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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 NTRS1995

Color Helmet Mounted Display System with Real Time Computer Generated and Video Imagery for In-Flight Simulation

NASA Ames Research Center and the US Army are developing the Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) using a Sikorsky UH-60 helicopter for the purpose of flight systems research. A primary use of the RASCAL is in-flight simulation for which the visual scene will use computer generated imagery and synthetic vision. This research is made possible in part to a full color wide field of view Helmet Mounted Display (HMD) system that provides high performance color imagery suitable for daytime operations in a flight-rated package. This paper describes the design and performance characteristics of the HMD system. Emphasis is placed on the design specifications, testing, and integration into the aircraft of Kaiser Electronics' RASCAL HMD system that was designed and built under contract for NASA. The optical performance and design of the Helmet mounted display unit will be discussed as well as the unique capabilities provided by the system's Programmable Display Generator (PDG).

Sawyer, Kevin↗

NASA NTRS1989

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Tescher, Andrew G.↗

NASA NTRS1991

A computer vision system for the recognition of trees in aerial photographs

Increasing problems of forest damage in Central Europe set the demand for an appropriate forest damage assessment tool. The Vision Expert System (VES) is presented which is capable of finding trees in color infrared aerial photographs. Concept and architecture of VES are discussed briefly. The system is applied to a multisource test data set. The processing of this multisource data set leads to a multiple interpretation result for one scene. An integration of these results will provide a better scene description by the vision system. This is achieved by an implementation of Steven's correlation algorithm.

Pinz, Axel J.↗

NASA NTRS2010

Daytime Water Detection Based on Color Variation

Robust water detection is a critical perception requirement for unmanned ground vehicle (UGV) autonomous navigation. This is particularly true in wide open areas where water can collect in naturally occurring terrain depressions during periods of heavy precipitation and form large water bodies (such as ponds). At far range, reflections of the sky provide a strong cue for water. But at close range, the color coming out of a water body dominates sky reflections and the water cue from sky reflections is of marginal use. We model this behavior by using water body intensity data from multiple frames of RGB imagery to estimate the total reflection coefficient contribution from surface reflections and the combination of all other factors. Then we describe an algorithm that uses one of the color cameras in a forward- looking, UGV-mounted stereo-vision perception system to detect water bodies in wide open areas. This detector exploits the knowledge that the change in saturation-to-brightness ratio across a water body from the leading to trailing edge is uniform and distinct from other terrain types. In test sequences approaching a pond under clear, overcast, and cloudy sky conditions, the true positive and false negative water detection rates were (95.76%, 96.71%, 98.77%) and (0.45%, 0.60%, 0.62%), respectively. This software has been integrated on an experimental unmanned vehicle and field tested at Ft. Indiantown Gap, PA.

reflection coefficient↗

NASA NTRS2009

Adaptive Morphological Feature-Based Object Classifier for a Color Imaging System

Utilizing a Compact Color Microscope Imaging System (CCMIS), a unique algorithm has been developed that combines human intelligence along with machine vision techniques to produce an autonomous microscope tool for biomedical, industrial, and space applications. This technique is based on an adaptive, morphological, feature-based mapping function comprising 24 mutually inclusive feature metrics that are used to determine the metrics for complex cell/objects derived from color image analysis. Some of the features include: Area (total numbers of non-background pixels inside and including the perimeter), Bounding Box (smallest rectangle that bounds and object), centerX (x-coordinate of intensity-weighted, center-of-mass of an entire object or multi-object blob), centerY (y-coordinate of intensity-weighted, center-of-mass, of an entire object or multi-object blob), Circumference (a measure of circumference that takes into account whether neighboring pixels are diagonal, which is a longer distance than horizontally or vertically joined pixels), . Elongation (measure of particle elongation given as a number between 0 and 1. If equal to 1, the particle bounding box is square. As the elongation decreases from 1, the particle becomes more elongated), . Ext_vector (extremal vector), . Major Axis (the length of a major axis of a smallest ellipse encompassing an object), . Minor Axis (the length of a minor axis of a smallest ellipse encompassing an object), . Partial (indicates if the particle extends beyond the field of view), . Perimeter Points (points that make up a particle perimeter), . Roundness [(4(pi) x area)/perimeter(squared)) the result is a measure of object roundness, or compactness, given as a value between 0 and 1. The greater the ratio, the rounder the object.], . Thin in center (determines if an object becomes thin in the center, (figure-eight-shaped), . Theta (orientation of the major axis), . Smoothness and color metrics for each component (red, green, blue) the minimum, maximum, average, and standard deviation within the particle are tracked. These metrics can be used for autonomous analysis of color images from a microscope, video camera, or digital, still image. It can also automatically identify tumor morphology of stained images and has been used to detect stained cell phenomena (see figure).

McDowell, Mark↗

NASA NTRS1990

Ames vision group research overview

A major goal of the reseach group is to develop mathematical and computational models of early human vision. These models are valuable in the prediction of human performance, in the design of visual coding schemes and displays, and in robotic vision. To date researchers have models of retinal sampling, spatial processing in visual cortex, contrast sensitivity, and motion processing. Based on their models of early human vision, researchers developed several schemes for efficient coding and compression of monochrome and color images. These are pyramid schemes that decompose the image into features that vary in location, size, orientation, and phase. To determine the perceptual fidelity of these codes, researchers developed novel human testing methods that have received considerable attention in the research community. Researchers constructed models of human visual motion processing based on physiological and psychophysical data, and have tested these models through simulation and human experiments. They also explored the application of these biological algorithms to applications in automated guidance of rotorcraft and autonomous landing of spacecraft. Researchers developed networks for inhomogeneous image sampling, for pyramid coding of images, for automatic geometrical correction of disordered samples, and for removal of motion artifacts from unstable cameras.

Watson, Andrew B.↗

NASA NTRS2000

Terrain Perception for DEMO III

The Demo III program has as its primary focus the development of autonomous mobility for a small rugged cross country vehicle. In this paper we report recent progress on both stereo-based obstacle detection and terrain cover color-based classification.

autonomous navigation color classification terrain↗

NASA NTRS2008

Synthetic Vision Displays for Planetary and Lunar Lander Vehicles

Aviation research has demonstrated that Synthetic Vision (SV) technology can substantially enhance situation awareness, reduce pilot workload, improve aviation safety, and promote flight path control precision. SV, and related flight deck technologies are currently being extended for application in planetary exploration vehicles. SV, in particular, holds significant potential for many planetary missions since the SV presentation provides a computer-generated view for the flight crew of the terrain and other significant environmental characteristics independent of the outside visibility conditions, window locations, or vehicle attributes. SV allows unconstrained control of the computer-generated scene lighting, terrain coloring, and virtual camera angles which may provide invaluable visual cues to pilots/astronauts, not available from other vision technologies. In addition, important vehicle state information may be conformally displayed on the view such as forward and down velocities, altitude, and fuel remaining to enhance trajectory control and vehicle system status. The paper accompanies a conference demonstration that introduced a prototype NASA Synthetic Vision system for lunar lander spacecraft. The paper will describe technical challenges and potential solutions to SV applications for the lunar landing mission, including the requirements for high-resolution lunar terrain maps, accurate positioning and orientation, and lunar cockpit display concepts to support projected mission challenges.

Arthur, Jarvis J., III↗

NASA NTRS1989

Radiation Blocking Lenses

Biomedical Optical Company of America's (BOCA) suntiger lenses, similar in principle to natural filters in the eyes of hawks and eagles, bar 99 percent of potentially harmful wavelengths, while allowing visually useful colors of light (red, orange, green) to pass through. They also improve visual acuity, night vision and haze or fog visibility. The lenses evolved from work done by James B. Stephens and Dr. Charles G. Miller of the Jet Propulsion Laboratory. They developed a formula and produced a commercial welding curtain that absorbs, filters, and scatters light. This research led to protective glasses now used by dentists, workers in hazardous environments, CRT operators and skiers.

Source record↗

NASA NTRS1991

Automated rendezvous and capture system

This paper describes an ARC system that is an attempt to simplify opration, reduce energy requirements, reduce weight, and provide longterm use and reliability. The ARC system is a laser/optical/holographic (LOH) control system for guidance, rendezvous, and docking (RVD). The LOH/RVD utilizes a hologram, residing at the target platform. Excited by a laser diode, the hologram projects an image at a given distance from the platform. A vision system in the automated chase vehicle sees the projected image and, by optical comparisons, guides the chase vehicle to that image, reaching a proximity conductive to soft docking. The vision system then shifts to a second hologram image holding at close proximity (2mm) to the target platform and guides to it for controlled, precise docking at the rendezvous point. The holographic image projections from the target platform, are composed of color hues and may be circular, triangular or of any other shape and texture that may enhance the ability of the chase vehicle's vision system to analyze information pertinent to velocity, attitude, and roll of the target platform. Any movement of the image, whether planned or errant, will be translated by the vision system into synchronous adjustments throughout the vehicle approach path.

Kader, Jack B.↗

NASA NTRS2007

Design and Testing of an Unlimited Field-of-regard Synthetic Vision Head-worn Display for Commercial Aircraft Surface Operations

Experiments and flight tests have shown that a Head-Up Display (HUD) and a head-down, electronic moving map (EMM) can be enhanced with Synthetic Vision for airport surface operations. While great success in ground operations was demonstrated with a HUD, the research noted that two major HUD limitations during ground operations were their monochrome form and limited, fixed field of regard. A potential solution to these limitations found with HUDs may be emerging Head Worn Displays (HWDs). HWDs are small, lightweight full color display devices that may be worn without significant encumbrance to the user. By coupling the HWD with a head tracker, unlimited field-of-regard may be realized for commercial aviation applications. In the proposed paper, the results of two ground simulation experiments conducted at NASA Langley are summarized. The experiments evaluated the efficacy of head-worn display applications of Synthetic Vision and Enhanced Vision technology to enhance transport aircraft surface operations. The two studies tested a combined six display concepts: (1) paper charts with existing cockpit displays, (2) baseline consisting of existing cockpit displays including a Class III electronic flight bag display of the airport surface; (3) an advanced baseline that also included displayed traffic and routing information, (4) a modified version of a HUD and EMM display demonstrated in previous research; (5) an unlimited field-of-regard, full color, head-tracked HWD with a conformal 3-D synthetic vision surface view; and (6) a fully integrated HWD concept. The fully integrated HWD concept is a head-tracked, color, unlimited field-of-regard concept that provides a 3-D conformal synthetic view of the airport surface integrated with advanced taxi route clearance, taxi precision guidance, and data-link capability. The results of the experiments showed that the fully integrated HWD provided greater path performance compared to using paper charts alone. Further, when comparing the HWD with the HUD concept, there were no differences in path performance. In addition, the HWD and HUD concepts were rated via paired-comparisons the same in terms of situational awareness and workload. However, there were over twice as many taxi incursion events with the HUD than the HWD.

Arthur, Jarvis J., III↗

NASA NTRS1986

Flight evaluation of a precision landing task for a powered-lift STOL aircraft

A flight research experiment was conducted with the NASA-Ames Research Center's Quiet Short-Haul Research Aircraft to determine the factors which influence the touchdown distribution for a powered-lift STOL aircraft. The pilots were given two tasks for each of a series of precision approaches flown using a microwave landing system (MLS) in simulated instrument meteorological conditions. They flew the aircraft, with forward vision obscured by a screen, to a 100-ft decision height using a flightpath-oriented, color electronic display and one of four levels of control augmentation. Approaches were flown along a nominal 6 deg glidepath, as well as to calibrated offsets at the decision height to establish a variety of initial conditions for the landing task. The screen was removed at the decision height and the pilot was briefed to land in a 200 foot touchdown zone of the STOLport with a sink rate less than 5 ft/sec. Statistical performance envelopes and pilot ratings are used to describe the results of this experiment. The data generated are expected to be useful for establishing STOL aircraft operating requirements and STOL MLS approach criteria.

Watson, D. M.↗

NASA NTRS1993

High Tech Art: Chameleon Glass

Dichroic Glass is a technology wherein extremely thin films of metal are vacuum deposited on a glass surface. The coated glass shields spacecraft instruments from cosmic radiation and protects human vision from unfiltered sunlight in space. Because the coating process allows some wavelengths of light and color to reflect and others to pass through, a chameleon effect is produced. Murray Schwartz, a former aerospace engineer, has based his business KROMA on this NASA optical technology. He produces dichroic stained glass windows, mobiles and jewelry. The technique involves deposition of super thin layers of metal oxides applied one layer at a time in a specific order and thickness for the desired effect. His product line is unique and has been very successful.

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DOE OSTI2025

Automated Waterbox Inspection for Nuclear Power Plants Using Computer Vision - Based Change Detection

Nuclear power plant waterboxes require regular inspection for leaks, missing components, and structural damage during maintenance outages. Traditional manual inspection is time-consuming and poses safety risks from confined space entry. We developed an automated computer vision system for drone-based waterbox inspection in partnership with Florida Light and Power. Our approach uses feature detection and matching to identify critical changes between baseline and current inspection images, automatically flagging additions (leaks/debris), removals (missing plugs), and translations (displaced components) while compensating for drone movement and environmental variations. We systematically evaluated six feature matching methods, from classical approaches (SIFT+BF) to state-of-the-art neural networks (SuperPoint+SuperGlue), using both standard benchmarks (HPatches) and waterbox-specific validation with real-world augmentations. SuperPoint+SuperGlue achieved superior performance with 7.82 pixels RMSE and 100% success rate—2.8x better accuracy than our baseline. While the pre-trained model has commercial licensing restrictions for nuclear deployment, our findings validate this architecture for custom training. We implemented a real-time GUI demonstrating the SIFT+BF approach for immediate deployment, processing drone feeds at 30 FPS with color-coded change visualization. Future work includes training a custom SuperPoint+SuperGlue model on waterbox data and integrating Vision-Language Models for automated reporting and maintenance guidance.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

NASA NTRS1992

Comparison of central axis and jet ring coolant supply for turbine disk cooling on a SSME-HPOTP model

The test facility, test methods and results are presented for an experimental study modeling the cooling of turbine disks in the blade attachment regions with multiple impinging jets, in a configuration simulating the disk cooling method employed on the Space Shuttle Main Engine oxygen turbopump. The study's objective was to provide a comparison of detailed local convection heat transfer rates obtained for a single center-supply of disk coolant with those obtained with the present flight configuration where disk coolant is supplied through an array of 19 jets located near the disk outer radius. Specially constructed disk models were used in a program designed to evaluate possible benefits and identify any possible detrimental effects involved in employing an alternate disk cooling scheme. The study involved the design, construction and testing of two full scale rotating model disks, one plane and smooth for baseline testing and the second contoured to the present flight configuration, together with the corresponding plane and contoured stator disks. Local heat transfer rates are determined from the color display of encapsulated liquid crystals coated on the disk in conjunction with use of a computer vision system. The test program was composed of a wide variety of disk speeds, flowrates, and geometrical configurations, including testing for the effects of disk boltheads and gas ingestion from the gas path region radially outboard of the disk-cavity.

Kim, Y. W.↗

DOE OSTI2024

In Search of Optimum Fresh-Cut Raw Material: Using Computer Vision Systems as a Sensory Screening Tool for Browning-Resistant Romaine Lettuce Accessions

The popularity of ready-to-eat (RTE) salads has prompted novel technology to prolong the shelf life of their ingredients. Fresh-cut romaine lettuce is widely used in RTE salads; however, its tendency to quickly discolor continues to be a challenge for the industry. Selecting the ideal lettuce accessions for use in RTE salads is essential to ensure maximum shelf life, and it is critical to have a practical way to assess and compare the quality of multiple lettuce accessions that are being considered for use in fresh-cut applications. Thus, in this work we aimed to determine whether a computer vision system (CVS) composed of image acquisition, processing, and analysis could be effective to detect visual quality differences among 16 accessions of fresh-cut romaine lettuce during postharvest storage. The CVS involved a post-capturing color correction, effective image segmentation, and calculation of a browning index, which was tested as a predictor of quality and shelf life of fresh-cut romaine lettuce. The results demonstrated that machine vision software can be implemented to replace or supplement the scoring of a trained panel and instrumental quality measurements. Overall visual quality, a key sensory parameter that determines food preferences and consumer behavior, was highly correlated with the browning index, with a Pearson correlation coefficient of −0.85. Other important sensory decision parameters were also strongly or moderately correlated with the browning index, with Pearson correlation coefficients of −0.84 for freshness, 0.79 for off odor, and 0.57 for browning. The ranking of the accessions according to quality acceptability from the sensory evaluation produced a similar pattern to those obtained with the CVS. This study revealed that multiple lettuce accessions can be effectively benchmarked for their performance as fresh-cut sources via a CVS-based method. Future opportunities and challenges in using machine vision image processing to predict consumer preferences for RTE salad greens is also discussed.

Agriculture↗

NASA NTRS1991

Digital visual communications using a Perceptual Components Architecture

The next era of space exploration will generate extraordinary volumes of image data, and management of this image data is beyond current technical capabilities. We propose a strategy for coding visual information that exploits the known properties of early human vision. This Perceptual Components Architecture codes images and image sequences in terms of discrete samples from limited bands of color, spatial frequency, orientation, and temporal frequency. This spatiotemporal pyramid offers efficiency (low bit rate), variable resolution, device independence, error-tolerance, and extensibility.

Watson, Andrew B.↗

DOE OSTI2020

Vegetation Detection Using Deep Learning and Conventional Methods

Land cover classification with the focus on chlorophyll-rich vegetation detection plays an important role in urban growth monitoring and planning, autonomous navigation, drone mapping, biodiversity conservation, etc. Conventional approaches usually apply the normalized difference vegetation index (NDVI) for vegetation detection. In this paper, we investigate the performance of deep learning and conventional methods for vegetation detection. Two deep learning methods, DeepLabV3+ and our customized convolutional neural network (CNN) were evaluated with respect to their detection performance when training and testing datasets originated from different geographical sites with different image resolutions. A novel object-based vegetation detection approach, which utilizes NDVI, computer vision, and machine learning (ML) techniques, is also proposed. The vegetation detection methods were applied to high-resolution airborne color images which consist of RGB and near-infrared (NIR) bands. RGB color images alone were also used with the two deep learning methods to examine their detection performances without the NIR band. The detection performances of the deep learning methods with respect to the object-based detection approach are discussed and sample images from the datasets are used for demonstrations.

58 GEOSCIENCES↗