the regional fracture field in the study area.

Martin-Kaye, P. H. A.↗
NASA NTRS1982

Computer processed LANDSAT data

Background information and exercises are provided to: (1) establish or expand understanding of the concepts, methods, and terminology of computer processing of image producing data; (2) develop insight into the advantages of computer based image processing compared with the photointerpretation approach for processing, classifying, interpreting, and applying remote sensing data; (3) foster a broad perspective on the principal of the main techniques for image enhancement, pattern recognition, and thematic classification; (4) appreciate the pros and cons of batch and interactive modes of image analysis; (5) examine and evaluate some specific computer generated products for subscenes in Pennsylvania and New Jersey; and (6) interrelate these particular examples of output with more theoretical explanations of computer processing strategies and procedures.

Source record↗
NASA NTRS1990

Tectonic evolution of Eastern Ishtar Terra, Venus

Tectonic deformation is cited as the cause for the complex morphology and topography of Eastern Ishtar Terra. A number of models proposed to account for this deformation are reviewed, and their predictions for the geology of Fortuna Tessera are examined. The detailed geology, topography, and structural fabric of Eastern Ishtar are reviewed, and these observations are compared to the predictions of the existing models for the formation and evolution of Fortuna Tessera. On the basis of the analysis, a number of conclusions are drawn regarding the evolution of Eastern Ishtar Terra. These include the recognition of primary morphological and topographical patterns which allow Eastern Ishtar Terra to be divided into four major physiographic regions named Maxwell Montes, Eastern Fortuna Tessera, Central Fortuna Tessera, and Northern Fortuna Tessera. A model is suggested that accounts for the morphology and high topography of Eastern Ishtar Terra.

Vorder Bruegge, R. W.↗
NASA NTRS1992

Analysis of interstellar cloud structure based on IRAS images

The goal of this project was to develop new tools for the analysis of the structure of densely sampled maps of interstellar star-forming regions. A particular emphasis was on the recognition and characterization of nested hierarchical structure and fractal irregularity, and their relation to the level of star formation activity. The panoramic IRAS images provided data with the required range in spatial scale, greater than a factor of 100, and in column density, greater than a factor of 50. In order to construct densely sampled column density maps of star-forming clouds, column density images of four nearby cloud complexes were constructed from IRAS data. The regions have various degrees of star formation activity, and most of them have probably not been affected much by the disruptive effects of young massive stars. The largest region, the Scorpius-Ophiuchus cloud complex, covers about 1000 square degrees (it was subdivided into a few smaller regions for analysis). Much of the work during the early part of the project focused on an 80 square degree region in the core of the Taurus complex, a well-studied region of low-mass star formation.

Scalo, John M.↗
NASA NTRS1978

Area estimation of crops by digital analysis of Landsat data

The study for which the results are presented had these objectives: (1) to use Landsat data and computer-implemented pattern recognition to classify the major crops from regions encompassing different climates, soils, and crops; (2) to estimate crop areas for counties and states by using crop identification data obtained from the Landsat identifications; and (3) to evaluate the accuracy, precision, and timeliness of crop area estimates obtained from Landsat data. The paper describes the method of developing the training statistics and evaluating the classification accuracy. Landsat MSS data were adequate to accurately identify wheat in Kansas; corn and soybean estimates for Indiana were less accurate. Systematic sampling of entire counties made possible by computer classification methods resulted in very precise area estimates at county, district, and state levels.

Bauer, M. E.↗
NASA NTRS2001

Report on Automated Semantic Analysis of Scientific and Engineering Codes

The loss of the Mars Climate Orbiter due to a software error reveals what insiders know: software development is difficult and risky because, in part, current practices do not readily handle the complex details of software. Yet, for scientific software development the MCO mishap represents the tip of the iceberg; few errors are so public, and many errors are avoided with a combination of expertise, care, and testing during development and modification. Further, this effort consumes valuable time and resources even when hardware costs and execution time continually decrease. Software development could use better tools! This lack of tools has motivated the semantic analysis work explained in this report. However, this work has a distinguishing emphasis; the tool focuses on automated recognition of the fundamental mathematical and physical meaning of scientific code. Further, its comprehension is measured by quantitatively evaluating overall recognition with practical codes. This emphasis is necessary if software errors-like the MCO error-are to be quickly and inexpensively avoided in the future. This report evaluates the progress made with this problem. It presents recommendations, describes the approach, the tool's status, the challenges, related research, and a development strategy.

Stewart. Maark E. M.↗
NASA NTRS2023

EVA Task and 3D Pose Recognition from Video

Extravehicular Activity (EVA) has been known to involve potential risks of biomechanical stresses and injuries to crewmembers. Gathering of EVA motion patterns is necessary for risk analysis and mitigation. However, many existing techniques, such as motion capture systems, are not only cost-prohibitive but are impractical for retrospective analysis of past missions. In this work, a software tool was developed, which can estimate the 3D poses of a spacesuit from photographs or videos, without using special sensors or equipment. The tool is based on the state-of-the-art artificial intelligence and machine learning (AI/ML) system, which was trained by studying and capturing motion patterns of past and current spacesuit test data. The AI/ML tool was further enhanced using synthetically generated data, in which the suit postures, backgrounds, camera angles and illumination conditions were parametrically adjusted and rendered for training. The tool, incorporated the methodologies of Convolutional Neural Network (CNN), was trained, and tested in the cloud computing environment. The trained model was then applied on new imagery and video to extract estimated joint positions and suit outlines. The joint positions were further processed to capture activity (“digging”), pose labels (“bending”), and other useful downstream information. The model performance on new imagery and video was successfully assessed for accuracy and reliability. This AI/ML based posture recognition tool thus allows for the quantification of injury risk and task performance characterization for both current and past missions and training, which can immensely help to improve EVA task and suit design.

Kyung Han Kim↗
NASA NTRS2004

A Comparative Analysis of Barchan Dunes in the Intra-Crater Dune Fields and the North Polar Sand Sea

Martian sand dunes have the potential to contribute data on geological history through a study of their form. Recognition of the characteristics of both recent and ancient dunes is the first step towards understanding the present as well as past aeolian systems, and by proxy, climatic conditions on Mars. Dunes studied in detail in Viking 1 and 2 Orbiter images have been classified as barchan, barchanoid, transverse, and complex. Regionally, they are concentrated in four locations: The North and South Polar regions, in intra crater dune fields and in troughs and valleys. Here we present the results of a morphometric analysis of barchan dunes in two of these locations: the North Polar Sand Sea (NPSS) and intra-crater dunes.

Bourke, M. C.↗