Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Machine vision”

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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Monocular Ranging for Small Unmanned Aerial Systems in the Far-Field

Recent proliferation of small Unmanned Aerial Systems (sUAS) applications requires onboard collision avoidance systems to mitigate the risk of collision with non-cooperative aircraft and manned aircraft, which may not see sUAS in time to perform an avoidance maneuver. An attractive avenue for onboard collision avoidance is the utilization of machine vision cameras due to their low size, weight and power (SWaP) requirements. In this paper, we characterize the range performance of a machine vision system developed in-house and mounted onto an sUAS. The technique was designed to estimate the performance of a sense-and-avoid system to ensure that the sensing components meet the well-clear requirements for the chosen platform and avoidance strategy. Experimental flight-test data was acquired from test-flights flown along multiple collision geometries for two intruders: a general Aviation (GA) aircraft and a fixed-wing sUAS. The ownship and both intruders were instrumented with inertial navigation systems (INS) recording position and attitude information. The range at first detection, 𝑹𝟎, was extracted from in-flight imagery of head-on collision course geometry synchronized with INS data from both aircraft and ground-truth values extracted from the raw imagery. This initial detection distance, 𝑹𝟎, scales with atmospheric attenuation. Therefore, under clear sky conditions, the derived 𝑹𝟎 value represents the upper bound on the detection range achievable by the test configuration of the detector. Results indicate that the maximum initial detection distance for a 4k resolution action camera fitted with a 41º Field of View (FOV) lens is 2.763 ± 0.037 km for a GA aircraft and 0.881 ± 0.061 km for a fixed-wing sUAS, respectively. The in results this study suggest that a vision-based detect and track system may be analyzed using the sensor characterization and contextualized within aircraft well-clear volumes.

Chester V. Dolph↗
DOE OSTI2024

Anti-distortion bioinspired camera with an inhomogeneous photo-pixel array

The bioinspired camera, comprising a single lens and a curved image sensor—a photodiode array on a curved surface—, was born of flexible electronics. Its economical build lends itself well to space-constrained machine vision applications. The curved sensor, much akin to the retina, helps image focusing, but the curvature also creates a problem of image distortion, which can undermine machine vision tasks such as object recognition. Here we report an anti-distortion single-lens camera, where 4096 silicon photodiodes arrayed on a curved surface in a nonuniform pattern assimilated to the distorting optics are the key to anti-distortion engineering. That is, the photo-pixel distribution pattern itself is warped in the same manner as images are warped, which correctively reverses distortion. Acquired images feature no appreciable distortion across a 120° horizontal view, as confirmed by their neural-network recognition accuracies. This distortion correction via photo-pixel array reconfiguration is a form of in-sensor computing.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS2006

Identification Of Cells With A Compact Microscope Imaging System With Intelligent Controls

A Microscope Imaging System (CMIS) with intelligent controls is disclosed that provides techniques for scanning, identifying, detecting and tracking mic?oscopic changes in selected characteristics or features of various surfaces including, but not limited to, cells, spheres, and manufactured products subject to difficult-to-see imperfections. The practice of the present invention provides applications that include colloidal hard spheres experiments, biological cell detection for patch clamping, cell movement and tracking, as well as defect identification in products, such as semiconductor devices, where surface damage can be significant, but difficult to detect. The CMIS system is a machine vision system, which combines intelligent image processing with remote control capabilities and provides the ability to autofocus on a microscope sample, automatically scan an image, and perform machine vision analysis on multiple samples simultaneously.

McDowell, Mark↗
NASA NTRS2006

Operation of a Cartesian Robotic System in a Compact Microscope with Intelligent Controls

A Microscope Imaging System (CMIS) with intelligent controls is disclosed that provides techniques for scanning, identifying, detecting and tracking microscopic changes in selected characteristics or features of various surfaces including, but not limited to, cells, spheres, and manufactured products subject to difficult-to-see imperfections. The practice of the present invention provides applications that include colloidal hard spheres experiments, biological cell detection for patch clamping, cell movement and tracking, as well as defect identification in products, such as semiconductor devices, where surface damage can be significant, but difficult to detect. The CMIS system is a machine vision system, which combines intelligent image processing with remote control capabilities and provides the ability to autofocus on a microscope sample, automatically scan an image, and perform machine vision analysis on multiple samples simultaneously.

McDowell, Mark↗
NASA NTRS2007

Tracking of Cells with a Compact Microscope Imaging System with Intelligent Controls

A Microscope Imaging System (CMIS) with intelligent controls is disclosed that provides techniques for scanning, identifying, detecting and tracking microscopic changes in selected characteristics or features of various surfaces including, but not limited to, cells, spheres, and manufactured products subject to difficult-to-see imperfections. The practice of the present invention provides applications that include colloidal hard spheres experiments, biological cell detection for patch clamping, cell movement and tracking, as well as defect identification in products, such as semiconductor devices, where surface damage can be significant, but difficult to detect. The CMIS system is a machine vision system, which combines intelligent image processing with remote control capabilities and provides the ability to autofocus on a microscope sample, automatically scan an image, and perform machine vision analysis on multiple samples simultaneously

McDowell, Mark↗
NASA NTRS2007

Tracking of cells with a compact microscope imaging system with intelligent controls

A Microscope Imaging System (CMIS) with intelligent controls is disclosed that provides techniques for scanning, identifying, detecting and tracking microscopic changes in selected characteristics or features of various surfaces including, but not limited to, cells, spheres, and manufactured products subject to difficult-to-see imperfections. The practice of the present invention provides applications that include colloidal hard spheres experiments, biological cell detection for patch clamping, cell movement and tracking, as well as defect identification in products, such as semiconductor devices, where surface damage can be significant, but difficult to detect. The CMIS system is a machine vision system, which combines intelligent image processing with remote control capabilities and provides the ability to auto-focus on a microscope sample, automatically scan an image, and perform machine vision analysis on multiple samples simultaneously.

McDowell, Mark↗
NASA NTRS1990

The JPL/KSC telerobotic inspection demonstration

An ASEA IRB90 robotic manipulator with attached inspection cameras was moved through a Space Shuttle Payload Assist Module (PAM) Cradle under computer control. The Operator and Operator Control Station, including graphics simulation, gross-motion spatial planning, and machine vision processing, were located at JPL. The Safety and Support personnel, PAM Cradle, IRB90, and image acquisition system, were stationed at the Kennedy Space Center (KSC). Images captured at KSC were used both for processing by a machine vision system at JPL, and for inspection by the JPL Operator. The system found collision-free paths through the PAM Cradle, demonstrated accurate knowledge of the location of both objects of interest and obstacles, and operated with a communication delay of two seconds. Safe operation of the IRB90 near Shuttle flight hardware was obtained both through the use of a gross-motion spatial planner developed at JPL using artificial intelligence techniques, and infrared beams and pressure sensitive strips mounted to the critical surfaces of the flight hardward at KSC. The Demonstration showed that telerobotics is effective for real tasks, safe for personnel and hardware, and highly productive and reliable for Shuttle payload operations and Space Station external operations.

Mittman, David↗
NASA NTRS1991

Autonomous pre-alignment of a docking mechanism

The subject project can be described as the development and testing of a digitally controlled docking mechanism. The mechanism consists of a 6 DOF parallel manipulator for docking interface pre-alignment, and a machine vision sensor for real-time target tracking. The parallel manipulator also can be used for capture/latching, energy attenuation, and structural rigidization of docking, but the scope of this paper is the proof-of-concept demonstration of autonomous pre-alignment of a docking mechanism using machine vision.

Carroll, Monty B.↗
NASA NTRS1989

Local intensity adaptive image coding

The objective of preprocessing for machine vision is to extract intrinsic target properties. The most important properties ordinarily are structure and reflectance. Illumination in space, however, is a significant problem as the extreme range of light intensity, stretching from deep shadow to highly reflective surfaces in direct sunlight, impairs the effectiveness of standard approaches to machine vision. To overcome this critical constraint, an image coding scheme is being investigated which combines local intensity adaptivity, image enhancement, and data compression. It is very effective under the highly variant illumination that can exist within a single frame or field of view, and it is very robust to noise at low illuminations. Some of the theory and salient features of the coding scheme are reviewed. Its performance is characterized in a simulated space application, the research and development activities are described.

Huck, Friedrich O.↗
NASA NTRS2005

Automated Counting of Particles To Quantify Cleanliness

A machine vision system, similar to systems used in microbiological laboratories to count cultured microbes, has been proposed for quantifying the cleanliness of nominally precisely cleaned hardware by counting residual contaminant particles. The system would include a microscope equipped with an electronic camera and circuitry to digitize the camera output, a personal computer programmed with machine-vision and interface software, and digital storage media. A filter pad, through which had been aspirated solvent from rinsing the hardware in question, would be placed on the microscope stage. A high-resolution image of the filter pad would be recorded. The computer would analyze the image and present a histogram of sizes of particles on the filter. On the basis of the histogram and a measure of the desired level of cleanliness, the hardware would be accepted or rejected. If the hardware were accepted, the image would be saved, along with other information, as a quality record. If the hardware were rejected, the histogram and ancillary information would be recorded for analysis of trends. The software would perceive particles that are too large or too numerous to meet a specified particle-distribution profile. Anomalous particles or fibrous material would be flagged for inspection.

Rhode, James↗
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

Multispectral Image Processing for Plants

The development of a machine vision system to monitor plant growth and health is one of three essential steps towards establishing an intelligent system capable of accurately assessing the state of a controlled ecological life support system for long-term space travel. Besides a network of sensors, simulators are needed to predict plant features, and artificial intelligence algorithms are needed to determine the state of a plant based life support system. Multispectral machine vision and image processing can be used to sense plant features, including health and nutritional status.

Miles, Gaines E.↗
NASA NTRS2009

Hardware Implementation of a Bilateral Subtraction Filter

A bilateral subtraction filter has been implemented as a hardware module in the form of a field-programmable gate array (FPGA). In general, a bilateral subtraction filter is a key subsystem of a high-quality stereoscopic machine vision system that utilizes images that are large and/or dense. Bilateral subtraction filters have been implemented in software on general-purpose computers, but the processing speeds attainable in this way even on computers containing the fastest processors are insufficient for real-time applications. The present FPGA bilateral subtraction filter is intended to accelerate processing to real-time speed and to be a prototype of a link in a stereoscopic-machine- vision processing chain, now under development, that would process large and/or dense images in real time and would be implemented in an FPGA. In terms that are necessarily oversimplified for the sake of brevity, a bilateral subtraction filter is a smoothing, edge-preserving filter for suppressing low-frequency noise. The filter operation amounts to replacing the value for each pixel with a weighted average of the values of that pixel and the neighboring pixels in a predefined neighborhood or window (e.g., a 9 9 window). The filter weights depend partly on pixel values and partly on the window size. The present FPGA implementation of a bilateral subtraction filter utilizes a 9 9 window. This implementation was designed to take advantage of the ability to do many of the component computations in parallel pipelines to enable processing of image data at the rate at which they are generated. The filter can be considered to be divided into the following parts (see figure): a) An image pixel pipeline with a 9 9- pixel window generator, b) An array of processing elements; c) An adder tree; d) A smoothing-and-delaying unit; and e) A subtraction unit. After each 9 9 window is created, the affected pixel data are fed to the processing elements. Each processing element is fed the pixel value for its position in the window as well as the pixel value for the central pixel of the window. The absolute difference between these two pixel values is calculated and used as an address in a lookup table. Each processing element has a lookup table, unique for its position in the window, containing the weight coefficients for the Gaussian function for that position. The pixel value is multiplied by the weight, and the outputs of the processing element are the weight and pixel-value weight product. The products and weights are fed to the adder tree. The sum of the products and the sum of the weights are fed to the divider, which computes the sum of products the sum of weights. The output of the divider is denoted the bilateral smoothed image. The smoothing function is a simple weighted average computed over a 3 3 subwindow centered in the 9 9 window. After smoothing, the image is delayed by an additional amount of time needed to match the processing time for computing the bilateral smoothed image. The bilateral smoothed image is then subtracted from the 3 3 smoothed image to produce the final output. The prototype filter as implemented in a commercially available FPGA processes one pixel per clock cycle. Operation at a clock speed of 66 MHz has been demonstrated, and results of a static timing analysis have been interpreted as suggesting that the clock speed could be increased to as much as 100 MHz.

Huertas, Andres↗
NASA NTRS2003

Sonoluminescence Bubble Measurements using Vision-Based Algorithms

Vision-based measurement methods were used to measure bubble sizes in this sonoluminescence experiment. Bubble imaging was accomplished by placing the bubble between a bright light source and a microscope-CCD camera system. A collimated light-emitting diode was operated in a pulsed model with an adjustable time delay with respect to the piezo-electric transducer drive signal. The light-emitting diode produced a bubble shadowgraph consisting of a multiple exposure made by numerous light pulses imaged onto a charge-couple device camera. Each image was transferred from the camera to a computer-controlled machine vision system via a frame grabber. The frame grabber was equipped with on-board memory to accomodate sequential image buffering while images were transferred to the host processor and analyzed. This configuration allowed the host computer to perform diameter measurements, centroid position measurements and shape estimation in "real-time" as the next image was being acquired. Bubble size measurement accuracy with an uncertainty of 3 microns was achieved using standard lenses and machine vision algorithms. Bubble centroid position accuracy was also within the 3 micron tolerance of the vision system. This uncertainty estimation accounted for the optical spatial resolution, digitization errors and the edge detection algorithm accuracy. The vision algorithms include camera calibration, thresholding, edge detection, edge position determination, distance between two edges computations and centroid position computations.

Hall, Nancy R.↗
DOE OSTI2025

Integrating Machine-learning-assisted Computer Vision with RICH System

Developments in artificial intelligence have vastly expanded the capabilities of robots. Currently, the Spallation Neutron Source (SNS) beamlines at Oak Ridge National Lab (ORNL) have robotic sample loaders to increase the efficiency of running experiments. However, they require retraining if anything about the situation changes, e.g., where the samples are, and cannot notice if errors occur. So, the viability of using computer vision and machine learning to enhance these sample loaders’ functionality was investigated. In this project, the RICH system with a Dobot CR3 6-axis robot present at the VULCAN beamline assisted by an Intel Realsense D435i camera, a unique camera that enables convenient translation of 2D pixel coordinates to 3D world points, was programmed to load ceramic crucibles into a thermogravimetric analyzer (TGA) furnace. An algorithm was constructed in Python with three major phases planned: (1) obtaining a sample, (2) moving it to the target location, and then (3) bringing the sample back to its original location once the experiment finished. In the first phase, the algorithm would dynamically detect sample locations using ArUco markers to recognize the samples’ general location and a custom-trained yolov5 object detection model to locate the crucibles’ centers. Afterward, the robot would be directed to pick up samples based on the crucibles’ calculated positions. In the second phase, the robot would move the sample to a secondary point, reorient its grip, and place the sample at the target location. In the final phase, the robot would determine whether the sample was intact and would bring it back to its original place if it was or raise an alarm. Using this algorithm, the robot was able to pick up different types of crucibles at varying positions. These results indicate that integrating machine-learning-assisted computer vision with robotic sample loaders can result in effective autonomous detection of samples.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

Real-time model-based vision system for object acquisition and tracking

A machine vision system is described which is designed to acquire and track polyhedral objects moving and rotating in space by means of two or more cameras, programmable image-processing hardware, and a general-purpose computer for high-level functions. The image-processing hardware is capable of performing a large variety of operations on images and on image-like arrays of data. Acquisition utilizes image locations and velocities of the features extracted by the image-processing hardware to determine the three-dimensional position, orientation, velocity, and angular velocity of the object. Tracking correlates edges detected in the current image with edge locations predicted from an internal model of the object and its motion, continually updating velocity information to predict where edges should appear in future frames. With some 10 frames processed per second, real-time tracking is possible.

Wilcox, Brian↗
NASA NTRS1994

Technology for Robotic Surface Inspection in Space

This paper presents on-going esearch in robotic ispeciton of space platforms. Three main area of investigation are discussed: machine-vision inspection techniques, an integrated sensor end-effector, and an orbital environment laboratory simulation.

robotic↗
NASA NTRS1993

Vision-based aircraft guidance

Early research on the development of machine vision algorithms to serve as pilot aids in aircraft flight operations is discussed. The research is useful for synthesizing new cockpit instrumentation that can enhance flight safety and efficiency. With the present work as the basis, future research will produce low-cost instrument by integrating a conventional TV camera together with off-the=shelf digitizing hardware for flight test verification. Initial focus of the research will be on developing pilot aids for clear-night operations. Latter part of the research will examine synthetic vision issues for poor visibility flight operations. Both research efforts will contribute towards the high-speed civil transport aircraft program. It is anticipated that the research reported here will also produce pilot aids for conducting helicopter flight operations during emergency search and rescue. The primary emphasis of the present research effort is on near-term, flight demonstrable technologies. This report discusses pilot aids for night landing and takeoff and synthetic vision as an aid to low visibility landing.

Menon, P. K.↗