Cooperative multisensor system for real-time face detection and tracking in uncontrolled conditions

NASA Astrophysics Data System (ADS)

Marchesotti, Luca; Piva, Stefano; Turolla, Andrea; Minetti, Deborah; Regazzoni, Carlo S.

2005-03-01

The presented work describes an innovative architecture for multi-sensor distributed video surveillance applications. The aim of the system is to track moving objects in outdoor environments with a cooperative strategy exploiting two video cameras. The system also exhibits the capacity of focusing its attention on the faces of detected pedestrians collecting snapshot frames of face images, by segmenting and tracking them over time at different resolution. The system is designed to employ two video cameras in a cooperative client/server structure: the first camera monitors the entire area of interest and detects the moving objects using change detection techniques. The detected objects are tracked over time and their position is indicated on a map representing the monitored area. The objects" coordinates are sent to the server sensor in order to point its zooming optics towards the moving object. The second camera tracks the objects at high resolution. As well as the client camera, this sensor is calibrated and the position of the object detected on the image plane reference system is translated in its coordinates referred to the same area map. In the map common reference system, data fusion techniques are applied to achieve a more precise and robust estimation of the objects" track and to perform face detection and tracking. The work novelties and strength reside in the cooperative multi-sensor approach, in the high resolution long distance tracking and in the automatic collection of biometric data such as a person face clip for recognition purposes.

Statistical Hypothesis Testing using CNN Features for Synthesis of Adversarial Counterexamples to Human and Object Detection Vision Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raj, Sunny; Jha, Sumit Kumar; Pullum, Laura L.

Validating the correctness of human detection vision systems is crucial for safety applications such as pedestrian collision avoidance in autonomous vehicles. The enormous space of possible inputs to such an intelligent system makes it difficult to design test cases for such systems. In this report, we present our tool MAYA that uses an error model derived from a convolutional neural network (CNN) to explore the space of images similar to a given input image, and then tests the correctness of a given human or object detection system on such perturbed images. We demonstrate the capability of our tool on themore » pre-trained Histogram-of-Oriented-Gradients (HOG) human detection algorithm implemented in the popular OpenCV toolset and the Caffe object detection system pre-trained on the ImageNet benchmark. Our tool may serve as a testing resource for the designers of intelligent human and object detection systems.« less

An object detection and tracking system for unmanned surface vehicles

NASA Astrophysics Data System (ADS)

Yang, Jian; Xiao, Yang; Fang, Zhiwen; Zhang, Naiwen; Wang, Li; Li, Tao

2017-10-01

Object detection and tracking are critical parts of unmanned surface vehicles(USV) to achieve automatic obstacle avoidance. Off-the-shelf object detection methods have achieved impressive accuracy in public datasets, though they still meet bottlenecks in practice, such as high time consumption and low detection quality. In this paper, we propose a novel system for USV, which is able to locate the object more accurately while being fast and stable simultaneously. Firstly, we employ Faster R-CNN to acquire several initial raw bounding boxes. Secondly, the image is segmented to a few superpixels. For each initial box, the superpixels inside will be grouped into a whole according to a combination strategy, and a new box is thereafter generated as the circumscribed bounding box of the final superpixel. Thirdly, we utilize KCF to track these objects after several frames, Faster-RCNN is again used to re-detect objects inside tracked boxes to prevent tracking failure as well as remove empty boxes. Finally, we utilize Faster R-CNN to detect objects in the next image, and refine object boxes by repeating the second module of our system. The experimental results demonstrate that our system is fast, robust and accurate, which can be applied to USV in practice.

Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System

PubMed Central

Jung, Jaehoon; Yoon, Inhye; Paik, Joonki

2016-01-01

This paper presents an object occlusion detection algorithm using object depth information that is estimated by automatic camera calibration. The object occlusion problem is a major factor to degrade the performance of object tracking and recognition. To detect an object occlusion, the proposed algorithm consists of three steps: (i) automatic camera calibration using both moving objects and a background structure; (ii) object depth estimation; and (iii) detection of occluded regions. The proposed algorithm estimates the depth of the object without extra sensors but with a generic red, green and blue (RGB) camera. As a result, the proposed algorithm can be applied to improve the performance of object tracking and object recognition algorithms for video surveillance systems. PMID:27347978

Radar signal pre-processing to suppress surface bounce and multipath

DOEpatents

Paglieroni, David W; Mast, Jeffrey E; Beer, N. Reginald

2013-12-31

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes that return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Spatially assisted down-track median filter for GPR image post-processing

DOEpatents

Paglieroni, David W; Beer, N Reginald

2014-10-07

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Spatially adaptive migration tomography for multistatic GPR imaging

DOEpatents

Paglieroni, David W; Beer, N. Reginald

2013-08-13

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Synthetic aperture integration (SAI) algorithm for SAR imaging

DOEpatents

Chambers, David H; Mast, Jeffrey E; Paglieroni, David W; Beer, N. Reginald

2013-07-09

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Zero source insertion technique to account for undersampling in GPR imaging

DOEpatents

Chambers, David H; Mast, Jeffrey E; Paglieroni, David W

2014-02-25

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Demonstration of Uncued Optical Surveillance of LEO

NASA Astrophysics Data System (ADS)

Zimmer, P.; Ackermann, M.; McGraw, J.

2014-09-01

J.T. McGraw and Associates, LLC, in collaboration with the University of New Mexico (UNM), has built and is operating two proof-of-concept wide-field imaging systems to test novel techniques for uncued surveillance of LEO. The imaging systems are built from off-the-shelf optics and detectors resulting in a 350mm aperture and a 6 square degree field of view. For streak detection, field of view is of critical importance because the maximum exposure time on the object is limited by its crossing time and measurements of apparent angular motion are better constrained with longer streaks. The current match of the detector to the optical system is optimized for detection of objects at altitudes above 450km, which for a circular orbit, corresponds to apparent motions of approximately 1 deg./sec. Using our GPU-accelerated detection scheme, the proof-of-concept systems have detected objects fainter than V=12.3, which approximately corresponds to a 24 cm object at 1000 km altitude at better than 6 sigma significance, from sites near and within Albuquerque, NM. This work demonstrates scalable optical systems designed for near real time detection of fast moving objects, which can be then handed off to other instruments capable of tracking and characterizing them. The two proof-of-concept systems, separated by ~30km, work together by taking simultaneous images of the same orbital volume to constrain the orbits of detected objects using parallax measurements. These detections are followed-up by photometric observations taken at UNM to independently assess the objects and the quality of the derived orbits. We believe this demonstrates the potential of small telescope arrays for detecting and cataloguing heretofore unknown LEO objects.

Edge detection based on computational ghost imaging with structured illuminations

NASA Astrophysics Data System (ADS)

Yuan, Sheng; Xiang, Dong; Liu, Xuemei; Zhou, Xin; Bing, Pibin

2018-03-01

Edge detection is one of the most important tools to recognize the features of an object. In this paper, we propose an optical edge detection method based on computational ghost imaging (CGI) with structured illuminations which are generated by an interference system. The structured intensity patterns are designed to make the edge of an object be directly imaged from detected data in CGI. This edge detection method can extract the boundaries for both binary and grayscale objects in any direction at one time. We also numerically test the influence of distance deviations in the interference system on edge extraction, i.e., the tolerance of the optical edge detection system to distance deviation. Hopefully, it may provide a guideline for scholars to build an experimental system.

A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments.

PubMed

Al-Nawashi, Malek; Al-Hazaimeh, Obaida M; Saraee, Mohamad

2017-01-01

Abnormal activity detection plays a crucial role in surveillance applications, and a surveillance system that can perform robustly in an academic environment has become an urgent need. In this paper, we propose a novel framework for an automatic real-time video-based surveillance system which can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment. To develop our system, we have divided the work into three phases: preprocessing phase, abnormal human activity detection phase, and content-based image retrieval phase. For motion object detection, we used the temporal-differencing algorithm and then located the motions region using the Gaussian function. Furthermore, the shape model based on OMEGA equation was used as a filter for the detected objects (i.e., human and non-human). For object activities analysis, we evaluated and analyzed the human activities of the detected objects. We classified the human activities into two groups: normal activities and abnormal activities based on the support vector machine. The machine then provides an automatic warning in case of abnormal human activities. It also embeds a method to retrieve the detected object from the database for object recognition and identification using content-based image retrieval. Finally, a software-based simulation using MATLAB was performed and the results of the conducted experiments showed an excellent surveillance system that can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment with no human intervention.

Security Applications Of Computer Motion Detection

NASA Astrophysics Data System (ADS)

Bernat, Andrew P.; Nelan, Joseph; Riter, Stephen; Frankel, Harry

1987-05-01

An important area of application of computer vision is the detection of human motion in security systems. This paper describes the development of a computer vision system which can detect and track human movement across the international border between the United States and Mexico. Because of the wide range of environmental conditions, this application represents a stringent test of computer vision algorithms for motion detection and object identification. The desired output of this vision system is accurate, real-time locations for individual aliens and accurate statistical data as to the frequency of illegal border crossings. Because most detection and tracking routines assume rigid body motion, which is not characteristic of humans, new algorithms capable of reliable operation in our application are required. Furthermore, most current detection and tracking algorithms assume a uniform background against which motion is viewed - the urban environment along the US-Mexican border is anything but uniform. The system works in three stages: motion detection, object tracking and object identi-fication. We have implemented motion detection using simple frame differencing, maximum likelihood estimation, mean and median tests and are evaluating them for accuracy and computational efficiency. Due to the complex nature of the urban environment (background and foreground objects consisting of buildings, vegetation, vehicles, wind-blown debris, animals, etc.), motion detection alone is not sufficiently accurate. Object tracking and identification are handled by an expert system which takes shape, location and trajectory information as input and determines if the moving object is indeed representative of an illegal border crossing.

Wavelet Fusion for Concealed Object Detection Using Passive Millimeter Wave Sequence Images

NASA Astrophysics Data System (ADS)

Chen, Y.; Pang, L.; Liu, H.; Xu, X.

2018-04-01

PMMW imaging system can create interpretable imagery on the objects concealed under clothing, which gives the great advantage to the security check system. Paper addresses wavelet fusion to detect concealed objects using passive millimeter wave (PMMW) sequence images. According to PMMW real-time imager acquired image characteristics and storage methods firstly, using the sum of squared difference (SSD) as the image-related parameters to screen the sequence images. Secondly, the selected images are optimized using wavelet fusion algorithm. Finally, the concealed objects are detected by mean filter, threshold segmentation and edge detection. The experimental results show that this method improves the detection effect of concealed objects by selecting the most relevant images from PMMW sequence images and using wavelet fusion to enhance the information of the concealed objects. The method can be effectively applied to human body concealed object detection in millimeter wave video.

Objective-lens-free Fiber-based Position Detection with Nanometer Resolution in a Fiber Optical Trapping System.

PubMed

Ti, Chaoyang; Ho-Thanh, Minh-Tri; Wen, Qi; Liu, Yuxiang

2017-10-13

Position detection with high accuracy is crucial for force calibration of optical trapping systems. Most existing position detection methods require high-numerical-aperture objective lenses, which are bulky, expensive, and difficult to miniaturize. Here, we report an affordable objective-lens-free, fiber-based position detection scheme with 2 nm spatial resolution and 150 MHz bandwidth. This fiber based detection mechanism enables simultaneous trapping and force measurements in a compact fiber optical tweezers system. In addition, we achieved more reliable signal acquisition with less distortion compared with objective based position detection methods, thanks to the light guiding in optical fibers and small distance between the fiber tips and trapped particle. As a demonstration of the fiber based detection, we used the fiber optical tweezers to apply a force on a cell membrane and simultaneously measure the cellular response.

Detection of nuclei in 4D Nomarski DIC microscope images of early Caenorhabditis elegans embryos using local image entropy and object tracking

PubMed Central

Hamahashi, Shugo; Onami, Shuichi; Kitano, Hiroaki

2005-01-01

Background The ability to detect nuclei in embryos is essential for studying the development of multicellular organisms. A system of automated nuclear detection has already been tested on a set of four-dimensional (4D) Nomarski differential interference contrast (DIC) microscope images of Caenorhabditis elegans embryos. However, the system needed laborious hand-tuning of its parameters every time a new image set was used. It could not detect nuclei in the process of cell division, and could detect nuclei only from the two- to eight-cell stages. Results We developed a system that automates the detection of nuclei in a set of 4D DIC microscope images of C. elegans embryos. Local image entropy is used to produce regions of the images that have the image texture of the nucleus. From these regions, those that actually detect nuclei are manually selected at the first and last time points of the image set, and an object-tracking algorithm then selects regions that detect nuclei in between the first and last time points. The use of local image entropy makes the system applicable to multiple image sets without the need to change its parameter values. The use of an object-tracking algorithm enables the system to detect nuclei in the process of cell division. The system detected nuclei with high sensitivity and specificity from the one- to 24-cell stages. Conclusion A combination of local image entropy and an object-tracking algorithm enabled highly objective and productive detection of nuclei in a set of 4D DIC microscope images of C. elegans embryos. The system will facilitate genomic and computational analyses of C. elegans embryos. PMID:15910690

Vision System for Coarsely Estimating Motion Parameters for Unknown Fast Moving Objects in Space

PubMed Central

Chen, Min; Hashimoto, Koichi

2017-01-01

Motivated by biological interests in analyzing navigation behaviors of flying animals, we attempt to build a system measuring their motion states. To do this, in this paper, we build a vision system to detect unknown fast moving objects within a given space, calculating their motion parameters represented by positions and poses. We proposed a novel method to detect reliable interest points from images of moving objects, which can be hardly detected by general purpose interest point detectors. 3D points reconstructed using these interest points are then grouped and maintained for detected objects, according to a careful schedule, considering appearance and perspective changes. In the estimation step, a method is introduced to adapt the robust estimation procedure used for dense point set to the case for sparse set, reducing the potential risk of greatly biased estimation. Experiments are conducted against real scenes, showing the capability of the system of detecting multiple unknown moving objects and estimating their positions and poses. PMID:29206189

Implications for Planetary System Formation from Interstellar Object 1I/2017 U1 (‘Oumuamua)

NASA Astrophysics Data System (ADS)

Trilling, David E.; Robinson, Tyler; Roegge, Alissa; Chandler, Colin Orion; Smith, Nathan; Loeffler, Mark; Trujillo, Chad; Navarro-Meza, Samuel; Glaspie, Lori M.

2017-12-01

The recently discovered minor body 1I/2017 U1 (‘Oumuamua) is the first known object in our solar system that is not bound by the Sun’s gravity. Its hyperbolic orbit (eccentricity greater than unity) strongly suggests that it originated outside our solar system; its red color is consistent with substantial space weathering experienced over a long interstellar journey. We carry out a simple calculation of the probability of detecting such an object. We find that the observed detection rate of 1I-like objects can be satisfied if the average mass of ejected material from nearby stars during the process of planetary formation is ˜20 Earth masses, similar to the expected value for our solar system. The current detection rate of such interstellar interlopers is estimated to be 0.2 yr-1, and the expected number of detections over the past few years is almost exactly one. When the Large Synoptic Survey Telescope begins its wide, fast, deep all-sky survey, the detection rate will increase to 1 yr-1. Those expected detections will provide further constraints on nearby planetary system formation through a better estimate of the number and properties of interstellar objects.

Fusion of thermal- and visible-band video for abandoned object detection

NASA Astrophysics Data System (ADS)

Beyan, Cigdem; Yigit, Ahmet; Temizel, Alptekin

2011-07-01

Timely detection of packages that are left unattended in public spaces is a security concern, and rapid detection is important for prevention of potential threats. Because constant surveillance of such places is challenging and labor intensive, automated abandoned-object-detection systems aiding operators have started to be widely used. In many studies, stationary objects, such as people sitting on a bench, are also detected as suspicious objects due to abandoned items being defined as items newly added to the scene and remained stationary for a predefined time. Therefore, any stationary object results in an alarm causing a high number of false alarms. These false alarms could be prevented by classifying suspicious items as living and nonliving objects. In this study, a system for abandoned object detection that aids operators surveilling indoor environments such as airports, railway or metro stations, is proposed. By analysis of information from a thermal- and visible-band camera, people and the objects left behind can be detected and discriminated as living and nonliving, reducing the false-alarm rate. Experiments demonstrate that using data obtained from a thermal camera in addition to a visible-band camera also increases the true detection rate of abandoned objects.

Real-time Human Activity Recognition

NASA Astrophysics Data System (ADS)

Albukhary, N.; Mustafah, Y. M.

2017-11-01

The traditional Closed-circuit Television (CCTV) system requires human to monitor the CCTV for 24/7 which is inefficient and costly. Therefore, there’s a need for a system which can recognize human activity effectively in real-time. This paper concentrates on recognizing simple activity such as walking, running, sitting, standing and landing by using image processing techniques. Firstly, object detection is done by using background subtraction to detect moving object. Then, object tracking and object classification are constructed so that different person can be differentiated by using feature detection. Geometrical attributes of tracked object, which are centroid and aspect ratio of identified tracked are manipulated so that simple activity can be detected.

Real-time object detection, tracking and occlusion reasoning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Divakaran, Ajay; Yu, Qian; Tamrakar, Amir

A system for object detection and tracking includes technologies to, among other things, detect and track moving objects, such as pedestrians and/or vehicles, in a real-world environment, handle static and dynamic occlusions, and continue tracking moving objects across the fields of view of multiple different cameras.

Shadow Detection Based on Regions of Light Sources for Object Extraction in Nighttime Video

PubMed Central

Lee, Gil-beom; Lee, Myeong-jin; Lee, Woo-Kyung; Park, Joo-heon; Kim, Tae-Hwan

2017-01-01

Intelligent video surveillance systems detect pre-configured surveillance events through background modeling, foreground and object extraction, object tracking, and event detection. Shadow regions inside video frames sometimes appear as foreground objects, interfere with ensuing processes, and finally degrade the event detection performance of the systems. Conventional studies have mostly used intensity, color, texture, and geometric information to perform shadow detection in daytime video, but these methods lack the capability of removing shadows in nighttime video. In this paper, a novel shadow detection algorithm for nighttime video is proposed; this algorithm partitions each foreground object based on the object’s vertical histogram and screens out shadow objects by validating their orientations heading toward regions of light sources. From the experimental results, it can be seen that the proposed algorithm shows more than 93.8% shadow removal and 89.9% object extraction rates for nighttime video sequences, and the algorithm outperforms conventional shadow removal algorithms designed for daytime videos. PMID:28327515

Passive Optical Link Budget for LEO Space Surveillance

NASA Astrophysics Data System (ADS)

Wagner, P.; Hasenohr, T.; Hampf, D.; Sproll, F.; Humbert, L.; Rodmann, J.; Riede, W.

The rising space debris population is becoming an increasing risk for space assets. Even objects with the size of 10mm can cause major damages to active spacecraft. Especially the orbits around 800km high are densely populated with space debris objects. To assess the risk of collisions with active satellites, the Earth orbits need to be surveyed permanently. Space debris laser ranging systems for example can deliver highly accurate positional data for precise orbit determination. Therefor a priori information about the objects coarse trajectory is needed. Such initial orbit information can be provided by wide angle optical sensors. The Institute of Technical Physics at the German Aerospace Center in Stuttgart runs an observatory to perform passive as well as laser optical measurements to LEO objects. In order to detect unknown objects, a wide-angle imaging system with a field of view in the range of 5° to 15° equipped with an astronomical CCD camera and a commercial off the shelf (COTS) lens was designed to continuously observe the night sky for LEO objects. This paper presents the passive optical link budget for observing LEO objects to show the benefits and limits of the physical performance of an optical surveillance system. A compact COTS system is able to detect objects with a couple of decimeters in size while a large aperture telescope can detect objects with diameters below 10cm. Additionally, data captured by a passive optical staring system with a 10 cm aperture was analyzed. It is shown that 90% of all objects with a radar cross section larger than 2m² are detected with such a system during twilight conditions. The smallest detected LEO object with this system has a size of 0.32m x 0.32m x 0.26m. These measurements are compared to the developed link budget which allows an estimation of the performance of larger systems.

Real-Time Optical Surveillance of LEO/MEO with Small Telescopes

NASA Astrophysics Data System (ADS)

Zimmer, P.; McGraw, J.; Ackermann, M.

J.T. McGraw and Associates, LLC operates two proof-of-concept wide-field imaging systems to test novel techniques for uncued surveillance of LEO/MEO/GEO and, in collaboration with the University of New Mexico (UNM), uses a third small telescope for rapidly queued same-orbit follow-up observations. Using our GPU-accelerated detection scheme, the proof-of-concept systems operating at sites near and within Albuquerque, NM, have detected objects fainter than V=13 at greater than 6 sigma significance. This detection approximately corresponds to a 16 cm object with albedo of 0.12 at 1000 km altitude. Dozens of objects are measured during each operational twilight period, many of which have no corresponding catalog object. The two proof-of-concept systems, separated by ~30km, work together by taking simultaneous images of the same orbital volume to constrain the orbits of detected objects using parallax measurements. These detections are followed-up by imaging photometric observations taken at UNM to confirm and further constrain the initial orbit determination and independently assess the objects and verify the quality of the derived orbits. This work continues to demonstrate that scalable optical systems designed for real-time detection of fast moving objects, which can be then handed off to other instruments capable of tracking and characterizing them, can provide valuable real-time surveillance data at LEO and beyond, which substantively informs the SSA process.

Accelerating object detection via a visual-feature-directed search cascade: algorithm and field programmable gate array implementation

NASA Astrophysics Data System (ADS)

Kyrkou, Christos; Theocharides, Theocharis

2016-07-01

Object detection is a major step in several computer vision applications and a requirement for most smart camera systems. Recent advances in hardware acceleration for real-time object detection feature extensive use of reconfigurable hardware [field programmable gate arrays (FPGAs)], and relevant research has produced quite fascinating results, in both the accuracy of the detection algorithms as well as the performance in terms of frames per second (fps) for use in embedded smart camera systems. Detecting objects in images, however, is a daunting task and often involves hardware-inefficient steps, both in terms of the datapath design and in terms of input/output and memory access patterns. We present how a visual-feature-directed search cascade composed of motion detection, depth computation, and edge detection, can have a significant impact in reducing the data that needs to be examined by the classification engine for the presence of an object of interest. Experimental results on a Spartan 6 FPGA platform for face detection indicate data search reduction of up to 95%, which results in the system being able to process up to 50 1024×768 pixels images per second with a significantly reduced number of false positives.

Visual Sensor Based Abnormal Event Detection with Moving Shadow Removal in Home Healthcare Applications

PubMed Central

Lee, Young-Sook; Chung, Wan-Young

2012-01-01

Vision-based abnormal event detection for home healthcare systems can be greatly improved using visual sensor-based techniques able to detect, track and recognize objects in the scene. However, in moving object detection and tracking processes, moving cast shadows can be misclassified as part of objects or moving objects. Shadow removal is an essential step for developing video surveillance systems. The goal of the primary is to design novel computer vision techniques that can extract objects more accurately and discriminate between abnormal and normal activities. To improve the accuracy of object detection and tracking, our proposed shadow removal algorithm is employed. Abnormal event detection based on visual sensor by using shape features variation and 3-D trajectory is presented to overcome the low fall detection rate. The experimental results showed that the success rate of detecting abnormal events was 97% with a false positive rate of 2%. Our proposed algorithm can allow distinguishing diverse fall activities such as forward falls, backward falls, and falling asides from normal activities. PMID:22368486

Object detection in MOUT: evaluation of a hybrid approach for confirmation and rejection of object detection hypotheses

NASA Astrophysics Data System (ADS)

Manger, Daniel; Metzler, Jürgen

2014-03-01

Military Operations in Urban Terrain (MOUT) require the capability to perceive and to analyze the situation around a patrol in order to recognize potential threats. A permanent monitoring of the surrounding area is essential in order to appropriately react to the given situation, where one relevant task is the detection of objects that can pose a threat. Especially the robust detection of persons is important, as in MOUT scenarios threats usually arise from persons. This task can be supported by image processing systems. However, depending on the scenario, person detection in MOUT can be challenging, e.g. persons are often occluded in complex outdoor scenes and the person detection also suffers from low image resolution. Furthermore, there are several requirements on person detection systems for MOUT such as the detection of non-moving persons, as they can be a part of an ambush. Existing detectors therefore have to operate on single images with low thresholds for detection in order to not miss any person. This, in turn, leads to a comparatively high number of false positive detections which renders an automatic vision-based threat detection system ineffective. In this paper, a hybrid detection approach is presented. A combination of a discriminative and a generative model is examined. The objective is to increase the accuracy of existing detectors by integrating a separate hypotheses confirmation and rejection step which is built by a discriminative and generative model. This enables the overall detection system to make use of both the discriminative power and the capability to detect partly hidden objects with the models. The approach is evaluated on benchmark data sets generated from real-world image sequences captured during MOUT exercises. The extension shows a significant improvement of the false positive detection rate.

Detection and Tracking of Dynamic Objects by Using a Multirobot System: Application to Critical Infrastructures Surveillance

PubMed Central

Rodríguez-Canosa, Gonzalo; Giner, Jaime del Cerro; Barrientos, Antonio

2014-01-01

The detection and tracking of mobile objects (DATMO) is progressively gaining importance for security and surveillance applications. This article proposes a set of new algorithms and procedures for detecting and tracking mobile objects by robots that work collaboratively as part of a multirobot system. These surveillance algorithms are conceived of to work with data provided by long distance range sensors and are intended for highly reliable object detection in wide outdoor environments. Contrary to most common approaches, in which detection and tracking are done by an integrated procedure, the approach proposed here relies on a modular structure, in which detection and tracking are carried out independently, and the latter might accept input data from different detection algorithms. Two movement detection algorithms have been developed for the detection of dynamic objects by using both static and/or mobile robots. The solution to the overall problem is based on the use of a Kalman filter to predict the next state of each tracked object. Additionally, new tracking algorithms capable of combining dynamic objects lists coming from either one or various sources complete the solution. The complementary performance of the separated modular structure for detection and identification is evaluated and, finally, a selection of test examples discussed. PMID:24526305

Positron emission imaging device and method of using the same

DOEpatents

Bingham, Philip R.; Mullens, James Allen

2013-01-15

An imaging system and method of imaging are disclosed. The imaging system can include an external radiation source producing pairs of substantially simultaneous radiation emissions of a picturization emission and a verification emissions at an emission angle. The imaging system can also include a plurality of picturization sensors and at least one verification sensor for detecting the picturization and verification emissions, respectively. The imaging system also includes an object stage is arranged such that a picturization emission can pass through an object supported on said object stage before being detected by one of said plurality of picturization sensors. A coincidence system and a reconstruction system can also be included. The coincidence can receive information from the picturization and verification sensors and determine whether a detected picturization emission is direct radiation or scattered radiation. The reconstruction system can produce a multi-dimensional representation of an object imaged with the imaging system.

Methods, systems and devices for detecting threatening objects and for classifying magnetic data

DOEpatents

Kotter, Dale K [Shelley, ID; Roybal, Lyle G [Idaho Falls, ID; Rohrbaugh, David T [Idaho Falls, ID; Spencer, David F [Idaho Falls, ID

2012-01-24

A method for detecting threatening objects in a security screening system. The method includes a step of classifying unique features of magnetic data as representing a threatening object. Another step includes acquiring magnetic data. Another step includes determining if the acquired magnetic data comprises a unique feature.

Eddy Current System and Method for Crack Detection

NASA Technical Reports Server (NTRS)

Wincheski, Russell A. (Inventor); Simpson, John W. (Inventor)

2012-01-01

An eddy current system and method enables detection of sub-surface damage in a cylindrical object. The invention incorporates a dual frequency, orthogonally wound eddy current probe mounted on a stepper motor-controlled scanning system. The system is designed to inspect for outer surface damage from the interior of the cylindrical object.

Detection of buried magnetic objects by a SQUID gradiometer system

NASA Astrophysics Data System (ADS)

Meyer, Hans-Georg; Hartung, Konrad; Linzen, Sven; Schneider, Michael; Stolz, Ronny; Fried, Wolfgang; Hauspurg, Sebastian

2009-05-01

We present a magnetic detection system based on superconducting gradiometric sensors (SQUID gradiometers). The system provides a unique fast mapping of large areas with a high resolution of the magnetic field gradient as well as the local position. A main part of this work is the localization and classification of magnetic objects in the ground by automatic interpretation of geomagnetic field gradients, measured by the SQUID system. In accordance with specific features the field is decomposed into segments, which allow inferences to possible objects in the ground. The global consideration of object describing properties and their optimization using error minimization methods allows the reconstruction of superimposed features and detection of buried objects. The analysis system of measured geomagnetic fields works fully automatically. By a given surface of area-measured gradients the algorithm determines within numerical limits the absolute position of objects including depth with sub-pixel accuracy and allows an arbitrary position and attitude of sources. Several SQUID gradiometer data sets were used to show the applicability of the analysis algorithm.

Object Detection Applied to Indoor Environments for Mobile Robot Navigation.

PubMed

Hernández, Alejandra Carolina; Gómez, Clara; Crespo, Jonathan; Barber, Ramón

2016-07-28

To move around the environment, human beings depend on sight more than their other senses, because it provides information about the size, shape, color and position of an object. The increasing interest in building autonomous mobile systems makes the detection and recognition of objects in indoor environments a very important and challenging task. In this work, a vision system to detect objects considering usual human environments, able to work on a real mobile robot, is developed. In the proposed system, the classification method used is Support Vector Machine (SVM) and as input to this system, RGB and depth images are used. Different segmentation techniques have been applied to each kind of object. Similarly, two alternatives to extract features of the objects are explored, based on geometric shape descriptors and bag of words. The experimental results have demonstrated the usefulness of the system for the detection and location of the objects in indoor environments. Furthermore, through the comparison of two proposed methods for extracting features, it has been determined which alternative offers better performance. The final results have been obtained taking into account the proposed problem and that the environment has not been changed, that is to say, the environment has not been altered to perform the tests.

Object Detection Applied to Indoor Environments for Mobile Robot Navigation

PubMed Central

Hernández, Alejandra Carolina; Gómez, Clara; Crespo, Jonathan; Barber, Ramón

2016-01-01

To move around the environment, human beings depend on sight more than their other senses, because it provides information about the size, shape, color and position of an object. The increasing interest in building autonomous mobile systems makes the detection and recognition of objects in indoor environments a very important and challenging task. In this work, a vision system to detect objects considering usual human environments, able to work on a real mobile robot, is developed. In the proposed system, the classification method used is Support Vector Machine (SVM) and as input to this system, RGB and depth images are used. Different segmentation techniques have been applied to each kind of object. Similarly, two alternatives to extract features of the objects are explored, based on geometric shape descriptors and bag of words. The experimental results have demonstrated the usefulness of the system for the detection and location of the objects in indoor environments. Furthermore, through the comparison of two proposed methods for extracting features, it has been determined which alternative offers better performance. The final results have been obtained taking into account the proposed problem and that the environment has not been changed, that is to say, the environment has not been altered to perform the tests. PMID:27483264

Object Detection and Classification by Decision-Level Fusion for Intelligent Vehicle Systems.

PubMed

Oh, Sang-Il; Kang, Hang-Bong

2017-01-22

To understand driving environments effectively, it is important to achieve accurate detection and classification of objects detected by sensor-based intelligent vehicle systems, which are significantly important tasks. Object detection is performed for the localization of objects, whereas object classification recognizes object classes from detected object regions. For accurate object detection and classification, fusing multiple sensor information into a key component of the representation and perception processes is necessary. In this paper, we propose a new object-detection and classification method using decision-level fusion. We fuse the classification outputs from independent unary classifiers, such as 3D point clouds and image data using a convolutional neural network (CNN). The unary classifiers for the two sensors are the CNN with five layers, which use more than two pre-trained convolutional layers to consider local to global features as data representation. To represent data using convolutional layers, we apply region of interest (ROI) pooling to the outputs of each layer on the object candidate regions generated using object proposal generation to realize color flattening and semantic grouping for charge-coupled device and Light Detection And Ranging (LiDAR) sensors. We evaluate our proposed method on a KITTI benchmark dataset to detect and classify three object classes: cars, pedestrians and cyclists. The evaluation results show that the proposed method achieves better performance than the previous methods. Our proposed method extracted approximately 500 proposals on a 1226 × 370 image, whereas the original selective search method extracted approximately 10 6 × n proposals. We obtained classification performance with 77.72% mean average precision over the entirety of the classes in the moderate detection level of the KITTI benchmark dataset.

Object Detection and Classification by Decision-Level Fusion for Intelligent Vehicle Systems

PubMed Central

Oh, Sang-Il; Kang, Hang-Bong

2017-01-01

To understand driving environments effectively, it is important to achieve accurate detection and classification of objects detected by sensor-based intelligent vehicle systems, which are significantly important tasks. Object detection is performed for the localization of objects, whereas object classification recognizes object classes from detected object regions. For accurate object detection and classification, fusing multiple sensor information into a key component of the representation and perception processes is necessary. In this paper, we propose a new object-detection and classification method using decision-level fusion. We fuse the classification outputs from independent unary classifiers, such as 3D point clouds and image data using a convolutional neural network (CNN). The unary classifiers for the two sensors are the CNN with five layers, which use more than two pre-trained convolutional layers to consider local to global features as data representation. To represent data using convolutional layers, we apply region of interest (ROI) pooling to the outputs of each layer on the object candidate regions generated using object proposal generation to realize color flattening and semantic grouping for charge-coupled device and Light Detection And Ranging (LiDAR) sensors. We evaluate our proposed method on a KITTI benchmark dataset to detect and classify three object classes: cars, pedestrians and cyclists. The evaluation results show that the proposed method achieves better performance than the previous methods. Our proposed method extracted approximately 500 proposals on a 1226×370 image, whereas the original selective search method extracted approximately 106×n proposals. We obtained classification performance with 77.72% mean average precision over the entirety of the classes in the moderate detection level of the KITTI benchmark dataset. PMID:28117742

An explosives detection system for airline security using coherent x-ray scattering technology

NASA Astrophysics Data System (ADS)

Madden, Robert W.; Mahdavieh, Jacob; Smith, Richard C.; Subramanian, Ravi

2008-08-01

L-3 Communications Security and Detection Systems (SDS) has developed a new system for automated alarm resolution in airline baggage Explosive Detection Systems (EDS) based on coherent x-ray scattering spectroscopy. The capabilities of the system were demonstrated in tests with concealed explosives at the Transportation Security Laboratory and airline passenger baggage at Orlando International Airport. The system uses x-ray image information to identify suspicious objects and performs targeted diffraction measurements to classify them. This extra layer of detection capability affords a significant reduction in the rate of false alarm objects that must presently be resolved by opening passenger bags for hand inspection.

Biased Competition in Visual Processing Hierarchies: A Learning Approach Using Multiple Cues.

PubMed

Gepperth, Alexander R T; Rebhan, Sven; Hasler, Stephan; Fritsch, Jannik

2011-03-01

In this contribution, we present a large-scale hierarchical system for object detection fusing bottom-up (signal-driven) processing results with top-down (model or task-driven) attentional modulation. Specifically, we focus on the question of how the autonomous learning of invariant models can be embedded into a performing system and how such models can be used to define object-specific attentional modulation signals. Our system implements bi-directional data flow in a processing hierarchy. The bottom-up data flow proceeds from a preprocessing level to the hypothesis level where object hypotheses created by exhaustive object detection algorithms are represented in a roughly retinotopic way. A competitive selection mechanism is used to determine the most confident hypotheses, which are used on the system level to train multimodal models that link object identity to invariant hypothesis properties. The top-down data flow originates at the system level, where the trained multimodal models are used to obtain space- and feature-based attentional modulation signals, providing biases for the competitive selection process at the hypothesis level. This results in object-specific hypothesis facilitation/suppression in certain image regions which we show to be applicable to different object detection mechanisms. In order to demonstrate the benefits of this approach, we apply the system to the detection of cars in a variety of challenging traffic videos. Evaluating our approach on a publicly available dataset containing approximately 3,500 annotated video images from more than 1 h of driving, we can show strong increases in performance and generalization when compared to object detection in isolation. Furthermore, we compare our results to a late hypothesis rejection approach, showing that early coupling of top-down and bottom-up information is a favorable approach especially when processing resources are constrained.

An Underwater Target Detection System for Electro-Optical Imagery Data

DTIC Science & Technology

2010-06-01

detection and segmentation of underwater mine-like objects in the EO images captured with a CCD-based image sensor. The main focus of this research is to...develop a robust detection algorithm that can be used to detect low contrast and partial underwater objects from the EO imagery with low false alarm rate...underwater target detection I. INTRODUCTION Automatic detection and recognition of underwater objects from EO imagery poses a serious challenge due to poor

Neutron Interrogation System For Underwater Threat Detection And Identification

NASA Astrophysics Data System (ADS)

Barzilov, Alexander P.; Novikov, Ivan S.; Womble, Phil C.

2009-03-01

Wartime and terrorist activities, training and munitions testing, dumping and accidents have generated significant munitions contamination in the coastal and inland waters in the United States and abroad. Although current methods provide information about the existence of the anomaly (for instance, metal objects) in the sea bottom, they fail to identify the nature of the found objects. Field experience indicates that often in excess of 90% of objects excavated during the course of munitions clean up are found to be non-hazardous items (false alarm). The technology to detect and identify waterborne or underwater threats is also vital for protection of critical infrastructures (ports, dams, locks, refineries, and LNG/LPG). We are proposing a compact neutron interrogation system, which will be used to confirm possible threats by determining the chemical composition of the suspicious underwater object. The system consists of an electronic d-T 14-MeV neutron generator, a gamma detector to detect the gamma signal from the irradiated object and a data acquisition system. The detected signal then is analyzed to quantify the chemical elements of interest and to identify explosives or chemical warfare agents.

Aerial vehicles collision avoidance using monocular vision

NASA Astrophysics Data System (ADS)

Balashov, Oleg; Muraviev, Vadim; Strotov, Valery

2016-10-01

In this paper image-based collision avoidance algorithm that provides detection of nearby aircraft and distance estimation is presented. The approach requires a vision system with a single moving camera and additional information about carrier's speed and orientation from onboard sensors. The main idea is to create a multi-step approach based on a preliminary detection, regions of interest (ROI) selection, contour segmentation, object matching and localization. The proposed algorithm is able to detect small targets but unlike many other approaches is designed to work with large-scale objects as well. To localize aerial vehicle position the system of equations relating object coordinates in space and observed image is solved. The system solution gives the current position and speed of the detected object in space. Using this information distance and time to collision can be estimated. Experimental research on real video sequences and modeled data is performed. Video database contained different types of aerial vehicles: aircrafts, helicopters, and UAVs. The presented algorithm is able to detect aerial vehicles from several kilometers under regular daylight conditions.

Conventional and phase contrast x-ray imaging techniques and ultrasound imaging method in breast tumor detection: initial comparison studies using phantom

NASA Astrophysics Data System (ADS)

Guo, Yuran; Wu, Di; Omoumi, Farid H.; Li, Yuhua; Wong, Molly Donovan; Ghani, Muhammad U.; Zheng, Bin; Liu, Hong

2018-02-01

The objective of this study was to demonstrate the capability of the high-energy in-line phase contrast imaging in detecting the breast tumors which are undetectable by conventional x-ray imaging but detectable by ultrasound. Experimentally, a CIRS multipurpose breast phantom with heterogeneous 50% glandular and 50% adipose breast tissue was imaged by high-energy in-line phase contrast system, conventional x-ray system and ultrasonography machine. The high-energy in-line phase contrast projection was acquired at 120 kVp, 0.3 mAs with the focal spot size of 18.3 μm. The conventional x-ray projection was acquired at 40 kVp, 3.3 mAs with the focal spot size of 22.26 μm. Both of the x-ray imaging acquisitions were conducted with a unique mean glandular dose of 0.08 mGy. As the result, the high-energy in-line phase contrast system was able to detect one lesion-like object which was also detected by the ultrasonography. This object was spherical shape with the length of about 12.28 mm. Also, the conventional x-ray system was not able to detect any objects. This result indicated the advantages provided by high-energy in-line phase contrast over conventional x-ray system in detecting lesion-like object under the same radiation dose. To meet the needs of current clinical strategies for high-density breasts screening, breast phantoms with higher glandular densities will be employed in future studies.

Selective visual attention in object detection processes

NASA Astrophysics Data System (ADS)

Paletta, Lucas; Goyal, Anurag; Greindl, Christian

2003-03-01

Object detection is an enabling technology that plays a key role in many application areas, such as content based media retrieval. Attentive cognitive vision systems are here proposed where the focus of attention is directed towards the most relevant target. The most promising information is interpreted in a sequential process that dynamically makes use of knowledge and that enables spatial reasoning on the local object information. The presented work proposes an innovative application of attention mechanisms for object detection which is most general in its understanding of information and action selection. The attentive detection system uses a cascade of increasingly complex classifiers for the stepwise identification of regions of interest (ROIs) and recursively refined object hypotheses. While the most coarse classifiers are used to determine first approximations on a region of interest in the input image, more complex classifiers are used for more refined ROIs to give more confident estimates. Objects are modelled by local appearance based representations and in terms of posterior distributions of the object samples in eigenspace. The discrimination function to discern between objects is modeled by a radial basis functions (RBF) network that has been compared with alternative networks and been proved consistent and superior to other artifical neural networks for appearance based object recognition. The experiments were led for the automatic detection of brand objects in Formula One broadcasts within the European Commission's cognitive vision project DETECT.

A new method of edge detection for object recognition

USGS Publications Warehouse

Maddox, Brian G.; Rhew, Benjamin

2004-01-01

Traditional edge detection systems function by returning every edge in an input image. This can result in a large amount of clutter and make certain vectorization algorithms less accurate. Accuracy problems can then have a large impact on automated object recognition systems that depend on edge information. A new method of directed edge detection can be used to limit the number of edges returned based on a particular feature. This results in a cleaner image that is easier for vectorization. Vectorized edges from this process could then feed an object recognition system where the edge data would also contain information as to what type of feature it bordered.

A dynamical approach in exploring the unknown mass in the Solar system using pulsar timing arrays

NASA Astrophysics Data System (ADS)

Guo, Y. J.; Lee, K. J.; Caballero, R. N.

2018-04-01

The error in the Solar system ephemeris will lead to dipolar correlations in the residuals of pulsar timing array for widely separated pulsars. In this paper, we utilize such correlated signals, and construct a Bayesian data-analysis framework to detect the unknown mass in the Solar system and to measure the orbital parameters. The algorithm is designed to calculate the waveform of the induced pulsar-timing residuals due to the unmodelled objects following the Keplerian orbits in the Solar system. The algorithm incorporates a Bayesian-analysis suit used to simultaneously analyse the pulsar-timing data of multiple pulsars to search for coherent waveforms, evaluate the detection significance of unknown objects, and to measure their parameters. When the object is not detectable, our algorithm can be used to place upper limits on the mass. The algorithm is verified using simulated data sets, and cross-checked with analytical calculations. We also investigate the capability of future pulsar-timing-array experiments in detecting the unknown objects. We expect that the future pulsar-timing data can limit the unknown massive objects in the Solar system to be lighter than 10-11-10-12 M⊙, or measure the mass of Jovian system to a fractional precision of 10-8-10-9.

Influence of grid control and object detection on radiation exposure and image quality using mobile C-arms - first results.

PubMed

Gosch, D; Ratzmer, A; Berauer, P; Kahn, T

2007-09-01

The objective of this study was to examine the extent to which the image quality on mobile C-arms can be improved by an innovative exposure rate control system (grid control). In addition, the possible dose reduction in the pulsed fluoroscopy mode using 25 pulses/sec produced by automatic adjustment of the pulse rate through motion detection was to be determined. As opposed to conventional exposure rate control systems, which use a measuring circle in the center of the field of view, grid control is based on a fine mesh of square cells which are overlaid on the entire fluoroscopic image. The system uses only those cells for exposure control that are covered by the object to be visualized. This is intended to ensure optimally exposed images, regardless of the size, shape and position of the object to be visualized. The system also automatically detects any motion of the object. If a pulse rate of 25 pulses/sec is selected and no changes in the image are observed, the pulse rate used for pulsed fluoroscopy is gradually reduced. This may decrease the radiation exposure. The influence of grid control on image quality was examined using an anthropomorphic phantom. The dose reduction achieved with the help of object detection was determined by evaluating the examination data of 146 patients from 5 different countries. The image of the static phantom made with grid control was always optimally exposed, regardless of the position of the object to be visualized. The average dose reduction when using 25 pulses/sec resulting from object detection and automatic down-pulsing was 21 %, and the maximum dose reduction was 60 %. Grid control facilitates C-arm operation, since optimum image exposure can be obtained independently of object positioning. Object detection may lead to a reduction in radiation exposure for the patient and operating staff.

Systems and methods for detecting an image of an object by use of an X-ray beam having a polychromatic distribution

DOEpatents

Parham, Christopher; Zhong, Zhong; Pisano, Etta; Connor, Dean; Chapman, Leroy D.

2010-06-22

Systems and methods for detecting an image of an object using an X-ray beam having a polychromatic energy distribution are disclosed. According to one aspect, a method can include detecting an image of an object. The method can include generating a first X-ray beam having a polychromatic energy distribution. Further, the method can include positioning a single monochromator crystal in a predetermined position to directly intercept the first X-ray beam such that a second X-ray beam having a predetermined energy level is produced. Further, an object can be positioned in the path of the second X-ray beam for transmission of the second X-ray beam through the object and emission from the object as a transmitted X-ray beam. The transmitted X-ray beam can be directed at an angle of incidence upon a crystal analyzer. Further, an image of the object can be detected from a beam diffracted from the analyzer crystal.

Real-time, continuous-wave terahertz imaging using a microbolometer focal-plane array

NASA Technical Reports Server (NTRS)

Hu, Qing (Inventor); Min Lee, Alan W. (Inventor)

2010-01-01

The present invention generally provides a terahertz (THz) imaging system that includes a source for generating radiation (e.g., a quantum cascade laser) having one or more frequencies in a range of about 0.1 THz to about 10 THz, and a two-dimensional detector array comprising a plurality of radiation detecting elements that are capable of detecting radiation in that frequency range. An optical system directs radiation from the source to an object to be imaged. The detector array detects at least a portion of the radiation transmitted through the object (or reflected by the object) so as to form a THz image of that object.

Object detection system based on multimodel saliency maps

NASA Astrophysics Data System (ADS)

Guo, Ya'nan; Luo, Chongfan; Ma, Yide

2017-03-01

Detection of visually salient image regions is extensively applied in computer vision and computer graphics, such as object detection, adaptive compression, and object recognition, but any single model always has its limitations to various images, so in our work, we establish a method based on multimodel saliency maps to detect the object, which intelligently absorbs the merits of various individual saliency detection models to achieve promising results. The method can be roughly divided into three steps: in the first step, we propose a decision-making system to evaluate saliency maps obtained by seven competitive methods and merely select the three most valuable saliency maps; in the second step, we introduce heterogeneous PCNN algorithm to obtain three prime foregrounds; and then a self-designed nonlinear fusion method is proposed to merge these saliency maps; at last, the adaptive improved and simplified PCNN model is used to detect the object. Our proposed method can constitute an object detection system for different occasions, which requires no training, is simple, and highly efficient. The proposed saliency fusion technique shows better performance over a broad range of images and enriches the applicability range by fusing different individual saliency models, this proposed system is worthy enough to be called a strong model. Moreover, the proposed adaptive improved SPCNN model is stemmed from the Eckhorn's neuron model, which is skilled in image segmentation because of its biological background, and in which all the parameters are adaptive to image information. We extensively appraise our algorithm on classical salient object detection database, and the experimental results demonstrate that the aggregation of saliency maps outperforms the best saliency model in all cases, yielding highest precision of 89.90%, better recall rates of 98.20%, greatest F-measure of 91.20%, and lowest mean absolute error value of 0.057, the value of proposed saliency evaluation EHA reaches to 215.287. We deem our method can be wielded to diverse applications in the future.

Radar based autonomous sensor module

NASA Astrophysics Data System (ADS)

Styles, Tim

2016-10-01

Most surveillance systems combine camera sensors with other detection sensors that trigger an alert to a human operator when an object is detected. The detection sensors typically require careful installation and configuration for each application and there is a significant burden on the operator to react to each alert by viewing camera video feeds. A demonstration system known as Sensing for Asset Protection with Integrated Electronic Networked Technology (SAPIENT) has been developed to address these issues using Autonomous Sensor Modules (ASM) and a central High Level Decision Making Module (HLDMM) that can fuse the detections from multiple sensors. This paper describes the 24 GHz radar based ASM, which provides an all-weather, low power and license exempt solution to the problem of wide area surveillance. The radar module autonomously configures itself in response to tasks provided by the HLDMM, steering the transmit beam and setting range resolution and power levels for optimum performance. The results show the detection and classification performance for pedestrians and vehicles in an area of interest, which can be modified by the HLDMM without physical adjustment. The module uses range-Doppler processing for reliable detection of moving objects and combines Radar Cross Section and micro-Doppler characteristics for object classification. Objects are classified as pedestrian or vehicle, with vehicle sub classes based on size. Detections are reported only if the object is detected in a task coverage area and it is classified as an object of interest. The system was shown in a perimeter protection scenario using multiple radar ASMs, laser scanners, thermal cameras and visible band cameras. This combination of sensors enabled the HLDMM to generate reliable alerts with improved discrimination of objects and behaviours of interest.

Chemical detection system and related methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caffrey, Augustine J.; Chichester, David L.; Egger, Ann E.

2017-06-27

A chemical detection system includes a frame, an emitter coupled to the frame, and a detector coupled to the frame proximate the emitter. The system also includes a shielding system coupled to the frame and positioned at least partially between the emitter and the detector, wherein the frame positions a sensing surface of the detector in a direction substantially parallel to a plane extending along a front portion of the frame. A method of analyzing composition of a suspect object includes directing neutrons at the object, detecting gamma rays emitted from the object, and communicating spectrometer information regarding the gammamore » rays. The method also includes presenting a GUI to a user with a dynamic status of an ongoing neutron spectroscopy process. The dynamic status includes a present confidence for a plurality of compounds being present in the suspect object responsive to changes in the spectrometer information during the ongoing process.« less

High accuracy position method based on computer vision and error analysis

NASA Astrophysics Data System (ADS)

Chen, Shihao; Shi, Zhongke

2003-09-01

The study of high accuracy position system is becoming the hotspot in the field of autocontrol. And positioning is one of the most researched tasks in vision system. So we decide to solve the object locating by using the image processing method. This paper describes a new method of high accuracy positioning method through vision system. In the proposed method, an edge-detection filter is designed for a certain running condition. Here, the filter contains two mainly parts: one is image-processing module, this module is to implement edge detection, it contains of multi-level threshold self-adapting segmentation, edge-detection and edge filter; the other one is object-locating module, it is to point out the location of each object in high accurate, and it is made up of medium-filtering and curve-fitting. This paper gives some analysis error for the method to prove the feasibility of vision in position detecting. Finally, to verify the availability of the method, an example of positioning worktable, which is using the proposed method, is given at the end of the paper. Results show that the method can accurately detect the position of measured object and identify object attitude.

Flexibility in Visual Working Memory: Accurate Change Detection in the Face of Irrelevant Variations in Position

PubMed Central

Woodman, Geoffrey F.; Vogel, Edward K.; Luck, Steven J.

2012-01-01

Many recent studies of visual working memory have used change-detection tasks in which subjects view sequential displays and are asked to report whether they are identical or if one object has changed. A key question is whether the memory system used to perform this task is sufficiently flexible to detect changes in object identity independent of spatial transformations, but previous research has yielded contradictory results. To address this issue, the present study compared standard change-detection tasks with tasks in which the objects varied in size or position between successive arrays. Performance was nearly identical across the standard and transformed tasks unless the task implicitly encouraged spatial encoding. These results resolve the discrepancies in prior studies and demonstrate that the visual working memory system can detect changes in object identity across spatial transformations. PMID:22287933

Shape-based human detection for threat assessment

NASA Astrophysics Data System (ADS)

Lee, Dah-Jye; Zhan, Pengcheng; Thomas, Aaron; Schoenberger, Robert B.

2004-07-01

Detection of intrusions for early threat assessment requires the capability of distinguishing whether the intrusion is a human, an animal, or other objects. Most low-cost security systems use simple electronic motion detection sensors to monitor motion or the location of objects within the perimeter. Although cost effective, these systems suffer from high rates of false alarm, especially when monitoring open environments. Any moving objects including animals can falsely trigger the security system. Other security systems that utilize video equipment require human interpretation of the scene in order to make real-time threat assessment. Shape-based human detection technique has been developed for accurate early threat assessments for open and remote environment. Potential threats are isolated from the static background scene using differential motion analysis and contours of the intruding objects are extracted for shape analysis. Contour points are simplified by removing redundant points connecting short and straight line segments and preserving only those with shape significance. Contours are represented in tangent space for comparison with shapes stored in database. Power cepstrum technique has been developed to search for the best matched contour in database and to distinguish a human from other objects from different viewing angles and distances.

3D Backscatter Imaging System

NASA Technical Reports Server (NTRS)

Whitaker, Ross (Inventor); Turner, D. Clark (Inventor)

2016-01-01

Systems and methods for imaging an object using backscattered radiation are described. The imaging system comprises both a radiation source for irradiating an object that is rotationally movable about the object, and a detector for detecting backscattered radiation from the object that can be disposed on substantially the same side of the object as the source and which can be rotationally movable about the object. The detector can be separated into multiple detector segments with each segment having a single line of sight projection through the object and so detects radiation along that line of sight. Thus, each detector segment can isolate the desired component of the backscattered radiation. By moving independently of each other about the object, the source and detector can collect multiple images of the object at different angles of rotation and generate a three dimensional reconstruction of the object. Other embodiments are described.

Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition.

PubMed

Wong, Sebastien C; Stamatescu, Victor; Gatt, Adam; Kearney, David; Lee, Ivan; McDonnell, Mark D

2017-10-01

This paper addresses the problem of online tracking and classification of multiple objects in an image sequence. Our proposed solution is to first track all objects in the scene without relying on object-specific prior knowledge, which in other systems can take the form of hand-crafted features or user-based track initialization. We then classify the tracked objects with a fast-learning image classifier, that is based on a shallow convolutional neural network architecture and demonstrate that object recognition improves when this is combined with object state information from the tracking algorithm. We argue that by transferring the use of prior knowledge from the detection and tracking stages to the classification stage, we can design a robust, general purpose object recognition system with the ability to detect and track a variety of object types. We describe our biologically inspired implementation, which adaptively learns the shape and motion of tracked objects, and apply it to the Neovision2 Tower benchmark data set, which contains multiple object types. An experimental evaluation demonstrates that our approach is competitive with the state-of-the-art video object recognition systems that do make use of object-specific prior knowledge in detection and tracking, while providing additional practical advantages by virtue of its generality.

Systems and methods for detecting an image of an object using multi-beam imaging from an X-ray beam having a polychromatic distribution

DOEpatents

Parham, Christopher A; Zhong, Zhong; Pisano, Etta; Connor, Jr., Dean M

2015-03-03

Systems and methods for detecting an image of an object using a multi-beam imaging system from an x-ray beam having a polychromatic energy distribution are disclosed. According to one aspect, a method can include generating a first X-ray beam having a polychromatic energy distribution. Further, the method can include positioning a plurality of monochromator crystals in a predetermined position to directly intercept the first X-ray beam such that a plurality of second X-ray beams having predetermined energy levels are produced. Further, an object can be positioned in the path of the second X-ray beams for transmission of the second X-ray beams through the object and emission from the object as transmitted X-ray beams. The transmitted X-ray beams can each be directed at an angle of incidence upon one or more crystal analyzers. Further, an image of the object can be detected from the beams diffracted from the analyzer crystals.

LABRADOR: a learning autonomous behavior-based robot for adaptive detection and object retrieval

NASA Astrophysics Data System (ADS)

Yamauchi, Brian; Moseley, Mark; Brookshire, Jonathan

2013-01-01

As part of the TARDEC-funded CANINE (Cooperative Autonomous Navigation in a Networked Environment) Program, iRobot developed LABRADOR (Learning Autonomous Behavior-based Robot for Adaptive Detection and Object Retrieval). LABRADOR was based on the rugged, man-portable, iRobot PackBot unmanned ground vehicle (UGV) equipped with an explosives ordnance disposal (EOD) manipulator arm and a custom gripper. For LABRADOR, we developed a vision-based object learning and recognition system that combined a TLD (track-learn-detect) filter based on object shape features with a color-histogram-based object detector. Our vision system was able to learn in real-time to recognize objects presented to the robot. We also implemented a waypoint navigation system based on fused GPS, IMU (inertial measurement unit), and odometry data. We used this navigation capability to implement autonomous behaviors capable of searching a specified area using a variety of robust coverage strategies - including outward spiral, random bounce, random waypoint, and perimeter following behaviors. While the full system was not integrated in time to compete in the CANINE competition event, we developed useful perception, navigation, and behavior capabilities that may be applied to future autonomous robot systems.

AN/FSY-3 Space Fence System Support of Conjunction Assessment

NASA Astrophysics Data System (ADS)

Koltiska, M.; Du, H.; Prochoda, D.; Kelly, K.

2016-09-01

The Space Fence System is a ground-based space surveillance radar system designed to detect and track all objects in Low Earth Orbit the size of a softball or larger. The system detects many objects that are not currently in the catalog of satellites and space debris that is maintained by the US Air Force. In addition, it will also be capable of tracking many of the deep space objects in the catalog. By providing daily updates of the orbits of these new objects along with updates of most of the objects in the catalog, it will enhance Space Situational Awareness and significantly improve our ability to predict close approaches, aka conjunctions, of objects in space. With this additional capacity for tracking objects in space the Space Surveillance Network has significantly more resources for monitoring orbital debris, especially for debris that could collide with active satellites and other debris.

Evaluation of 3M molecular detection system and ANSR pathogen detection system for rapid detection of salmonella from egg products

USDA-ARS?s Scientific Manuscript database

Loop-mediated isothermal amplification (LAMP) is a novel simple detection technology that amplifies DNA with high speed, efficiency, and specificity under isothermal conditions. The objective of this study was to evaluate the effectiveness of 3M Molecular Detection System (MDS) and ANSR Pathogen Det...

A Meteorological (humidity, temperature, aerosols)) mobile dial system: Concepts and design

NASA Technical Reports Server (NTRS)

Cahen, C.; Lesne, J. L.; Benard, J.; Ponsardin, P.

1986-01-01

Since 1982 a program was conducted to develop a mobile meteorological (humidity, temperature, aerosols) Differential Absorption Lidar (DIAL) devoted to the studies of the nuclear power plant atmospheric surroundings. The measurement objectives are defined according to the user needs and the lidar feasibility. The concepts and design adopted to meet both the requirement and the measurement objectives are described. Each sub-system is addressed sequentially: transmitting system, receiving system, detection system, and post detection.

Detection technique for artificially illuminated objects in the outer solar system and beyond.

PubMed

Loeb, Abraham; Turner, Edwin L

2012-04-01

Existing and planned optical telescopes and surveys can detect artificially illuminated objects, comparable in total brightness to a major terrestrial city, at the outskirts of the Solar System. Orbital parameters of Kuiper belt objects (KBOs) are routinely measured to exquisite precisions of<10(-3). Here, we propose to measure the variation of the observed flux F from such objects as a function of their changing orbital distances D. Sunlight-illuminated objects will show a logarithmic slope α ≡ (d log F/d log D)=-4, whereas artificially illuminated objects should exhibit α=-2. The proposed Large Synoptic Survey Telescope (LSST) and other planned surveys will provide superb data and allow measurement of α for thousands of KBOs. If objects with α=-2 are found, follow-up observations could measure their spectra to determine whether they are illuminated by artificial lighting. The search can be extended beyond the Solar System with future generations of telescopes on the ground and in space that would have the capacity to detect phase modulation due to very strong artificial illumination on the nightside of planets as they orbit their parent stars.

Low-complexity object detection with deep convolutional neural network for embedded systems

NASA Astrophysics Data System (ADS)

Tripathi, Subarna; Kang, Byeongkeun; Dane, Gokce; Nguyen, Truong

2017-09-01

We investigate low-complexity convolutional neural networks (CNNs) for object detection for embedded vision applications. It is well-known that consolidation of an embedded system for CNN-based object detection is more challenging due to computation and memory requirement comparing with problems like image classification. To achieve these requirements, we design and develop an end-to-end TensorFlow (TF)-based fully-convolutional deep neural network for generic object detection task inspired by one of the fastest framework, YOLO.1 The proposed network predicts the localization of every object by regressing the coordinates of the corresponding bounding box as in YOLO. Hence, the network is able to detect any objects without any limitations in the size of the objects. However, unlike YOLO, all the layers in the proposed network is fully-convolutional. Thus, it is able to take input images of any size. We pick face detection as an use case. We evaluate the proposed model for face detection on FDDB dataset and Widerface dataset. As another use case of generic object detection, we evaluate its performance on PASCAL VOC dataset. The experimental results demonstrate that the proposed network can predict object instances of different sizes and poses in a single frame. Moreover, the results show that the proposed method achieves comparative accuracy comparing with the state-of-the-art CNN-based object detection methods while reducing the model size by 3× and memory-BW by 3 - 4× comparing with one of the best real-time CNN-based object detectors, YOLO. Our 8-bit fixed-point TF-model provides additional 4× memory reduction while keeping the accuracy nearly as good as the floating-point model. Moreover, the fixed- point model is capable of achieving 20× faster inference speed comparing with the floating-point model. Thus, the proposed method is promising for embedded implementations.

Systems for detecting charged particles in object inspection

DOEpatents

Morris, Christopher L.; Makela, Mark F.

2013-08-20

Techniques, apparatus and systems for detecting particles such as muons. In one implementation, a monitoring system has a cosmic ray-produced charged particle tracker with a plurality of drift cells. The drift cells, which can be for example aluminum drift tubes, can be arranged at least above and below a volume to be scanned to thereby track incoming and outgoing charged particles, such as cosmic ray-produced muons, while also detecting gamma rays. The system can selectively detect devices or materials, such as iron, lead, gold and/or tungsten, occupying the volume from multiple scattering of the charged particles passing through the volume and can also detect any radioactive sources occupying the volume from gamma rays emitted therefrom. If necessary, the drift tubes can be sealed to eliminate the need for a gas handling system. The system can be employed to inspect occupied vehicles at border crossings for nuclear threat objects.

Transmission mode terahertz computed tomography

DOEpatents

Ferguson, Bradley Stuart; Wang, Shaohong; Zhang, Xi-Cheng

2006-10-10

A method of obtaining a series of images of a three-dimensional object by transmitting pulsed terahertz (THz) radiation through the entire object from a plurality of angles, optically detecting changes in the transmitted THz radiation using pulsed laser radiation, and constructing a plurality of imaged slices of the three-dimensional object using the detected changes in the transmitted THz radiation. The THz radiation is transmitted through the object as a scanning spot. The object is placed within the Rayleigh range of the focused THz beam and a focusing system is used to transfer the imaging plane from adjacent the object to a desired distance away from the object. A related system is also disclosed.

Trace detection of explosives using an in-line high-volume sampler, preconcentrator, and Fido explosives detector

NASA Astrophysics Data System (ADS)

Ingram, Russ; Sikes, John

2010-04-01

This paper shall demonstrate the results of a prototype system to detect explosive objects and obscured contaminated targets. By combining a high volume sampling nozzle with an inline 2-stage preconcentrator and a Fido, greater standoff is achieved than with the Fido alone. The direct application of this system is on the Autonomous Mine Detection System (AMDS) but could be deployed on a large variety of robotic platforms. It is being developed under the auspices of the U.S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate, Countermine Division. This device is one of several detection tools and technologies to be used on the AMDS. These systems will have multiple, and at times, overlapping objectives. One objective is trace detection on the surface of an unknown potential target. By increasing the standoff capabilities of the detector, the fine manipulation of the robot deploying the detector is less critical. Current detectors used on robotic systems must either be directly in the vapor plume or make direct contact with the target. By increasing the standoff, detection is more easily and quickly achieved. The end result detector must overcome cross-contamination, sample throughput, and environmental issues. The paper will provide preliminary results of the prototype system to include data, and where feasible, video of testing results.

System and method for automated object detection in an image

DOEpatents

Kenyon, Garrett T.; Brumby, Steven P.; George, John S.; Paiton, Dylan M.; Schultz, Peter F.

2015-10-06

A contour/shape detection model may use relatively simple and efficient kernels to detect target edges in an object within an image or video. A co-occurrence probability may be calculated for two or more edge features in an image or video using an object definition. Edge features may be differentiated between in response to measured contextual support, and prominent edge features may be extracted based on the measured contextual support. The object may then be identified based on the extracted prominent edge features.

Interplanetary Dust Observations by the Juno MAG Investigation

NASA Astrophysics Data System (ADS)

Jørgensen, John; Benn, Mathias; Denver, Troelz; Connerney, Jack; Jørgensen, Peter; Bolton, Scott; Brauer, Peter; Levin, Steven; Oliversen, Ronald

2017-04-01

The spin-stabilized and solar powered Juno spacecraft recently concluded a 5-year voyage through the solar system en route to Jupiter, arriving on July 4th, 2016. During the cruise phase from Earth to the Jovian system, the Magnetometer investigation (MAG) operated two magnetic field sensors and four co-located imaging systems designed to provide accurate attitude knowledge for the MAG sensors. One of these four imaging sensors - camera "D" of the Advanced Stellar Compass (ASC) - was operated in a mode designed to detect all luminous objects in its field of view, recording and characterizing those not found in the on-board star catalog. The capability to detect and track such objects ("non-stellar objects", or NSOs) provides a unique opportunity to sense and characterize interplanetary dust particles. The camera's detection threshold was set to MV9 to minimize false detections and discourage tracking of known objects. On-board filtering algorithms selected only those objects tracked through more than 5 consecutive images and moving with an apparent angular rate between 15"/s and 10,000"/s. The coordinates (RA, DEC), intensity, and apparent velocity of such objects were stored for eventual downlink. Direct detection of proximate dust particles is precluded by their large (10-30 km/s) relative velocity and extreme angular rates, but their presence may be inferred using the collecting area of Juno's large ( 55m2) solar arrays. Dust particles impact the spacecraft at high velocity, creating an expanding plasma cloud and ejecta with modest (few m/s) velocities. These excavated particles are revealed in reflected sunlight and tracked moving away from the spacecraft from the point of impact. Application of this novel detection method during Juno's traversal of the solar system provides new information on the distribution of interplanetary (µm-sized) dust.

Performance analysis of a multispectral system for mine detection in the littoral zone

NASA Astrophysics Data System (ADS)

Hargrove, John T.; Louchard, Eric

2004-09-01

Science & Technology International (STI) has developed, under contract with the Office of Naval Research, a system of multispectral airborne sensors and processing algorithms capable of detecting mine-like objects in the surf zone. STI has used this system to detect mine-like objects in a littoral environment as part of blind tests at Kaneohe Marine Corps Base Hawaii, and Panama City, Florida. The airborne and ground subsystems are described. The detection algorithm is graphically illustrated. We report on the performance of the system configured to operate without a human in the loop. A subsurface (underwater bottom proud mine in the surf zone and moored mine in shallow water) mine detection capability is demonstrated in the surf zone, and in shallow water with wave spillage and foam. Our analysis demonstrates that this STI-developed multispectral airborne mine detection system provides a technical foundation for a viable mine counter-measures system for use prior to an amphibious assault.

Object detection system using SPAD proximity detectors

NASA Astrophysics Data System (ADS)

Stark, Laurence; Raynor, Jeffrey M.; Henderson, Robert K.

2011-10-01

This paper presents an object detection system based upon the use of multiple single photon avalanche diode (SPAD) proximity sensors operating upon the time-of-flight (ToF) principle, whereby the co-ordinates of a target object in a coordinate system relative to the assembly are calculated. The system is similar to a touch screen system in form and operation except that the lack of requirement of a physical sensing surface provides a novel advantage over most existing touch screen technologies. The sensors are controlled by FPGA-based firmware and each proximity sensor in the system measures the range from the sensor to the target object. A software algorithm is implemented to calculate the x-y coordinates of the target object based on the distance measurements from at least two separate sensors and the known relative positions of these sensors. Existing proximity sensors were capable of determining the distance to an object with centimetric accuracy and were modified to obtain a wide field of view in the x-y axes with low beam angle in z in order to provide a detection area as large as possible. Design and implementation of the firmware, electronic hardware, mechanics and optics are covered in the paper. Possible future work would include characterisation with alternative designs of proximity sensors, as this is the component which determines the highest achievable accur1acy of the system.

System for critical infrastructure security based on multispectral observation-detection module

NASA Astrophysics Data System (ADS)

Trzaskawka, Piotr; Kastek, Mariusz; Życzkowski, Marek; Dulski, Rafał; Szustakowski, Mieczysław; Ciurapiński, Wiesław; Bareła, Jarosław

2013-10-01

Recent terrorist attacks and possibilities of such actions in future have forced to develop security systems for critical infrastructures that embrace sensors technologies and technical organization of systems. The used till now perimeter protection of stationary objects, based on construction of a ring with two-zone fencing, visual cameras with illumination are efficiently displaced by the systems of the multisensor technology that consists of: visible technology - day/night cameras registering optical contrast of a scene, thermal technology - cheap bolometric cameras recording thermal contrast of a scene and active ground radars - microwave and millimetre wavelengths that record and detect reflected radiation. Merging of these three different technologies into one system requires methodology for selection of technical conditions of installation and parameters of sensors. This procedure enables us to construct a system with correlated range, resolution, field of view and object identification. Important technical problem connected with the multispectral system is its software, which helps couple the radar with the cameras. This software can be used for automatic focusing of cameras, automatic guiding cameras to an object detected by the radar, tracking of the object and localization of the object on the digital map as well as target identification and alerting. Based on "plug and play" architecture, this system provides unmatched flexibility and simplistic integration of sensors and devices in TCP/IP networks. Using a graphical user interface it is possible to control sensors and monitor streaming video and other data over the network, visualize the results of data fusion process and obtain detailed information about detected intruders over a digital map. System provide high-level applications and operator workload reduction with features such as sensor to sensor cueing from detection devices, automatic e-mail notification and alarm triggering. The paper presents a structure and some elements of critical infrastructure protection solution which is based on a modular multisensor security system. System description is focused mainly on methodology of selection of sensors parameters. The results of the tests in real conditions are also presented.

An integrated framework for detecting suspicious behaviors in video surveillance

NASA Astrophysics Data System (ADS)

Zin, Thi Thi; Tin, Pyke; Hama, Hiromitsu; Toriu, Takashi

2014-03-01

In this paper, we propose an integrated framework for detecting suspicious behaviors in video surveillance systems which are established in public places such as railway stations, airports, shopping malls and etc. Especially, people loitering in suspicion, unattended objects left behind and exchanging suspicious objects between persons are common security concerns in airports and other transit scenarios. These involve understanding scene/event, analyzing human movements, recognizing controllable objects, and observing the effect of the human movement on those objects. In the proposed framework, multiple background modeling technique, high level motion feature extraction method and embedded Markov chain models are integrated for detecting suspicious behaviors in real time video surveillance systems. Specifically, the proposed framework employs probability based multiple backgrounds modeling technique to detect moving objects. Then the velocity and distance measures are computed as the high level motion features of the interests. By using an integration of the computed features and the first passage time probabilities of the embedded Markov chain, the suspicious behaviors in video surveillance are analyzed for detecting loitering persons, objects left behind and human interactions such as fighting. The proposed framework has been tested by using standard public datasets and our own video surveillance scenarios.

Underwater detection by using ultrasonic sensor

NASA Astrophysics Data System (ADS)

Bakar, S. A. A.; Ong, N. R.; Aziz, M. H. A.; Alcain, J. B.; Haimi, W. M. W. N.; Sauli, Z.

2017-09-01

This paper described the low cost implementation of hardware and software in developing the system of ultrasonic which can visualize the feedback of sound in the form of measured distance through mobile phone and monitoring the frequency of detection by using real time graph of Java application. A single waterproof transducer of JSN-SR04T had been used to determine the distance of an object based on operation of the classic pulse echo detection method underwater. In this experiment, the system was tested by placing the housing which consisted of Arduino UNO, Bluetooth module of HC-06, ultrasonic sensor and LEDs at the top of the box and the transducer was immersed in the water. The system which had been tested for detection in vertical form was found to be capable of reporting through the use of colored LEDs as indicator to the relative proximity of object distance underwater form the sensor. As a conclusion, the system can detect the presence of an object underwater within the range of ultrasonic sensor and display the measured distance onto the mobile phone and the real time graph had been successfully generated.

Risk Factors Detection for Strategic Importance Objectives in Littoral Areas

NASA Astrophysics Data System (ADS)

Slămnoiu, G.; Radu, O.; Roşca, V.; Pascu, C.; Surdu, G.; Curcă, E.; Damian, R. G.; Rădulescu, A.

2017-06-01

With the invention and development of underwater explosive devices the need to neutralize them has also appeared, both for enemy and for own devices once conflicts are finished. The fight against active underwater explosive devices is a very complicated action that requires a very careful approach. Also, in the current context, strategic importance objectives located in the littoral areas can also become targets for divers or fast boats (suicidal actions).The system for detection, localization, tracking and identification of risk factors for strategic importance objectives in littoral areas has as one of its components an AUV and a hydro-acoustic sub-system for determining the ‘fingerprints’ of potential targets. The overall system will provide support for main missions such as underwater environment surveillance (detection, monitoring) in harbor areas and around other coast objectives, ship anchorage areas, mandatory pass points and also provide warnings about the presence of underwater and surface dangers in the interest areas.

The BEFWM system for detection and phase conjugation of a weak laser beam

NASA Astrophysics Data System (ADS)

Khizhnyak, Anatoliy; Markov, Vladimir

2007-09-01

Real environmental conditions, such as atmospheric turbulence and aero-optics effects, make practical implementation of the object-in-the-loop (TIL) algorithm a very difficult task, especially when the system is set to operate with a signal from the diffuse surface image-resolved object. The problem becomes even more complex since for the remote object the intensity of the returned signal is extremely low. This presentation discusses the results of an analysis and experimental verification of a thresholdless coherent signal receiving system, capable not only in high-sensitivity detection of an ultra weak object-scattered light, but also in its high-gain amplification and phase conjugation. The process of coherent detection by using the Brillouin Enhanced Four Wave Mixing (BEFWM) enables retrieval of complete information on the received signal, including accurate measurement of its wavefront. This information can be used for direct real-time control of the adaptive mirror.

Numerical study of the polarization effect of GPR systems on the detection of buried objects

NASA Astrophysics Data System (ADS)

Sagnard, Florence

2017-04-01

This work is in line with the studies carried out in our department over the last few years on object detection in civil engineering structures and soils. In parallel to building of the second version of the Sense-City test site where several pipeline networks will be buried [1], we are developing numerical models using the FIT and the FDTD approaches to study more precisely the contribution of the polarization diversity in the detection of conductive and dielectric buried objects using the GPR technique. The simulations developed are based on a ultra-wide band SFCW GPR system that have been designed and evaluated in our laboratory. A parametric study is proposed to evaluate the influence of the antenna configurations and the antenna geometry when considering the polarization diversity in the detection and characterization of canonical objects. [1] http://www.sense-city.univ-paris-est.fr/index.php

A real-time standard parts inspection based on deep learning

NASA Astrophysics Data System (ADS)

Xu, Kuan; Li, XuDong; Jiang, Hongzhi; Zhao, Huijie

2017-10-01

Since standard parts are necessary components in mechanical structure like bogie and connector. These mechanical structures will be shattered or loosen if standard parts are lost. So real-time standard parts inspection systems are essential to guarantee their safety. Researchers would like to take inspection systems based on deep learning because it works well in image with complex backgrounds which is common in standard parts inspection situation. A typical inspection detection system contains two basic components: feature extractors and object classifiers. For the object classifier, Region Proposal Network (RPN) is one of the most essential architectures in most state-of-art object detection systems. However, in the basic RPN architecture, the proposals of Region of Interest (ROI) have fixed sizes (9 anchors for each pixel), they are effective but they waste much computing resources and time. In standard parts detection situations, standard parts have given size, thus we can manually choose sizes of anchors based on the ground-truths through machine learning. The experiments prove that we could use 2 anchors to achieve almost the same accuracy and recall rate. Basically, our standard parts detection system could reach 15fps on NVIDIA GTX1080 (GPU), while achieving detection accuracy 90.01% mAP.

Automatic Railway Traffic Object Detection System Using Feature Fusion Refine Neural Network under Shunting Mode.

PubMed

Ye, Tao; Wang, Baocheng; Song, Ping; Li, Juan

2018-06-12

Many accidents happen under shunting mode when the speed of a train is below 45 km/h. In this mode, train attendants observe the railway condition ahead using the traditional manual method and tell the observation results to the driver in order to avoid danger. To address this problem, an automatic object detection system based on convolutional neural network (CNN) is proposed to detect objects ahead in shunting mode, which is called Feature Fusion Refine neural network (FR-Net). It consists of three connected modules, i.e., the depthwise-pointwise convolution, the coarse detection module, and the object detection module. Depth-wise-pointwise convolutions are used to improve the detection in real time. The coarse detection module coarsely refine the locations and sizes of prior anchors to provide better initialization for the subsequent module and also reduces search space for the classification, whereas the object detection module aims to regress accurate object locations and predict the class labels for the prior anchors. The experimental results on the railway traffic dataset show that FR-Net achieves 0.8953 mAP with 72.3 FPS performance on a machine with a GeForce GTX1080Ti with the input size of 320 × 320 pixels. The results imply that FR-Net takes a good tradeoff both on effectiveness and real time performance. The proposed method can meet the needs of practical application in shunting mode.

Rapid Object Detection Systems, Utilising Deep Learning and Unmanned Aerial Systems (uas) for Civil Engineering Applications

NASA Astrophysics Data System (ADS)

Griffiths, D.; Boehm, J.

2018-05-01

With deep learning approaches now out-performing traditional image processing techniques for image understanding, this paper accesses the potential of rapid generation of Convolutional Neural Networks (CNNs) for applied engineering purposes. Three CNNs are trained on 275 UAS-derived and freely available online images for object detection of 3m2 segments of railway track. These includes two models based on the Faster RCNN object detection algorithm (Resnet and Incpetion-Resnet) as well as the novel onestage Focal Loss network architecture (Retinanet). Model performance was assessed with respect to three accuracy metrics. The first two consisted of Intersection over Union (IoU) with thresholds 0.5 and 0.1. The last assesses accuracy based on the proportion of track covered by object detection proposals against total track length. In under six hours of training (and two hours of manual labelling) the models detected 91.3 %, 83.1 % and 75.6 % of track in the 500 test images acquired from the UAS survey Retinanet, Resnet and Inception-Resnet respectively. We then discuss the potential for such applications of such systems within the engineering field for a range of scenarios.

Exploring Sources of Gravitational Waves From Star Cluster Dynamics

NASA Astrophysics Data System (ADS)

Fuhrman, Joshua; Geller, Aaron M.; Rodriguez, Carl L.; Rasio, Frederic A.

2017-01-01

The recent detection of ripples in space-time by the Laser Interferometer Gravitational-wave Observatory (LIGO) has ushered in the age of gravitational wave astronomy. Binary black hole systems formed in the center of modest star clusters offer a possible gravitational wave source detectable by the LIGO or Laser Interferometer Space Antennae (LISA) collaborations. We simulate clusters containing 1-40K objects using direct integration from a customized version of NBODY6++GPU. We identify Binary Black Hole (BBH) objects of interest by an inspiral time sufficiently less than the age of the universe such that their coalescence might be detectable. Such objects are tracked through time within our N-body simulations to characterize the role of dynamics in the evolution of the BBH system using member exchanges and large orbital eccentricity changes as indicators of dynamic’s influence. We produce 41 BBH system candidates for detection by LIGO, all of which are dynamically formed. We observe several trends in the production of these potential BBH LIGO sources: a low-N cutoff in initial cluster size between 1-5K objects, high eccentricity oscillations, and the frequent formation of stable triple systems with the BBH as the inner binary.

Digital image profilers for detecting faint sources which have bright companions, phase 2

NASA Technical Reports Server (NTRS)

Morris, Elena; Flint, Graham

1991-01-01

A breadboard image profiling system developed for the first phase of this project demonstrated the potential for detecting extremely faint optical sources in the presence of light companions. Experimental data derived from laboratory testing of the device supports the theory that image profilers of this type may approach the theoretical limit imposed by photon statistics. The objective of Phase 2 of this program is the development of a ground-based multichannel image profiling system capable of detecting faint stellar objects slightly displaced from brighter stars. We have finalized the multichannel image profiling system and attempted three field tests.

A habituation based approach for detection of visual changes in surveillance camera

NASA Astrophysics Data System (ADS)

Sha'abani, M. N. A. H.; Adan, N. F.; Sabani, M. S. M.; Abdullah, F.; Nadira, J. H. S.; Yasin, M. S. M.

2017-09-01

This paper investigates a habituation based approach in detecting visual changes using video surveillance systems in a passive environment. Various techniques have been introduced for dynamic environment such as motion detection, object classification and behaviour analysis. However, in a passive environment, most of the scenes recorded by the surveillance system are normal. Therefore, implementing a complex analysis all the time in the passive environment resulting on computationally expensive, especially when using a high video resolution. Thus, a mechanism of attention is required, where the system only responds to an abnormal event. This paper proposed a novelty detection mechanism in detecting visual changes and a habituation based approach to measure the level of novelty. The objective of the paper is to investigate the feasibility of the habituation based approach in detecting visual changes. Experiment results show that the approach are able to accurately detect the presence of novelty as deviations from the learned knowledge.

Scatter in Cargo Radiography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, Erin A.; Caggiano, Joseph A.; Runkle, Robert C.

As a complement to passive detection systems, radiographic inspection of cargo is an increasingly important tool for homeland security because it has the potential to detect highly attenuating objects associated with special nuclear material or surrounding shielding. Detecting such objects relies on high image contrast between regions of different density and atomic number (Z). Threat detection is affected by scatter of the interrogating beam, both in the cargo and surrounding objects, which degrades image contrast. Here, we work to determine the extent to which scatter plays a role in radiographic imaging of cargo containers.

The feasibility test of state-of-the-art face detection algorithms for vehicle occupant detection

NASA Astrophysics Data System (ADS)

Makrushin, Andrey; Dittmann, Jana; Vielhauer, Claus; Langnickel, Mirko; Kraetzer, Christian

2010-01-01

Vehicle seat occupancy detection systems are designed to prevent the deployment of airbags at unoccupied seats, thus avoiding the considerable cost imposed by the replacement of airbags. Occupancy detection can also improve passenger comfort, e.g. by activating air-conditioning systems. The most promising development perspectives are seen in optical sensing systems which have become cheaper and smaller in recent years. The most plausible way to check the seat occupancy by occupants is the detection of presence and location of heads, or more precisely, faces. This paper compares the detection performances of the three most commonly used and widely available face detection algorithms: Viola- Jones, Kienzle et al. and Nilsson et al. The main objective of this work is to identify whether one of these systems is suitable for use in a vehicle environment with variable and mostly non-uniform illumination conditions, and whether any one face detection system can be sufficient for seat occupancy detection. The evaluation of detection performance is based on a large database comprising 53,928 video frames containing proprietary data collected from 39 persons of both sexes and different ages and body height as well as different objects such as bags and rearward/forward facing child restraint systems.

Moving Object Detection on a Vehicle Mounted Back-Up Camera

PubMed Central

Kim, Dong-Sun; Kwon, Jinsan

2015-01-01

In the detection of moving objects from vision sources one usually assumes that the scene has been captured by stationary cameras. In case of backing up a vehicle, however, the camera mounted on the vehicle moves according to the vehicle’s movement, resulting in ego-motions on the background. This results in mixed motion in the scene, and makes it difficult to distinguish between the target objects and background motions. Without further treatments on the mixed motion, traditional fixed-viewpoint object detection methods will lead to many false-positive detection results. In this paper, we suggest a procedure to be used with the traditional moving object detection methods relaxing the stationary cameras restriction, by introducing additional steps before and after the detection. We also decribe the implementation as a FPGA platform along with the algorithm. The target application of this suggestion is use with a road vehicle’s rear-view camera systems. PMID:26712761

Comparison of detectability in step-and-shoot mode and continuous mode digital tomosynthesis systems

NASA Astrophysics Data System (ADS)

Lee, Changwoo; Han, Minah; Baek, Jongduk

2017-03-01

Digital tomosynthesis system has been widely used in chest, dental, and breast imaging. Since the digital tomosynthesis system provides volumetric images from multiple projection data, structural noise inherent in X-ray radiograph can be reduced, and thus signal detection performance is improved. Currently, tomosynthesis system uses two data acquisition modes: step-and-shoot mode and continuous mode. Several studies have been conducted to compare the system performance of two acquisition modes with respect to spatial resolution and contrast. In this work, we focus on signal detectability in step-and-shoot mode and continuous mode. For evaluation, uniform background is considered, and eight spherical objects with diameters of 0.5, 0.8, 1, 2, 3, 5, 8, 10 mm are used as signals. Projection data with and without spherical objects are acquired in step-and-shoot mode and continuous mode, respectively, and quantum noise are added. Then, noisy projection data are reconstructed by FDK algorithm. To compare the detection performance of two acquisition modes, we calculate task signal-to-noise ratio (SNR) of channelized Hotelling observer with Laguerre-Gauss channels for each spherical object. While the task-SNR values of two acquisition modes are similar for spherical objects larger than 1 mm diameter, step-and-shoot mode yields higher detectability for small signal sizes. The main reason of this behavior is that small signal is more affected by X-ray tube motion blur than large signal. Our results indicate that it is beneficial to use step-and-shoot data acquisition mode to improve the detectability of small signals (i.e., less than 1 mm diameter) in digital tomosynthesis systems.

The Fundamentals of Thermal Imaging Systems.

DTIC Science & Technology

1979-05-10

detection , recognition, or identification, of real ’coene objects aire discussed. It is hoped that the text will be useful to FLIR designers, evaluators...AND ANDERSON EXPERIMENT ........................ 205 Appendix F - BASIC SNR AND DETECTIVITY RELATIONS ................................... 209 Appendix... detection , recognition, or identification, of real scene objects are discussed. I• It is hoped that the material in the text will be useful to

Overseas testing of a multisensor landmine detection system: results and lessons learned

NASA Astrophysics Data System (ADS)

Keranen, Joe G.; Topolosky, Zeke

2009-05-01

The Nemesis detection system has been developed to provide an efficient and reliable unmanned, multi-sensor, groundbased platform to detect and mark landmines. The detection system consists of two detection sensor arrays: a Ground Penetrating Synthetic Aperture Radar (GPSAR) developed by Planning Systems, Inc. (PSI) and an electromagnetic induction (EMI) sensor array developed by Minelab Electronics, PTY. Limited. Under direction of the Night Vision and Electronic Sensors Directorate (NVESD), overseas testing was performed at Kampong Chhnang Test Center (KCTC), Cambodia, from May 12-30, 2008. Test objectives included: evaluation of detection performance, demonstration of real-time visualization and alarm generation, and evaluation of system operational efficiency. Testing was performed on five sensor test lanes, each consisting of a unique soil mixture and three off-road lanes which include curves, overgrowth, potholes, and non-uniform lane geometry. In this paper, we outline the test objectives, procedures, results, and lessons learned from overseas testing. We also describe the current state of the system, and plans for future enhancements and modifications including clutter rejection and feature-level fusion.

Submerged Object Detection and Classification System

DTIC Science & Technology

1993-04-16

example of this type of system is a conventional sonar device wherein a highly directional beam of sonic energy periodically radiates from a...scanning transducer which in turn operates as a receiver to detect echoes reflected from any object within the path of 15 propagation. Sonar devices...classification, which requires relatively high frequency signals. Sonar devices also have the shortcoming of sensing background noise generated by

Target detection using microwave irradiances from natural sources: A passive, local and global surveillance system

NASA Technical Reports Server (NTRS)

Stacey, J. M.

1984-01-01

Detection of metal objects on or near the Earth's surface was investigated using existing, passive, microwave sensors operating from Earth orbit. The range equations are derived from basic microwave principles and theories and the expressions are given explicitly to estimate the signal to noise ratio for detecting metal targets operating as bistatic scatterers. Actual measurements are made on a range of metal objects observed from orbit using existing passive microwave receiving systems. The details of the measurements and the results are tabulated and discussed. The advantages of a passive microwave sensor as it is applied to surveillance of metal objects as viewed from aerial platforms or from orbit, are examined.

Chemical sensing system for classification of minelike objects by explosives detection

NASA Astrophysics Data System (ADS)

Chambers, William B.; Rodacy, Philip J.; Jones, Edwin E.; Gomez, Bernard J.; Woodfin, Ronald L.

1998-09-01

Sandia National Laboratories has conducted research in chemical sensing and analysis of explosives for many years. Recently, that experience has been directed towards detecting mines and unexploded ordnance (UXO) by sensing the low-level explosive signatures associated with these objects. Our focus has been on the classification of UXO in shallow water and anti-personnel/anti tank mines on land. The objective of this work is to develop a field portable chemical sensing system which can be used to examine mine-like objects (MLO) to determine whether there are explosive molecules associated with the MLO. Two sampling subsystems have been designed, one for water collection and one for soil/vapor sampling. The water sampler utilizes a flow-through chemical adsorbent canister to extract and concentrate the explosive molecules. Explosive molecules are thermally desorbed from the concentrator and trapped in a focusing stage for rapid desorption into an ion-mobility spectrometer (IMS). We will describe a prototype system which consists of a sampler, concentrator-focuser, and detector. The soil sampler employs a light-weight probe for extracting and concentrating explosive vapor from the soil in the vicinity of an MLO. The chemical sensing system is capable of sub-part-per-billion detection of TNT and related explosive munition compounds. We will present the results of field and laboratory tests on buried landmines, which demonstrate our ability to detect the explosive signatures associated with these objects.

Kalman filter-based tracking of moving objects using linear ultrasonic sensor array for road vehicles

NASA Astrophysics Data System (ADS)

Li, Shengbo Eben; Li, Guofa; Yu, Jiaying; Liu, Chang; Cheng, Bo; Wang, Jianqiang; Li, Keqiang

2018-01-01

Detection and tracking of objects in the side-near-field has attracted much attention for the development of advanced driver assistance systems. This paper presents a cost-effective approach to track moving objects around vehicles using linearly arrayed ultrasonic sensors. To understand the detection characteristics of a single sensor, an empirical detection model was developed considering the shapes and surface materials of various detected objects. Eight sensors were arrayed linearly to expand the detection range for further application in traffic environment recognition. Two types of tracking algorithms, including an Extended Kalman filter (EKF) and an Unscented Kalman filter (UKF), for the sensor array were designed for dynamic object tracking. The ultrasonic sensor array was designed to have two types of fire sequences: mutual firing or serial firing. The effectiveness of the designed algorithms were verified in two typical driving scenarios: passing intersections with traffic sign poles or street lights, and overtaking another vehicle. Experimental results showed that both EKF and UKF had more precise tracking position and smaller RMSE (root mean square error) than a traditional triangular positioning method. The effectiveness also encourages the application of cost-effective ultrasonic sensors in the near-field environment perception in autonomous driving systems.

Methods and Apparatus for Detecting Defects in an Object of Interest

NASA Technical Reports Server (NTRS)

Hartman, John K. (Inventor); Pearson, Lee H (Inventor)

2017-01-01

A method for detecting defects in an object of interest comprises applying an ultrasonic signal including a tone burst having a predetermined frequency and number of cycles into an object of interest, receiving a return signal reflected from the object of interest, and processing the return signal to detect defects in at least one inner material. The object may have an outer material and the at least one inner material that have different acoustic impedances. An ultrasonic sensor system includes an ultrasonic sensor configured to generate an ultrasonic signal having a tone burst at a predetermined frequency corresponding to a resonant frequency of an outer material of an object of interest.

Object Detection for Agricultural and Construction Environments Using an Ultrasonic Sensor.

PubMed

Dvorak, J S; Stone, M L; Self, K P

2016-04-01

This study tested an ultrasonic sensor's ability to detect several objects commonly encountered in outdoor agricultural or construction environments: a water jug, a sheet of oriented strand board (OSB), a metalfence post, a human model, a wooden fence post, a Dracaena plant, a juniper plant, and a dog model. Tests were performed with each target object at distances from 0.01 to 3 m. Five tests were performed with each object at each location, and the sensor's ability to detect the object during each test was categorized as "undetected," "intermittent," "incorrect distance," or "good." Rigid objects that presented a larger surface area to the sensor, such as the water jug and OSB, were better detected than objects with a softer surface texture, which were occasionally not detected as the distance approached 3 m. Objects with extremely soft surface texture, such as the dog model, could be undetected at almost any distance from the sensor. The results of this testing should help designers offuture systems for outdoor environments, as the target objects tested can be found in nearly any agricultural or construction environment.

DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field.

PubMed

Christiansen, Peter; Nielsen, Lars N; Steen, Kim A; Jørgensen, Rasmus N; Karstoft, Henrik

2016-11-11

Convolutional neural network (CNN)-based systems are increasingly used in autonomous vehicles for detecting obstacles. CNN-based object detection and per-pixel classification (semantic segmentation) algorithms are trained for detecting and classifying a predefined set of object types. These algorithms have difficulties in detecting distant and heavily occluded objects and are, by definition, not capable of detecting unknown object types or unusual scenarios. The visual characteristics of an agriculture field is homogeneous, and obstacles, like people, animals and other obstacles, occur rarely and are of distinct appearance compared to the field. This paper introduces DeepAnomaly, an algorithm combining deep learning and anomaly detection to exploit the homogenous characteristics of a field to perform anomaly detection. We demonstrate DeepAnomaly as a fast state-of-the-art detector for obstacles that are distant, heavily occluded and unknown. DeepAnomaly is compared to state-of-the-art obstacle detectors including "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks" (RCNN). In a human detector test case, we demonstrate that DeepAnomaly detects humans at longer ranges (45-90 m) than RCNN. RCNN has a similar performance at a short range (0-30 m). However, DeepAnomaly has much fewer model parameters and (182 ms/25 ms =) a 7.28-times faster processing time per image. Unlike most CNN-based methods, the high accuracy, the low computation time and the low memory footprint make it suitable for a real-time system running on a embedded GPU (Graphics Processing Unit).

DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field

PubMed Central

Christiansen, Peter; Nielsen, Lars N.; Steen, Kim A.; Jørgensen, Rasmus N.; Karstoft, Henrik

2016-01-01

Convolutional neural network (CNN)-based systems are increasingly used in autonomous vehicles for detecting obstacles. CNN-based object detection and per-pixel classification (semantic segmentation) algorithms are trained for detecting and classifying a predefined set of object types. These algorithms have difficulties in detecting distant and heavily occluded objects and are, by definition, not capable of detecting unknown object types or unusual scenarios. The visual characteristics of an agriculture field is homogeneous, and obstacles, like people, animals and other obstacles, occur rarely and are of distinct appearance compared to the field. This paper introduces DeepAnomaly, an algorithm combining deep learning and anomaly detection to exploit the homogenous characteristics of a field to perform anomaly detection. We demonstrate DeepAnomaly as a fast state-of-the-art detector for obstacles that are distant, heavily occluded and unknown. DeepAnomaly is compared to state-of-the-art obstacle detectors including “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks” (RCNN). In a human detector test case, we demonstrate that DeepAnomaly detects humans at longer ranges (45–90 m) than RCNN. RCNN has a similar performance at a short range (0–30 m). However, DeepAnomaly has much fewer model parameters and (182 ms/25 ms =) a 7.28-times faster processing time per image. Unlike most CNN-based methods, the high accuracy, the low computation time and the low memory footprint make it suitable for a real-time system running on a embedded GPU (Graphics Processing Unit). PMID:27845717

NORAD's PARCS small satellite tests (1976 and 1978)

NASA Technical Reports Server (NTRS)

Kessler, D. J.

1985-01-01

NORAD sponsored small satellite tests in 1976 and 1978. The purpose of the tests was to use their more sensitive radar to determine the number of Earth orbiting objects which are not part of the official catalogue. Both tests used the PARCS radar. The characteristics of this radar are given. The detection capability of NORAD's operational system is estimated and compared to the PARC's radar sensitivity during these tests. The tests only slightly improved the detection capability, and the largest improvements were at the lowest and highest regions of its sensitivity range. The major conclusion of the test is that 17.7% of the objects detected were uncorrelated (i.e., not in the official catalogue). However, perhaps most significant is the altitutde and size distribution of detected objects are illustrated. The 1978 results are also summarized. This test concluded that at least 7% of the objects detected were not in the official catalogue. Another 6% of the detected objects were not tracked well enough to determine their status. Again, a large percentage of the detected objects at lower altitudes were not in the catalogue.

NORAD's PARCS small satellite tests (1976 and 1978)

NASA Astrophysics Data System (ADS)

Kessler, D. J.

1985-03-01

NORAD sponsored small satellite tests in 1976 and 1978. The purpose of the tests was to use their more sensitive radar to determine the number of Earth orbiting objects which are not part of the official catalogue. Both tests used the PARCS radar. The characteristics of this radar are given. The detection capability of NORAD's operational system is estimated and compared to the PARC's radar sensitivity during these tests. The tests only slightly improved the detection capability, and the largest improvements were at the lowest and highest regions of its sensitivity range. The major conclusion of the test is that 17.7% of the objects detected were uncorrelated (i.e., not in the official catalogue). However, perhaps most significant is the altitutde and size distribution of detected objects are illustrated. The 1978 results are also summarized. This test concluded that at least 7% of the objects detected were not in the official catalogue. Another 6% of the detected objects were not tracked well enough to determine their status. Again, a large percentage of the detected objects at lower altitudes were not in the catalogue.

Damage Detection and Verification System (DDVS) for In-Situ Health Monitoring

NASA Technical Reports Server (NTRS)

Williams, Martha K.; Lewis, Mark; Szafran, J.; Shelton, C.; Ludwig, L.; Gibson, T.; Lane, J.; Trautwein, T.

2015-01-01

Project presentation for Game Changing Program Smart Book Release. Detection and Verification System (DDVS) expands the Flat Surface Damage Detection System (FSDDS) sensory panels damage detection capabilities and includes an autonomous inspection capability utilizing cameras and dynamic computer vision algorithms to verify system health. Objectives of this formulation task are to establish the concept of operations, formulate the system requirements for a potential ISS flight experiment, and develop a preliminary design of an autonomous inspection capability system that will be demonstrated as a proof-of-concept ground based damage detection and inspection system.

Portable Microleak-Detection System

NASA Technical Reports Server (NTRS)

Rivers, H. Kevin; Sikora, Joseph G.; Sankaran, Sankara N.

2007-01-01

The figure schematically depicts a portable microleak-detection system that has been built especially for use in testing hydrogen tanks made of polymer-matrix composite materials. (As used here, microleak signifies a leak that is too small to be detectable by the simple soap-bubble technique.) The system can also be used to test for microleaks in tanks that are made of other materials and that contain gases other than hydrogen. Results of calibration tests have shown that measurement errors are less than 10 percent for leak rates ranging from 0.3 to 200 cm3/min. Like some other microleak-detection systems, this system includes a vacuum pump and associated plumbing for sampling the leaking gas, and a mass spectrometer for analyzing the molecular constituents of the gas. The system includes a flexible vacuum chamber that can be attached to the outer surface of a tank or other object of interest that is to be tested for leakage (hereafter denoted, simply, the test object). The gas used in a test can be the gas or vapor (e.g., hydrogen in the original application) to be contained by the test object. Alternatively, following common practice in leak testing, helium can be used as a test gas. In either case, the mass spectrometer can be used to verify that the gas measured by the system is the test gas rather than a different gas and, hence, that the leak is indeed from the test object.

Trainable Cataloging for Digital Image Libraries with Applications to Volcano Detection

NASA Technical Reports Server (NTRS)

Burl, M. C.; Fayyad, U. M.; Perona, P.; Smyth, P.

1995-01-01

Users of digital image libraries are often not interested in image data per se but in derived products such as catalogs of objects of interest. Converting an image database into a usable catalog is typically carried out manually at present. For many larger image databases the purely manual approach is completely impractical. In this paper we describe the development of a trainable cataloging system: the user indicates the location of the objects of interest for a number of training images and the system learns to detect and catalog these objects in the rest of the database. In particular we describe the application of this system to the cataloging of small volcanoes in radar images of Venus. The volcano problem is of interest because of the scale (30,000 images, order of 1 million detectable volcanoes), technical difficulty (the variability of the volcanoes in appearance) and the scientific importance of the problem. The problem of uncertain or subjective ground truth is of fundamental importance in cataloging problems of this nature and is discussed in some detail. Experimental results are presented which quantify and compare the detection performance of the system relative to human detection performance. The paper concludes by discussing the limitations of the proposed system and the lessons learned of general relevance to the development of digital image libraries.

Object tracking via background subtraction for monitoring illegal activity in crossroad

NASA Astrophysics Data System (ADS)

Ghimire, Deepak; Jeong, Sunghwan; Park, Sang Hyun; Lee, Joonwhoan

2016-07-01

In the field of intelligent transportation system a great number of vision-based techniques have been proposed to prevent pedestrians from being hit by vehicles. This paper presents a system that can perform pedestrian and vehicle detection and monitoring of illegal activity in zebra crossings. In zebra crossing, according to the traffic light status, to fully avoid a collision, a driver or pedestrian should be warned earlier if they possess any illegal moves. In this research, at first, we detect the traffic light status of pedestrian and monitor the crossroad for vehicle pedestrian moves. The background subtraction based object detection and tracking is performed to detect pedestrian and vehicles in crossroads. Shadow removal, blob segmentation, trajectory analysis etc. are used to improve the object detection and classification performance. We demonstrate the experiment in several video sequences which are recorded in different time and environment such as day time and night time, sunny and raining environment. Our experimental results show that such simple and efficient technique can be used successfully as a traffic surveillance system to prevent accidents in zebra crossings.

High resolution, high rate x-ray spectrometer

DOEpatents

Goulding, F.S.; Landis, D.A.

1983-07-14

It is an object of the invention to provide a pulse processing system for use with detected signals of a wide dynamic range which is capable of very high counting rates, with high throughput, with excellent energy resolution and a high signal-to-noise ratio. It is a further object to provide a pulse processing system wherein the fast channel resolving time is quite short and substantially independent of the energy of the detected signals. Another object is to provide a pulse processing system having a pile-up rejector circuit which will allow the maximum number of non-interfering pulses to be passed to the output. It is also an object of the invention to provide new methods for generating substantially symmetrically triangular pulses for use in both the main and fast channels of a pulse processing system.

Cyber-Physical Attacks With Control Objectives

DOE PAGES

Chen, Yuan; Kar, Soummya; Moura, Jose M. F.

2017-08-18

This study studies attackers with control objectives against cyber-physical systems (CPSs). The goal of the attacker is to counteract the CPS's controller and move the system to a target state while evading detection. We formulate a cost function that reflects the attacker's goals, and, using dynamic programming, we show that the optimal attack strategy reduces to a linear feedback of the attacker's state estimate. By changing the parameters of the cost function, we show how an attacker can design optimal attacks to balance the control objective and the detection avoidance objective. In conclusion, we provide a numerical illustration based onmore » a remotely controlled helicopter under attack.« less

Cyber-Physical Attacks With Control Objectives

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yuan; Kar, Soummya; Moura, Jose M. F.

This study studies attackers with control objectives against cyber-physical systems (CPSs). The goal of the attacker is to counteract the CPS's controller and move the system to a target state while evading detection. We formulate a cost function that reflects the attacker's goals, and, using dynamic programming, we show that the optimal attack strategy reduces to a linear feedback of the attacker's state estimate. By changing the parameters of the cost function, we show how an attacker can design optimal attacks to balance the control objective and the detection avoidance objective. In conclusion, we provide a numerical illustration based onmore » a remotely controlled helicopter under attack.« less

Lidar-based door and stair detection from a mobile robot

NASA Astrophysics Data System (ADS)

Bansal, Mayank; Southall, Ben; Matei, Bogdan; Eledath, Jayan; Sawhney, Harpreet

2010-04-01

We present an on-the-move LIDAR-based object detection system for autonomous and semi-autonomous unmanned vehicle systems. In this paper we make several contributions: (i) we describe an algorithm for real-time detection of objects such as doors and stairs in indoor environments; (ii) we describe efficient data structures and algorithms for processing 3D point clouds acquired by laser scanners in a streaming manner, which minimize the memory copying and access. We show qualitative results demonstrating the effectiveness of our approach on runs in an indoor office environment.

Determining the orientation of depth-rotated familiar objects.

PubMed

Niimi, Ryosuke; Yokosawa, Kazuhiko

2008-02-01

How does the human visual system determine the depth-orientation of familiar objects? We examined reaction times and errors in the detection of 15 degrees differences in the depth orientations of two simultaneously presented familiar objects, which were the same objects (Experiment 1) or different objects (Experiment 2). Detection of orientation differences was best for 0 degrees (front) and 180 degrees (back), while 45 degrees and 135 degrees yielded poorer results, and 90 degrees (side) showed intermediate results, suggesting that the visual system is tuned for front, side and back orientations. We further found that those advantages are due to orientation-specific features such as horizontal linear contours and symmetry, since the 90 degrees advantage was absent for objects with curvilinear contours, and asymmetric object diminished the 0 degrees and 180 degrees advantages. We conclude that the efficiency of visually determining object orientation is highly orientation-dependent, and object orientation may be perceived in favor of front-back axes.

Traffic monitoring with distributed smart cameras

NASA Astrophysics Data System (ADS)

Sidla, Oliver; Rosner, Marcin; Ulm, Michael; Schwingshackl, Gert

2012-01-01

The observation and monitoring of traffic with smart visions systems for the purpose of improving traffic safety has a big potential. Today the automated analysis of traffic situations is still in its infancy--the patterns of vehicle motion and pedestrian flow in an urban environment are too complex to be fully captured and interpreted by a vision system. 3In this work we present steps towards a visual monitoring system which is designed to detect potentially dangerous traffic situations around a pedestrian crossing at a street intersection. The camera system is specifically designed to detect incidents in which the interaction of pedestrians and vehicles might develop into safety critical encounters. The proposed system has been field-tested at a real pedestrian crossing in the City of Vienna for the duration of one year. It consists of a cluster of 3 smart cameras, each of which is built from a very compact PC hardware system in a weatherproof housing. Two cameras run vehicle detection and tracking software, one camera runs a pedestrian detection and tracking module based on the HOG dectection principle. All 3 cameras use sparse optical flow computation in a low-resolution video stream in order to estimate the motion path and speed of objects. Geometric calibration of the cameras allows us to estimate the real-world co-ordinates of detected objects and to link the cameras together into one common reference system. This work describes the foundation for all the different object detection modalities (pedestrians, vehicles), and explains the system setup, tis design, and evaluation results which we have achieved so far.

Lateral-Line Detection of Underwater Objects: From Goldfish to Submarines

NASA Astrophysics Data System (ADS)

van Hemmen, J. Leo

2010-03-01

Fish and some aquatic amphibians use their mechanosensory lateral-line system to navigate by means of hydrodynamic cues. How a fish determines an object's position and shape only through the lateral-line system and the ensuing neuronal processing is still a challenging problem. Our studies have shown that both stimulus position and stimulus form can be determined within the range of about one fish length and are encoded through the response of the afferent nerves originating from the detectors. A minimal detection model of a vibrating sphere (a dipole) has now been extended to other stimuli such as translating spheres, ellipsoids, or even wakes (vortex rings). The theoretical model is fully verified by experimental data. We have also constructed an underwater robot with an artificial lateral-line system designed to detect e.g. the presence of walls by measuring the change of water flow around the body. We will show how a simple model fits experimental results obtained from trout and goldfish and how a submarine may well be able to detect underwater objects by using an artificial lateral-line system.

Near-infrared high-resolution real-time omnidirectional imaging platform for drone detection

NASA Astrophysics Data System (ADS)

Popovic, Vladan; Ott, Beat; Wellig, Peter; Leblebici, Yusuf

2016-10-01

Recent technological advancements in hardware systems have made higher quality cameras. State of the art panoramic systems use them to produce videos with a resolution of 9000 x 2400 pixels at a rate of 30 frames per second (fps).1 Many modern applications use object tracking to determine the speed and the path taken by each object moving through a scene. The detection requires detailed pixel analysis between two frames. In fields like surveillance systems or crowd analysis, this must be achieved in real time.2 In this paper, we focus on the system-level design of multi-camera sensor acquiring near-infrared (NIR) spectrum and its ability to detect mini-UAVs in a representative rural Swiss environment. The presented results show the UAV detection from the trial that we conducted during a field trial in August 2015.

The MetaTelescope, a System for the Detection of Objects in Low and Higher Earth Orbits

NASA Astrophysics Data System (ADS)

Boer, M.

We present an original design involving several telescopes for the detection of mobiles in space over a very wide field of view. The system uses relatively simple and cheap telescopes associated with commercial CCD cameras that can be placed either in a single location or in relatively close (100m - 10km) locations. This last set-up opens the possibility of detecting parallaxes, but sky conditions should remain almost identical. Areas on the order of 800 square degrees can be surveyed. The system is versatile, i.e. it can detect and follow up objects either in the LEO or higher orbits. We will present the system, how it can be operated in order to have a more efficient setup while using even less telescopes, and possible implementations for space surveillance activities.

Visual Salience in the Change Detection Paradigm: The Special Role of Object Onset

ERIC Educational Resources Information Center

Cole, Geoff G.; Kentridge, Robert W.; Heywood, Charles A.

2004-01-01

The relative efficacy with which appearance of a new object orients visual attention was investigated. At issue is whether the visual system treats onset as being of particular importance or only 1 of a number of stimulus events equally likely to summon attention. Using the 1-shot change detection paradigm, the authors compared detectability of…

Discrimination Report: A Multisensor system for detection andcharacterization of UXO, ESTCP Project MM-0437,

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gasperikova, Erika; Smith, J. Torquil; Morrison, H.Frank

2008-01-14

The Berkeley UXO Discriminator (BUD) is an optimally designed active electromagnetic system that not only detects but also characterizes UXO. The performance of the system is governed by a target size-depth curve. BUD was designed to detect UXO in the 20 mm to 155 mm size range for depths between 0 and 1.5 m, and to characterize them in a depth range from 0 to 1.1 m. The system incorporates three orthogonal transmitters and eight pairs of differenced receivers. Eight receiver coils are placed horizontally along the two diagonals of the upper and lower planes of the two horizontal transmittermore » loops. These receiver coil pairs are located on symmetry lines through the center of the system and each pair sees identical fields during the on-time of the pulse in all of the transmitter coils. They are wired in opposition to produce zero output during the on-time of the pulses in three orthogonal transmitters. Moreover, this configuration dramatically reduces noise in the measurements by canceling the background electromagnetic fields (these fields are uniform over the scale of the receiver array and are consequently nulled by the differencing operation), and by canceling the noise contributed by the tilt motion of the receivers in the Earth's magnetic field, and greatly enhances receiver sensitivity to the gradients of the target response. BUD is mounted on a small cart to assure system mobility. System positioning is provided by a Real Time Kinematic (RTK) GPS receiver. The system has two modes of operation: (1) the search mode, in which BUD moves along a profile and exclusively detects targets in its vicinity providing target depth and horizontal location, and (2) the discrimination mode, in which BUD is stationary above a target, and determines three discriminating polarizability responses together with the object location and orientation from a single position of the system. The detection performance of the system is governed by a size-depth curve shown in Figure 2. This curve was calculated for BUD assuming that the receiver plane is 0.2 m above the ground. Figure 2 shows that, for example, BUD can detect an object with 0.1 m diameter down to the depth of 0.9 m with a depth uncertainty of 10%. Any objects buried at a depth of more than 1.3 m will have a low probability of detection. The discrimination performance of the system is governed by a size-depth curve shown in Figure 3. Again, this curve was calculated for BUD assuming that the receiver plane is 0.2 m above the ground. Figure 3 shows that, for example, BUD can determine the polarizability of an object with 0.1 m diameter down to the depth of 0.63 m with polarizability uncertainty of 10%. Any objects buried at the depth more than 0.9 m will have a low discrimination probability. Object orientation estimates and equivalent dipole polarizability estimates used for large and shallow UXO/scrap discrimination are more problematic as they are affected by higher order (non-dipole) terms induced in objects due to source field gradients along the length of the objects. For example, a vertical 0.4 m object directly below the system needs to be about 0.90 m deep for perturbations due to gradients along the length of the object to be of the order of 20% of the uniform field object response. Similarly, vertical objects 0.5 m, and 0.6 m long need to be 1.15 m, and 1.42 m, respectively, below the system. For horizontal objects the effect of gradients across the object diameter are much smaller. For example, 155 mm and 105 mm projectiles need to be only 0.30 m, and 0.19 m, respectively, below the system. A polarizability index (in cm{sup 3}), which is an average value of the product of time (in seconds) and polarizability rate (in m{sup 3}/s) over the 34 sample times logarithmically spaced from 143 to 1300 {micro}s, and three polarizabilities, can be calculated for any object. We used this polarizability index to decide when the object is in a uniform source field. Objects with the polarizability index smaller than 600 cm{sup 3} and deeper than 1.8 m below BUD, or smaller than 200 cm{sup 3} and deeper than 1.35 m, or smaller than 80 cm{sup 3} and deeper than 0.90 m, or smaller than 9 cm{sup 3} and deeper than 0.20 m below BUD are sufficiently deep that the effects of vertical source field gradients should be less than 15%. All other objects are considered large and shallow objects. At the moment, interpretation software is available for a single object only. In case of multiple objects the software indicates the possible presence of metallic objects but is unable to provide characteristics of each individual object.« less

Detection Technique for Artificially Illuminated Objects in the Outer Solar System and Beyond

PubMed Central

Loeb, Abraham

2012-01-01

Abstract Existing and planned optical telescopes and surveys can detect artificially illuminated objects, comparable in total brightness to a major terrestrial city, at the outskirts of the Solar System. Orbital parameters of Kuiper belt objects (KBOs) are routinely measured to exquisite precisions of<10−3. Here, we propose to measure the variation of the observed flux F from such objects as a function of their changing orbital distances D. Sunlight-illuminated objects will show a logarithmic slope α ≡ (d log F/d log D)=−4, whereas artificially illuminated objects should exhibit α=−2. The proposed Large Synoptic Survey Telescope (LSST) and other planned surveys will provide superb data and allow measurement of α for thousands of KBOs. If objects with α=−2 are found, follow-up observations could measure their spectra to determine whether they are illuminated by artificial lighting. The search can be extended beyond the Solar System with future generations of telescopes on the ground and in space that would have the capacity to detect phase modulation due to very strong artificial illumination on the nightside of planets as they orbit their parent stars. Key Words: Astrobiology—SETI—Kuiper belt objects—Artificial illumination. Astrobiology 12, 290–294. PMID:22490065

Integrated active sensor system for real time vibration monitoring.

PubMed

Liang, Qijie; Yan, Xiaoqin; Liao, Xinqin; Cao, Shiyao; Lu, Shengnan; Zheng, Xin; Zhang, Yue

2015-11-05

We report a self-powered, lightweight and cost-effective active sensor system for vibration monitoring with multiplexed operation based on contact electrification between sensor and detected objects. The as-fabricated sensor matrix is capable of monitoring and mapping the vibration state of large amounts of units. The monitoring contents include: on-off state, vibration frequency and vibration amplitude of each unit. The active sensor system delivers a detection range of 0-60 Hz, high accuracy (relative error below 0.42%), long-term stability (10000 cycles). On the time dimension, the sensor can provide the vibration process memory by recording the outputs of the sensor system in an extend period of time. Besides, the developed sensor system can realize detection under contact mode and non-contact mode. Its high performance is not sensitive to the shape or the conductivity of the detected object. With these features, the active sensor system has great potential in automatic control, remote operation, surveillance and security systems.

Integrated active sensor system for real time vibration monitoring

PubMed Central

Liang, Qijie; Yan, Xiaoqin; Liao, Xinqin; Cao, Shiyao; Lu, Shengnan; Zheng, Xin; Zhang, Yue

2015-01-01

We report a self-powered, lightweight and cost-effective active sensor system for vibration monitoring with multiplexed operation based on contact electrification between sensor and detected objects. The as-fabricated sensor matrix is capable of monitoring and mapping the vibration state of large amounts of units. The monitoring contents include: on-off state, vibration frequency and vibration amplitude of each unit. The active sensor system delivers a detection range of 0–60 Hz, high accuracy (relative error below 0.42%), long-term stability (10000 cycles). On the time dimension, the sensor can provide the vibration process memory by recording the outputs of the sensor system in an extend period of time. Besides, the developed sensor system can realize detection under contact mode and non-contact mode. Its high performance is not sensitive to the shape or the conductivity of the detected object. With these features, the active sensor system has great potential in automatic control, remote operation, surveillance and security systems. PMID:26538293

Remote laser drilling and sampling system for the detection of concealed explosives

NASA Astrophysics Data System (ADS)

Wild, D.; Pschyklenk, L.; Theiß, C.; Holl, G.

2017-05-01

The detection of hazardous materials like explosives is a central issue in national security in the field of counterterrorism. One major task includes the development of new methods and sensor systems for the detection. Many existing remote or standoff methods like infrared or raman spectroscopy find their limits, if the hazardous material is concealed in an object. Imaging technologies using x-ray or terahertz radiation usually yield no information about the chemical content itself. However, the exact knowledge of the real threat potential of a suspicious object is crucial for disarming the device. A new approach deals with a laser drilling and sampling system for the use as verification detector for suspicious objects. Central part of the system is a miniaturised, diode pumped Nd:YAG laser oscillator-amplifier. The system allows drilling into most materials like metals, synthetics or textiles with bore hole diameters in the micron scale. During the drilling process, the hazardous material can be sampled for further investigation with suitable detection methods. In the reported work, laser induced breakdown spectroscopy (LIBS) is used to monitor the drilling process and to classify the drilled material. Also experiments were carried out to show the system's ability to not ignite even sensitive explosives like triacetone triperoxide (TATP). The detection of concealed hazardous material is shown for different explosives using liquid chromatography and ion mobility spectrometry.

Multimedia Security System for Security and Medical Applications

ERIC Educational Resources Information Center

Zhou, Yicong

2010-01-01

This dissertation introduces a new multimedia security system for the performance of object recognition and multimedia encryption in security and medical applications. The system embeds an enhancement and multimedia encryption process into the traditional recognition system in order to improve the efficiency and accuracy of object detection and…

Evaluation of a bar-code system to detect unaccompanied baggage

DOT National Transportation Integrated Search

1988-02-01

The objective of the Unaccompanied Baggage Detection System (UBDS) Project has : been to gain field experience with a system designed to identify passengers who : check baggage for a flight and subsequently fail to board that flight. In the first : p...

Algorithms for detection of objects in image sequences captured from an airborne imaging system

NASA Technical Reports Server (NTRS)

Kasturi, Rangachar; Camps, Octavia; Tang, Yuan-Liang; Devadiga, Sadashiva; Gandhi, Tarak

1995-01-01

This research was initiated as a part of the effort at the NASA Ames Research Center to design a computer vision based system that can enhance the safety of navigation by aiding the pilots in detecting various obstacles on the runway during critical section of the flight such as a landing maneuver. The primary goal is the development of algorithms for detection of moving objects from a sequence of images obtained from an on-board video camera. Image regions corresponding to the independently moving objects are segmented from the background by applying constraint filtering on the optical flow computed from the initial few frames of the sequence. These detected regions are tracked over subsequent frames using a model based tracking algorithm. Position and velocity of the moving objects in the world coordinate is estimated using an extended Kalman filter. The algorithms are tested using the NASA line image sequence with six static trucks and a simulated moving truck and experimental results are described. Various limitations of the currently implemented version of the above algorithm are identified and possible solutions to build a practical working system are investigated.

Multi-sensor millimeter-wave system for hidden objects detection by non-collaborative screening

NASA Astrophysics Data System (ADS)

Zouaoui, Rhalem; Czarny, Romain; Diaz, Frédéric; Khy, Antoine; Lamarque, Thierry

2011-05-01

In this work, we present the development of a multi-sensor system for the detection of objects concealed under clothes using passive and active millimeter-wave (mmW) technologies. This study concerns both the optimization of a commercial passive mmW imager at 94 GHz using a phase mask and the development of an active mmW detector at 77 GHz based on synthetic aperture radar (SAR). A first wide-field inspection is done by the passive imager while the person is walking. If a suspicious area is detected, the active imager is switched-on and focused on this area in order to obtain more accurate data (shape of the object, nature of the material ...).

Lensfree in-line holographic detection of bacteria

NASA Astrophysics Data System (ADS)

Poher, V.; Allier, C. P.; Coutard, J. G.; Hervé, L.; Dinten, J. M.

2011-07-01

Due to low light scattering, bacteria are difficult to detect using lensless imaging systems. In order to detect individual bacteria, we report a method based on a thin wetting film imaging that produces a micro-lens effect on top of each bacterium when the sample dries up. The imaging using a high-end CMOS sensor is combined with an in-line holographic reconstruction to improve positive detection rate up to 95% with micron-sized beads at high density of ~103 objects/mm2. The system allows detecting from single bacterium to densely packed objects (103 bacteria/μl) within 10μl sample. As an example, E.coli, Bacillus subtilis and Bacillus thuringiensis, has been successfully detected with strong signal to noise ratio across a 24mm2 field of view.

Comparison of non-O157 Shiga toxin-producing E. coli detection systems

USDA-ARS?s Scientific Manuscript database

Category: methodology improvements Objective: To identify strengths and weaknesses of commercial Shiga toxin-producing E. coli detection systems and kits in a side by side fashion. Experimental Design: Three commercial Shiga toxin-producing E. coli detection tests (BAX, GDS, and GeneDisc) and two t...

Cost analysis of the Mercedes-Benz occupant detection system for air bag shut-off

DOT National Transportation Integrated Search

1997-04-01

The objective of this project is to develop the variable manufacturing costs and lead time estimates of an "occupant detection system for air bag shut off". The Mercedes-Benz system was used as a base for developing this data. The system consists of ...

Image-based tracking system for vibration measurement of a rotating object using a laser scanning vibrometer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Dongkyu, E-mail: akein@gist.ac.kr; Khalil, Hossam; Jo, Youngjoon

2016-06-28

An image-based tracking system using laser scanning vibrometer is developed for vibration measurement of a rotating object. The proposed system unlike a conventional one can be used where the position or velocity sensor such as an encoder cannot be attached to an object. An image processing algorithm is introduced to detect a landmark and laser beam based on their colors. Then, through using feedback control system, the laser beam can track a rotating object.

Foreign object detection and removal to improve automated analysis of chest radiographs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hogeweg, Laurens; Sanchez, Clara I.; Melendez, Jaime

2013-07-15

Purpose: Chest radiographs commonly contain projections of foreign objects, such as buttons, brassier clips, jewellery, or pacemakers and wires. The presence of these structures can substantially affect the output of computer analysis of these images. An automated method is presented to detect, segment, and remove foreign objects from chest radiographs.Methods: Detection is performed using supervised pixel classification with a kNN classifier, resulting in a probability estimate per pixel to belong to a projected foreign object. Segmentation is performed by grouping and post-processing pixels with a probability above a certain threshold. Next, the objects are replaced by texture inpainting.Results: The methodmore » is evaluated in experiments on 257 chest radiographs. The detection at pixel level is evaluated with receiver operating characteristic analysis on pixels within the unobscured lung fields and an A{sub z} value of 0.949 is achieved. Free response operator characteristic analysis is performed at the object level, and 95.6% of objects are detected with on average 0.25 false positive detections per image. To investigate the effect of removing the detected objects through inpainting, a texture analysis system for tuberculosis detection is applied to images with and without pathology and with and without foreign object removal. Unprocessed, the texture analysis abnormality score of normal images with foreign objects is comparable to those with pathology. After removing foreign objects, the texture score of normal images with and without foreign objects is similar, while abnormal images, whether they contain foreign objects or not, achieve on average higher scores.Conclusions: The authors conclude that removal of foreign objects from chest radiographs is feasible and beneficial for automated image analysis.« less

Minor Body Surveyor: A Multi-Object, High Speed, Spectro-Photometer Space Mission System Employing Wide-Area Intelligent Change Detection

NASA Astrophysics Data System (ADS)

Kaplan, M. L.; van Cleve, J. E.; Alcock, C.

2003-12-01

Detection and characterization of the small bodies of the outer solar system presents unique challenges to terrestrial based sensing systems, principally the inverse 4th power decrease of reflected and thermal signals with target distance from the Sun. These limits are surpassed by new techniques [1,2,3] employing star-object occultation event sensing, which are capable of detecting sub-kilometer objects in the Kuiper Belt and Oort cloud. This poster will present an instrument and space mission concept based on adaptations of the NASA Discovery Kepler program currently in development at Ball Aerospace and Technologies Corp. Instrument technologies to enable this space science mission are being pursued and will be described. In particular, key attributes of an optimized payload include the ability to provide: 1) Coarse spectral resolution (using an objective spectrometer approach) 2) Wide FOV, simultaneous object monitoring (up to 150,000 stars employing select data regions within a large focal plane mosaic) 3) Fast temporal frame integration and readout architectures (10 to 50 msec for each monitored object) 4) Real-time, intelligent change detection processing (to limit raw data volumes) The Minor Body Surveyor combines the focal plane and processing technology elements into a densely packaged format to support general space mission issues of mass and power consumption, as well as telemetry resources. Mode flexibility is incorporated into the real-time processing elements to allow for either temporal (Occultations) or spatial (Moving targets) change detection. In addition, a basic image capture mode is provided for general pointing and field reference measurements. The overall space mission architecture is described as well. [1] M. E. Bailey. Can 'Invisible' Bodies be Observed in the Solar System. Nature, 259:290-+, January 1976. [2] T. S. Axelrod, C. Alcock, K. H. Cook, and H.-S. Park. A Direct Census of the Oort Cloud with a Robotic Telescope. In ASP Conf. Ser. 34: Robotic Telescopes in the 1990s, pages 171-181, 1992. [3] F. Roques and M. Moncuquet. A Detection Method for Small Kuiper Belt Objects: The Search for Stellar Occultations. Icarus, 147:530-544, October 2000.

A Wireless Sensor Network-Based Portable Vehicle Detector Evaluation System

PubMed Central

Yoo, Seong-eun

2013-01-01

In an upcoming smart transportation environment, performance evaluations of existing Vehicle Detection Systems are crucial to maintain their accuracy. The existing evaluation method for Vehicle Detection Systems is based on a wired Vehicle Detection System reference and a video recorder, which must be operated and analyzed by capable traffic experts. However, this conventional evaluation system has many disadvantages. It is inconvenient to deploy, the evaluation takes a long time, and it lacks scalability and objectivity. To improve the evaluation procedure, this paper proposes a Portable Vehicle Detector Evaluation System based on wireless sensor networks. We describe both the architecture and design of a Vehicle Detector Evaluation System and the implementation results, focusing on the wireless sensor networks and methods for traffic information measurement. With the help of wireless sensor networks and automated analysis, our Vehicle Detector Evaluation System can evaluate a Vehicle Detection System conveniently and objectively. The extensive evaluations of our Vehicle Detector Evaluation System show that it can measure the traffic information such as volume counts and speed with over 98% accuracy. PMID:23344388

A wireless sensor network-based portable vehicle detector evaluation system.

PubMed

Yoo, Seong-eun

2013-01-17

In an upcoming smart transportation environment, performance evaluations of existing Vehicle Detection Systems are crucial to maintain their accuracy. The existing evaluation method for Vehicle Detection Systems is based on a wired Vehicle Detection System reference and a video recorder, which must be operated and analyzed by capable traffic experts. However, this conventional evaluation system has many disadvantages. It is inconvenient to deploy, the evaluation takes a long time, and it lacks scalability and objectivity. To improve the evaluation procedure, this paper proposes a Portable Vehicle Detector Evaluation System based on wireless sensor networks. We describe both the architecture and design of a Vehicle Detector Evaluation System and the implementation results, focusing on the wireless sensor networks and methods for traffic information measurement. With the help of wireless sensor networks and automated analysis, our Vehicle Detector Evaluation System can evaluate a Vehicle Detection System conveniently and objectively. The extensive evaluations of our Vehicle Detector Evaluation System show that it can measure the traffic information such as volume counts and speed with over 98% accuracy.

The model of the optical-electronic control system of vehicles location at level crossing

NASA Astrophysics Data System (ADS)

Verezhinskaia, Ekaterina A.; Gorbachev, Aleksei A.; Maruev, Ivan A.; Shavrygina, Margarita A.

2016-04-01

Level crossing - one of the most dangerous sections of the road network, where railway line crosses motor road at the same level. The collision of trains with vehicles at a level crossing is a serious type of road traffic accidents. The purpose of this research is to develop complex optical electronic control system of vehicles location in the dangerous zone of level crossing. The system consists of registration blocks (including photodetector, lens, infrared emitting diode), determinant devices and camera installed within the boundaries of level crossing. The system performs detection of objects (vehicles) by analysing the time of the object movement opposite to the registration block and level of the reflected signal from the object. The paper presents theoretical description and experimental research of main principles of the system operation. Experimental research of the system model with selected optical-electronic components have confirmed the possibility of metal objects detection at the required distance (0.5 - 2 m) with different values of background illuminance.

Near-Earth Asteroid Tracking (NEAT): First Year Results

NASA Astrophysics Data System (ADS)

Helin, E. F.; Rabinowitz, D. L.; Pravdo, S. H.; Lawrence, K. J.

1997-07-01

The successful detection of Near-Earth Asteroids (NEAs) has been demonstrated by the Near-Earth Asteroid Tracking (NEAT) program at the Jet Propulsion Laboratory during its first year of operation. The NEAT CCD camera system is installed on the U. S. Air Force 1-m GEODSS telescope in Maui. Using state-of-the-art software and hardware, the system initiates nightly transmitted observing script from JPL, moves the telescopes for successive exposures of the selected fields, detects moving objects as faint as V=20.5 in 40 s exposures, determines their astrometric positions, and downloads the data for review at JPL in the morning. The NEAT system is detecting NEAs larger than 200m, comets, and other unique objects at a rate competitive with current operating systems, and bright enough for important physical studies on moderate-sized telescopes. NEAT has detected over 10,000 asteroids over a wide range of magnitudes, demonstrating the excellent capability of the NEAT system. Fifty-five percent of the detections are new objects and over 900 of them have been followed on a second night to receive designation from the Minor Planet Center. 14 NEAs (9 Amors, 4 Apollos, and 1 Aten) have been discovered since March 1996. Also, 2 long period comets and 1996 PW, an asteroidal object with an orbit of a long-period comet, with an eccentricity of 0.992 and orbital period of 5900 years. Program discoveries will be reviewed along with analysis of results pertaining to the discovery efficiency, distribution on the sky, range of orbits and magnitudes. Related abstract: Lawrence, K., et al., 1997 DPS

Statistical and operational considerations for designs for x-ray tomographic spectrophotometry to detect, localize, and classify foreign objects in various systems

NASA Astrophysics Data System (ADS)

Fennelly, Alphonsus J.; Fry, Edward L.; Zukic, Muamer; Wilson, Michele M.; Janik, Tadeusz J.; Torr, Douglas G.

1994-11-01

In six companion papers we discuss a capability for x-ray tomographic spectrophotometry at three energy ranges to observe foreign objects in various systems using a novel x-ray optical and photometric approach. We describe new types of thin-film x-ray reflecting filters to provide energy-specific optical trains, inserted into existing x-ray interrogation systems. That is complemented by performing topographic imaging at a few, to several, energies in each case. That provides a full topographic and spectrophotometric analysis. Foreign objects can then be detected, localized, discriminated, and classified, so that they may be dealt with by excision, and replacement with benign system elements. We analyze statistical and operational concerns leading to the design of three systems: The first operates at x-ray energies of 1 - 10 keV; it deals with defects in microelectronic integrated circuits. The second operates at x-ray energies of 10 - 30 keV; it deals with the defects in human tissue. The chemical specificity and image resolution of the system will allow identification, localization, and mensuration of tumors without the need of biopsy. The system which we concentrate this discussion on, the third, operates at x- ray energies of 30 - 70 keV; it deals with the presence in transportation systems of explosive devices, and contraband materials and objects in luggage and cargo. We present the analysis of the statistical features of the detection problem in these types of systems, discussing the operational constraints which limits system performance. After considering the multivariate, multisignature, approach to the problem, we discuss the tomographic and spectrophotometric approach to the problem which yields a better solution to the detection problem within the operational constraints.

Operator-coached machine vision for space telerobotics

NASA Technical Reports Server (NTRS)

Bon, Bruce; Wilcox, Brian; Litwin, Todd; Gennery, Donald B.

1991-01-01

A prototype system for interactive object modeling has been developed and tested. The goal of this effort has been to create a system which would demonstrate the feasibility of high interactive operator-coached machine vision in a realistic task environment, and to provide a testbed for experimentation with various modes of operator interaction. The purpose for such a system is to use human perception where machine vision is difficult, i.e., to segment the scene into objects and to designate their features, and to use machine vision to overcome limitations of human perception, i.e., for accurate measurement of object geometry. The system captures and displays video images from a number of cameras, allows the operator to designate a polyhedral object one edge at a time by moving a 3-D cursor within these images, performs a least-squares fit of the designated edges to edge data detected with a modified Sobel operator, and combines the edges thus detected to form a wire-frame object model that matches the Sobel data.

Volumetric Security Alarm Based on a Spherical Ultrasonic Transducer Array

NASA Astrophysics Data System (ADS)

Sayin, Umut; Scaini, Davide; Arteaga, Daniel

Most of the existent alarm systems depend on physical or visual contact. The detection area is often limited depending on the type of the transducer, creating blind spots. Our proposition is a truly volumetric alarm system that can detect any movement in the intrusion area, based on monitoring the change over time of the impulse response of the room, which acts as an acoustic footprint. The device depends on an omnidirectional ultrasonic transducer array emitting sweep signals to calculate the impulse response in short intervals. Any change in the room conditions is monitored through a correlation function. The sensitivity of the alarm to different objects and different environments depends on the sweep duration, sweep bandwidth, and sweep interval. Successful detection of intrusions also depends on the size of the monitoring area and requires an adjustment of emitted ultrasound power. Strong air flow affects the performance of the alarm. A method for separating moving objects from strong air flow is devised using an adaptive thresholding on the correlation function involving a series of impulse response measurements. The alarm system can be also used for fire detection since air flow sourced from heating objects differ from random nature of the present air flow. Several measurements are made to test the integrity of the alarm in rooms sizing from 834-2080m3 with irregular geometries and various objects. The proposed system can efficiently detect intrusion whilst adequate emitting power is provided.

Comet/Asteroid Protection System (CAPS): A Space-Based System Concept for Revolutionizing Earth Protection and Utilization of Near-Earth Objects

NASA Technical Reports Server (NTRS)

Mazanek, Daniel D.; Roithmayr, Carlos M.; Antol, Jeffrey; Kay-Bunnell, Linda; Werner, Martin R.; Park, Sang-Young; Kumar, Renjith R.

2002-01-01

There exists an infrequent, but significant hazard to life and property due to impacting asteroids and comets. There is currently no specific search for long-period comets, smaller near-Earth asteroids, or smaller short-period comets. These objects represent a threat with potentially little or no warning time using conventional ground-based telescopes. These planetary bodies also represent a significant resource for commercial exploitation, long-term sustained space exploration, and scientific research. The Comet/Asteroid Protection System (CAPS) would expand the current detection effort to include long-period comets, as well as small asteroids and short-period comets capable of regional destruction. A space-based detection system, despite being more costly and complex than Earth-based initiatives, is the most promising way of expanding the range of detectable objects, and surveying the entire celestial sky on a regular basis. CAPS is a future spacebased system concept that provides permanent, continuous asteroid and comet monitoring, and rapid, controlled modification of the orbital trajectories of selected bodies. CAPS would provide an orbit modification system capable of diverting kilometer class objects, and modifying the orbits of smaller asteroids for impact defense and resource utilization. This paper provides a summary of CAPS and discusses several key areas and technologies that are being investigated.

Using advanced computer vision algorithms on small mobile robots

NASA Astrophysics Data System (ADS)

Kogut, G.; Birchmore, F.; Biagtan Pacis, E.; Everett, H. R.

2006-05-01

The Technology Transfer project employs a spiral development process to enhance the functionality and autonomy of mobile robot systems in the Joint Robotics Program (JRP) Robotic Systems Pool by converging existing component technologies onto a transition platform for optimization. An example of this approach is the implementation of advanced computer vision algorithms on small mobile robots. We demonstrate the implementation and testing of the following two algorithms useful on mobile robots: 1) object classification using a boosted Cascade of classifiers trained with the Adaboost training algorithm, and 2) human presence detection from a moving platform. Object classification is performed with an Adaboost training system developed at the University of California, San Diego (UCSD) Computer Vision Lab. This classification algorithm has been used to successfully detect the license plates of automobiles in motion in real-time. While working towards a solution to increase the robustness of this system to perform generic object recognition, this paper demonstrates an extension to this application by detecting soda cans in a cluttered indoor environment. The human presence detection from a moving platform system uses a data fusion algorithm which combines results from a scanning laser and a thermal imager. The system is able to detect the presence of humans while both the humans and the robot are moving simultaneously. In both systems, the two aforementioned algorithms were implemented on embedded hardware and optimized for use in real-time. Test results are shown for a variety of environments.

Reducing Runway Incursions: Can You Relate?

DOT National Transportation Integrated Search

1992-01-01

Side object detection systems (SODS) are collision warning systems which alert drivers to the presence of traffic alongside their vehicle within defined detection zones. The intent of SODS is to reduce collisions during lane changes and merging maneu...

A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization

PubMed Central

Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

2017-01-01

The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device’s built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction. PMID:28837096

A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization.

PubMed

Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

2017-08-24

The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device's built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction.

A Vision-Based System for Object Identification and Information Retrieval in a Smart Home

NASA Astrophysics Data System (ADS)

Grech, Raphael; Monekosso, Dorothy; de Jager, Deon; Remagnino, Paolo

This paper describes a hand held device developed to assist people to locate and retrieve information about objects in a home. The system developed is a standalone device to assist persons with memory impairments such as people suffering from Alzheimer's disease. A second application is object detection and localization for a mobile robot operating in an ambient assisted living environment. The device relies on computer vision techniques to locate a tagged object situated in the environment. The tag is a 2D color printed pattern with a detection range and a field of view such that the user may point from a distance of over 1 meter.

Radar system components to detect small and fast objects

NASA Astrophysics Data System (ADS)

Hülsmann, Axel; Zech, Christian; Klenner, Mathias; Tessmann, Axel; Leuther, Arnulf; Lopez-Diaz, Daniel; Schlechtweg, Michael; Ambacher, Oliver

2015-05-01

Small and fast objects, for example bullets of caliber 5 to 10 mm, fired from guns like AK-47, can cause serious problems to aircrafts in asymmetric warfare. Especially slow and big aircrafts, like heavy transport helicopters are an easy mark of small caliber hand fire weapons. These aircrafts produce so much noise, that the crew is not able to recognize an attack unless serious problems occur and important systems of the aircraft fail. This is just one of many scenarios, where the detection of fast and small objects is desirable. Another scenario is the collision of space debris particles with satellites.

MUSIC algorithm DoA estimation for cooperative node location in mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Warty, Chirag; Yu, Richard Wai; ElMahgoub, Khaled; Spinsante, Susanna

In recent years the technological development has encouraged several applications based on distributed communications network without any fixed infrastructure. The problem of providing a collaborative early warning system for multiple mobile nodes against a fast moving object. The solution is provided subject to system level constraints: motion of nodes, antenna sensitivity and Doppler effect at 2.4 GHz and 5.8 GHz. This approach consists of three stages. The first phase consists of detecting the incoming object using a highly directive two element antenna at 5.0 GHz band. The second phase consists of broadcasting the warning message using a low directivity broad antenna beam using 2× 2 antenna array which then in third phase will be detected by receiving nodes by using direction of arrival (DOA) estimation technique. The DOA estimation technique is used to estimate the range and bearing of the incoming nodes. The position of fast arriving object can be estimated using the MUSIC algorithm for warning beam DOA estimation. This paper is mainly intended to demonstrate the feasibility of early detection and warning system using a collaborative node to node communication links. The simulation is performed to show the behavior of detecting and broadcasting antennas as well as performance of the detection algorithm. The idea can be further expanded to implement commercial grade detection and warning system

Detection, Identification, Location, and Remote Sensing using SAW RFID Sensor Tags

NASA Technical Reports Server (NTRS)

Barton, Richard J.

2009-01-01

In this presentation, we will consider the problem of simultaneous detection, identification, location estimation, and remote sensing for multiple objects. In particular, we will describe the design and testing of a wireless system capable of simultaneously detecting the presence of multiple objects, identifying each object, and acquiring both a low-resolution estimate of location and a high-resolution estimate of temperature for each object based on wireless interrogation of passive surface acoustic wave (SAW) radiofrequency identification (RFID) sensor tags affixed to each object. The system is being studied for application on the lunar surface as well as for terrestrial remote sensing applications such as pre-launch monitoring and testing of spacecraft on the launch pad and monitoring of test facilities. The system utilizes a digitally beam-formed planar receiving antenna array to extend range and provide direction-of-arrival information coupled with an approximate maximum-likelihood signal processing algorithm to provide near-optimal estimation of both range and temperature. The system is capable of forming a large number of beams within the field of view and resolving the information from several tags within each beam. The combination of both spatial and waveform discrimination provides the capability to track and monitor telemetry from a large number of objects appearing simultaneously within the field of view of the receiving array. In the presentation, we will summarize the system design and illustrate several aspects of the operational characteristics and signal structure. We will examine the theoretical performance characteristics of the system and compare the theoretical results with results obtained from experiments in both controlled laboratory environments and in the field.

Salient man-made structure detection in infrared images

NASA Astrophysics Data System (ADS)

Li, Dong-jie; Zhou, Fu-gen; Jin, Ting

2013-09-01

Target detection, segmentation and recognition is a hot research topic in the field of image processing and pattern recognition nowadays, among which salient area or object detection is one of core technologies of precision guided weapon. Many theories have been raised in this paper; we detect salient objects in a series of input infrared images by using the classical feature integration theory and Itti's visual attention system. In order to find the salient object in an image accurately, we present a new method to solve the edge blur problem by calculating and using the edge mask. We also greatly improve the computing speed by improving the center-surround differences method. Unlike the traditional algorithm, we calculate the center-surround differences through rows and columns separately. Experimental results show that our method is effective in detecting salient object accurately and rapidly.

Polarized object detection in crabs: a two-channel system.

PubMed

Basnak, Melanie Ailín; Pérez-Schuster, Verónica; Hermitte, Gabriela; Berón de Astrada, Martín

2018-05-25

Many animal species take advantage of polarization vision for vital tasks such as orientation, communication and contrast enhancement. Previous studies have suggested that decapod crustaceans use a two-channel polarization system for contrast enhancement. Here, we characterize the polarization contrast sensitivity in a grapsid crab . We estimated the polarization contrast sensitivity of the animals by quantifying both their escape response and changes in heart rate when presented with polarized motion stimuli. The motion stimulus consisted of an expanding disk with an 82 deg polarization difference between the object and the background. More than 90% of animals responded by freezing or trying to avoid the polarized stimulus. In addition, we co-rotated the electric vector (e-vector) orientation of the light from the object and background by increments of 30 deg and found that the animals' escape response varied periodically with a 90 deg period. Maximum escape responses were obtained for object and background e-vectors near the vertical and horizontal orientations. Changes in cardiac response showed parallel results but also a minimum response when e-vectors of object and background were shifted by 45 deg with respect to the maxima. These results are consistent with an orthogonal receptor arrangement for the detection of polarized light, in which two channels are aligned with the vertical and horizontal orientations. It has been hypothesized that animals with object-based polarization vision rely on a two-channel detection system analogous to that of color processing in dichromats. Our results, obtained by systematically varying the e-vectors of object and background, provide strong empirical support for this theoretical model of polarized object detection. © 2018. Published by The Company of Biologists Ltd.

A multisensor system for detection and characterization of UXO(MM-0437) - Demonstration Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gasperikova, Erika; Smith, J.T.; Morrison, H.F.

2006-06-01

The Berkeley UXO discriminator (BUD) (Figure 1) is a portable Active Electromagnetic (AEM) system for UXO detection and characterization that quickly determines the location, size, and symmetry properties of a suspected UXO. The BUD comprises of three orthogonal transmitters that 'illuminate' a target with fields in three independent directions in order to stimulate the three polarization modes that, in general, characterize the target EM response. In addition, the BUD uses eight pairs of differenced receivers for response recording. Eight receiver coils are placed horizontally along the two diagonals of the upper and lower planes of the two horizontal transmitter loops.more » These receiver coil pairs are located on symmetry lines through the center of the system and each pair sees identical fields during the on-time of the pulse in all of the transmitter coils. They are wired in opposition to produce zero output during the on-time of the pulses in three orthogonal transmitters. Moreover, this configuration dramatically reduces noise in the measurements by canceling the background electromagnetic fields (these fields are uniform over the scale of the receiver array and are consequently nulled by the differencing operation), and by canceling the noise contributed by the tilt of the receivers in the Earth's magnetic field, and greatly enhances receivers sensitivity to the gradients of the target response. The BUD performs target characterization from a single position of the sensor platform above a target. BUD was designed to detect and characterize UXO in the 20 mm to 155 mm size range for depths between 0 and 1 m. The relationship between the object size and the depth at which it can be detected is illustrated in Figure 2. This curve was calculated for BUD assuming that the receiver plane is 20 cm above the ground. Figure 2 shows that, for example, BUD can detect and characterize an object with 10 cm diameter down to the depth of 90 cm with depth uncertainty of 10%. Any objects buried at the depth more than 1 m have a low probability of detection. With existing algorithms in the system computer it is not possible to recover the principal polarizabilities of large objects close to the system. Detection of large shallow objects is assured, but at present real time discrimination for shallow objects is not. Post processing of the field data is required for shape discrimination of large shallow targets. Next generation of BUD software will not have this limitation. Successful application of the inversion algorithm that solves for the target parameters is contingent upon resolution of this limitation. At the moment, interpretation software is developed for a single object only. In case of multiple objects the software indicates the presence of a cluster of objects but is unable to provide characteristics of each individual object.« less

Detection of a concealed object

DOEpatents

Keller, Paul E [Richland, WA; Hall, Thomas E [Kennewick, WA; McMakin, Douglas L [Richland, WA

2010-11-16

Disclosed are systems, methods, devices, and apparatus to determine if a clothed individual is carrying a suspicious, concealed object. This determination includes establishing data corresponding to an image of the individual through interrogation with electromagnetic radiation in the 200 MHz to 1 THz range. In one form, image data corresponding to intensity of reflected radiation and differential depth of the reflecting surface is received and processed to detect the suspicious, concealed object.

Detection of a concealed object

DOEpatents

Keller, Paul E [Richland, WA; Hall, Thomas E [Kennewick, WA; McMakin, Douglas L [Richland, WA

2008-04-29

Disclosed are systems, methods, devices, and apparatus to determine if a clothed individual is carrying a suspicious, concealed object. This determination includes establishing data corresponding to an image of the individual through interrogation with electromagnetic radiation in the 200 MHz to 1 THz range. In one form, image data corresponding to intensity of reflected radiation and differential depth of the reflecting surface is received and processed to detect the suspicious, concealed object.

Saliency-Guided Detection of Unknown Objects in RGB-D Indoor Scenes.

PubMed

Bao, Jiatong; Jia, Yunyi; Cheng, Yu; Xi, Ning

2015-08-27

This paper studies the problem of detecting unknown objects within indoor environments in an active and natural manner. The visual saliency scheme utilizing both color and depth cues is proposed to arouse the interests of the machine system for detecting unknown objects at salient positions in a 3D scene. The 3D points at the salient positions are selected as seed points for generating object hypotheses using the 3D shape. We perform multi-class labeling on a Markov random field (MRF) over the voxels of the 3D scene, combining cues from object hypotheses and 3D shape. The results from MRF are further refined by merging the labeled objects, which are spatially connected and have high correlation between color histograms. Quantitative and qualitative evaluations on two benchmark RGB-D datasets illustrate the advantages of the proposed method. The experiments of object detection and manipulation performed on a mobile manipulator validate its effectiveness and practicability in robotic applications.

Saliency-Guided Detection of Unknown Objects in RGB-D Indoor Scenes

PubMed Central

Bao, Jiatong; Jia, Yunyi; Cheng, Yu; Xi, Ning

2015-01-01

This paper studies the problem of detecting unknown objects within indoor environments in an active and natural manner. The visual saliency scheme utilizing both color and depth cues is proposed to arouse the interests of the machine system for detecting unknown objects at salient positions in a 3D scene. The 3D points at the salient positions are selected as seed points for generating object hypotheses using the 3D shape. We perform multi-class labeling on a Markov random field (MRF) over the voxels of the 3D scene, combining cues from object hypotheses and 3D shape. The results from MRF are further refined by merging the labeled objects, which are spatially connected and have high correlation between color histograms. Quantitative and qualitative evaluations on two benchmark RGB-D datasets illustrate the advantages of the proposed method. The experiments of object detection and manipulation performed on a mobile manipulator validate its effectiveness and practicability in robotic applications. PMID:26343656

Ground Testing of Prototype Hardware and Processing Algorithms for a Wide Area Space Surveillance System (WASSS)

NASA Astrophysics Data System (ADS)

Goldstein, N.; Dressler, R. A.; Richtsmeier, S. S.; McLean, J.; Dao, P. D.; Murray-Krezan, J.; Fulcoly, D. O.

2013-09-01

Recent ground testing of a wide area camera system and automated star removal algorithms has demonstrated the potential to detect, quantify, and track deep space objects using small aperture cameras and on-board processors. The camera system, which was originally developed for a space-based Wide Area Space Surveillance System (WASSS), operates in a fixed-stare mode, continuously monitoring a wide swath of space and differentiating celestial objects from satellites based on differential motion across the field of view. It would have greatest utility in a LEO orbit to provide automated and continuous monitoring of deep space with high refresh rates, and with particular emphasis on the GEO belt and GEO transfer space. Continuous monitoring allows a concept of change detection and custody maintenance not possible with existing sensors. The detection approach is equally applicable to Earth-based sensor systems. A distributed system of such sensors, either Earth-based, or space-based, could provide automated, persistent night-time monitoring of all of deep space. The continuous monitoring provides a daily record of the light curves of all GEO objects above a certain brightness within the field of view. The daily updates of satellite light curves offers a means to identify specific satellites, to note changes in orientation and operational mode, and to queue other SSA assets for higher resolution queries. The data processing approach may also be applied to larger-aperture, higher resolution camera systems to extend the sensitivity towards dimmer objects. In order to demonstrate the utility of the WASSS system and data processing, a ground based field test was conducted in October 2012. We report here the results of the observations made at Magdalena Ridge Observatory using the prototype WASSS camera, which has a 4×60° field-of-view , <0.05° resolution, a 2.8 cm2 aperture, and the ability to view within 4° of the sun. A single camera pointed at the GEO belt provided a continuous night-long record of the intensity and location of more than 50 GEO objects detected within the camera's 60-degree field-of-view, with a detection sensitivity similar to the camera's shot noise limit of Mv=13.7. Performance is anticipated to scale with aperture area, allowing the detection of dimmer objects with larger-aperture cameras. The sensitivity of the system depends on multi-frame averaging and an image processing algorithm that exploits the different angular velocities of celestial objects and SOs. Principal Components Analysis (PCA) is used to filter out all objects moving with the velocity of the celestial frame of reference. The resulting filtered images are projected back into an Earth-centered frame of reference, or into any other relevant frame of reference, and co-added to form a series of images of the GEO objects as a function of time. The PCA approach not only removes the celestial background, but it also removes systematic variations in system calibration, sensor pointing, and atmospheric conditions. The resulting images are shot-noise limited, and can be exploited to automatically identify deep space objects, produce approximate state vectors, and track their locations and intensities as a function of time.

Products recognition on shop-racks from local scale-invariant features

NASA Astrophysics Data System (ADS)

Zawistowski, Jacek; Kurzejamski, Grzegorz; Garbat, Piotr; Naruniec, Jacek

2016-04-01

This paper presents a system designed for the multi-object detection purposes and adjusted for the application of product search on the market shelves. System uses well known binary keypoint detection algorithms for finding characteristic points in the image. One of the main idea is object recognition based on Implicit Shape Model method. Authors of the article proposed many improvements of the algorithm. Originally fiducial points are matched with a very simple function. This leads to the limitations in the number of objects parts being success- fully separated, while various methods of classification may be validated in order to achieve higher performance. Such an extension implies research on training procedure able to deal with many objects categories. Proposed solution opens a new possibilities for many algorithms demanding fast and robust multi-object recognition.

Dynamic deformation inspection of a human arm by using a line-scan imaging system

NASA Astrophysics Data System (ADS)

Hu, Eryi

2009-11-01

A line-scan imaging system is used in the dynamic deformation measurement of a human arm when the muscle is contracting and relaxing. The measurement principle is based on the projection grating profilometry, and the measuring system is consisted of a line-scan CCD camera, a projector, optical lens and a personal computer. The detected human arm is put upon a reference plane, and a sinusoidal grating is projected onto the object surface and reference plane at an incidence angle, respectively. The deformed fringe pattern in the same line of the dynamic detected arm is captured by the line-scan CCD camera with free trigger model, and the deformed fringe pattern is recorded in the personal computer for processing. A fast Fourier transform combining with a filtering and spectrum shifting method is used to extract the phase information caused by the profile of the detected object. Thus, the object surface profile can be obtained following the geometric relationship between the fringe deformation and the object surface height. Furthermore, the deformation procedure can be obtained line by line. Some experimental results are presented to prove the feasibility of the inspection system.

Person detection and tracking with a 360° lidar system

NASA Astrophysics Data System (ADS)

Hammer, Marcus; Hebel, Marcus; Arens, Michael

2017-10-01

Today it is easily possible to generate dense point clouds of the sensor environment using 360° LiDAR (Light Detection and Ranging) sensors which are available since a number of years. The interpretation of these data is much more challenging. For the automated data evaluation the detection and classification of objects is a fundamental task. Especially in urban scenarios moving objects like persons or vehicles are of particular interest, for instance in automatic collision avoidance, for mobile sensor platforms or surveillance tasks. In literature there are several approaches for automated person detection in point clouds. While most techniques show acceptable results in object detection, the computation time is often crucial. The runtime can be problematic, especially due to the amount of data in the panoramic 360° point clouds. On the other hand, for most applications an object detection and classification in real time is needed. The paper presents a proposal for a fast, real-time capable algorithm for person detection, classification and tracking in panoramic point clouds.

An objectively-analyzed method for measuring the useful penetration of x-ray imaging systems.

PubMed

Glover, Jack L; Hudson, Lawrence T

2016-06-01

The ability to detect wires is an important capability of the cabinet x-ray imaging systems that are used in aviation security as well as the portable x-ray systems that are used by domestic law enforcement and military bomb squads. A number of national and international standards describe methods for testing this capability using the so called useful penetration test metric, where wires are imaged behind different thicknesses of blocking material. Presently, these tests are scored based on human judgments of wire visibility, which are inherently subjective. We propose a new method in which the useful penetration capabilities of an x-ray system are objectively evaluated by an image processing algorithm operating on digital images of a standard test object. The algorithm advantageously applies the Radon transform for curve parameter detection that reduces the problem of wire detection from two dimensions to one. The sensitivity of the wire detection method is adjustable and we demonstrate how the threshold parameter can be set to give agreement with human-judged results. The method was developed to be used in technical performance standards and is currently under ballot for inclusion in a US national aviation security standard.

An objectively-analyzed method for measuring the useful penetration of x-ray imaging systems

PubMed Central

Glover, Jack L.; Hudson, Lawrence T.

2016-01-01

The ability to detect wires is an important capability of the cabinet x-ray imaging systems that are used in aviation security as well as the portable x-ray systems that are used by domestic law enforcement and military bomb squads. A number of national and international standards describe methods for testing this capability using the so called useful penetration test metric, where wires are imaged behind different thicknesses of blocking material. Presently, these tests are scored based on human judgments of wire visibility, which are inherently subjective. We propose a new method in which the useful penetration capabilities of an x-ray system are objectively evaluated by an image processing algorithm operating on digital images of a standard test object. The algorithm advantageously applies the Radon transform for curve parameter detection that reduces the problem of wire detection from two dimensions to one. The sensitivity of the wire detection method is adjustable and we demonstrate how the threshold parameter can be set to give agreement with human-judged results. The method was developed to be used in technical performance standards and is currently under ballot for inclusion in a US national aviation security standard. PMID:27499586

An objectively-analyzed method for measuring the useful penetration of x-ray imaging systems

NASA Astrophysics Data System (ADS)

Glover, Jack L.; Hudson, Lawrence T.

2016-06-01

The ability to detect wires is an important capability of the cabinet x-ray imaging systems that are used in aviation security as well as the portable x-ray systems that are used by domestic law enforcement and military bomb squads. A number of national and international standards describe methods for testing this capability using the so called useful penetration test metric, where wires are imaged behind different thicknesses of blocking material. Presently, these tests are scored based on human judgments of wire visibility, which are inherently subjective. We propose a new method in which the useful penetration capabilities of an x-ray system are objectively evaluated by an image processing algorithm operating on digital images of a standard test object. The algorithm advantageously applies the Radon transform for curve parameter detection that reduces the problem of wire detection from two dimensions to one. The sensitivity of the wire detection method is adjustable and we demonstrate how the threshold parameter can be set to give agreement with human-judged results. The method was developed to be used in technical performance standards and is currently under ballot for inclusion in an international aviation security standard.

Flow detection via sparse frame analysis for suspicious event recognition in infrared imagery

NASA Astrophysics Data System (ADS)

Fernandes, Henrique C.; Batista, Marcos A.; Barcelos, Celia A. Z.; Maldague, Xavier P. V.

2013-05-01

It is becoming increasingly evident that intelligent systems are very bene¯cial for society and that the further development of such systems is necessary to continue to improve society's quality of life. One area that has drawn the attention of recent research is the development of automatic surveillance systems. In our work we outline a system capable of monitoring an uncontrolled area (an outside parking lot) using infrared imagery and recognizing suspicious events in this area. The ¯rst step is to identify moving objects and segment them from the scene's background. Our approach is based on a dynamic background-subtraction technique which robustly adapts detection to illumination changes. It is analyzed only regions where movement is occurring, ignoring in°uence of pixels from regions where there is no movement, to segment moving objects. Regions where movement is occurring are identi¯ed using °ow detection via sparse frame analysis. During the tracking process the objects are classi¯ed into two categories: Persons and Vehicles, based on features such as size and velocity. The last step is to recognize suspicious events that may occur in the scene. Since the objects are correctly segmented and classi¯ed it is possible to identify those events using features such as velocity and time spent motionless in one spot. In this paper we recognize the suspicious event suspicion of object(s) theft from inside a parked vehicle at spot X by a person" and results show that the use of °ow detection increases the recognition of this suspicious event from 78:57% to 92:85%.

Optical Observation, Image-processing, and Detection of Space Debris in Geosynchronous Earth Orbit

NASA Astrophysics Data System (ADS)

Oda, H.; Yanagisawa, T.; Kurosaki, H.; Tagawa, M.

2014-09-01

We report on optical observations and an efficient detection method of space debris in the geosynchronous Earth orbit (GEO). We operate our new Australia Remote Observatory (ARO) where an 18 cm optical telescope with a charged-coupled device (CCD) camera covering a 3.14-degree field of view is used for GEO debris survey, and analyse datasets of successive CCD images using the line detection method (Yanagisawa and Nakajima 2005). In our operation, the exposure time of each CCD image is set to be 3 seconds (or 5 seconds), and the time interval of CCD shutter open is about 4.7 seconds (or 6.7 seconds). In the line detection method, a sufficient number of sample objects are taken from each image based on their shape and intensity, which includes not only faint signals but also background noise (we take 500 sample objects from each image in this paper). Then we search a sequence of sample objects aligning in a straight line in the successive images to exclude the noise sample. We succeed in detecting faint signals (down to about 1.8 sigma of background noise) by applying the line detection method to 18 CCD images. As a result, we detected about 300 GEO objects up to magnitude of 15.5 among 5 nights data. We also calculate orbits of objects detected using the Simplified General Perturbations Satellite Orbit Model 4(SGP4), and identify the objects listed in the two-line-element (TLE) data catalogue publicly provided by the U.S. Strategic Command (USSTRATCOM). We found that a certain amount of our detections are new objects that are not contained in the catalogue. We conclude that our ARO and detection method posse a high efficiency detection of GEO objects despite the use of comparatively-inexpensive observation and analysis system. We also describe the image-processing specialized for the detection of GEO objects (not for usual astronomical objects like stars) in this paper.

TeraSCREEN: multi-frequency multi-mode Terahertz screening for border checks

NASA Astrophysics Data System (ADS)

Alexander, Naomi E.; Alderman, Byron; Allona, Fernando; Frijlink, Peter; Gonzalo, Ramón; Hägelen, Manfred; Ibáñez, Asier; Krozer, Viktor; Langford, Marian L.; Limiti, Ernesto; Platt, Duncan; Schikora, Marek; Wang, Hui; Weber, Marc Andree

2014-06-01

The challenge for any security screening system is to identify potentially harmful objects such as weapons and explosives concealed under clothing. Classical border and security checkpoints are no longer capable of fulfilling the demands of today's ever growing security requirements, especially with respect to the high throughput generally required which entails a high detection rate of threat material and a low false alarm rate. TeraSCREEN proposes to develop an innovative concept of multi-frequency multi-mode Terahertz and millimeter-wave detection with new automatic detection and classification functionalities. The system developed will demonstrate, at a live control point, the safe automatic detection and classification of objects concealed under clothing, whilst respecting privacy and increasing current throughput rates. This innovative screening system will combine multi-frequency, multi-mode images taken by passive and active subsystems which will scan the subjects and obtain complementary spatial and spectral information, thus allowing for automatic threat recognition. The TeraSCREEN project, which will run from 2013 to 2016, has received funding from the European Union's Seventh Framework Programme under the Security Call. This paper will describe the project objectives and approach.

The practical application of signal detection theory to image quality assessment in x-ray image intensifier-TV fluoroscopy.

PubMed

Marshall, N W

2001-06-01

This paper applies a published version of signal detection theory to x-ray image intensifier fluoroscopy data and compares the results with more conventional subjective image quality measures. An eight-bit digital framestore was used to acquire temporally contiguous frames of fluoroscopy data from which the modulation transfer function (MTF(u)) and noise power spectrum were established. These parameters were then combined to give detective quantum efficiency (DQE(u)) and used in conjunction with signal detection theory to calculate contrast-detail performance. DQE(u) was found to lie between 0.1 and 0.5 for a range of fluoroscopy systems. Two separate image quality experiments were then performed in order to assess the correspondence between the objective and subjective methods. First, image quality for a given fluoroscopy system was studied as a function of doserate using objective parameters and a standard subjective contrast-detail method. Following this, the two approaches were used to assess three different fluoroscopy units. Agreement between objective and subjective methods was good; doserate changes were modelled correctly while both methods ranked the three systems consistently.

Underwater electric field detection system based on weakly electric fish

NASA Astrophysics Data System (ADS)

Xue, Wei; Wang, Tianyu; Wang, Qi

2018-04-01

Weakly electric fish sense their surroundings in complete darkness by their active electric field detection system. However, due to the insufficient detection capacity of the electric field, the detection distance is not enough, and the detection accuracy is not high. In this paper, a method of underwater detection based on rotating current field theory is proposed to improve the performance of underwater electric field detection system. First of all, we built underwater detection system based on the theory of the spin current field mathematical model with the help of the results of previous researchers. Then we completed the principle prototype and finished the metal objects in the water environment detection experiments, laid the foundation for the further experiments.

Domain Anomaly Detection in Machine Perception: A System Architecture and Taxonomy.

PubMed

Kittler, Josef; Christmas, William; de Campos, Teófilo; Windridge, David; Yan, Fei; Illingworth, John; Osman, Magda

2014-05-01

We address the problem of anomaly detection in machine perception. The concept of domain anomaly is introduced as distinct from the conventional notion of anomaly used in the literature. We propose a unified framework for anomaly detection which exposes the multifaceted nature of anomalies and suggest effective mechanisms for identifying and distinguishing each facet as instruments for domain anomaly detection. The framework draws on the Bayesian probabilistic reasoning apparatus which clearly defines concepts such as outlier, noise, distribution drift, novelty detection (object, object primitive), rare events, and unexpected events. Based on these concepts we provide a taxonomy of domain anomaly events. One of the mechanisms helping to pinpoint the nature of anomaly is based on detecting incongruence between contextual and noncontextual sensor(y) data interpretation. The proposed methodology has wide applicability. It underpins in a unified way the anomaly detection applications found in the literature. To illustrate some of its distinguishing features, in here the domain anomaly detection methodology is applied to the problem of anomaly detection for a video annotation system.

Active marks structure optimization for optical-electronic systems of spatial position control of industrial objects

NASA Astrophysics Data System (ADS)

Sycheva, Elena A.; Vasilev, Aleksandr S.; Lashmanov, Oleg U.; Korotaev, Valery V.

2017-06-01

The article is devoted to the optimization of optoelectronic systems of the spatial position of objects. Probabilistic characteristics of the detection of an active structured mark on a random noisy background are investigated. The developed computer model and the results of the study allow us to estimate the probabilistic characteristics of detection of a complex structured mark on a random gradient background, and estimate the error of spatial coordinates. The results of the study make it possible to improve the accuracy of measuring the coordinates of the object. Based on the research recommendations are given on the choice of parameters of the optimal mark structure for use in opticalelectronic systems for monitoring the spatial position of large-sized structures.

A Discovery of a Candidate Companion to a Transiting System KOI-94: A Direct Imaging Study for a Possibility of a False Positive

NASA Technical Reports Server (NTRS)

Takahashi, Yasuhiro; Narita, Norio; Hirano, Teruyuki; Kuzuhara, Masayuki; Tamura, Motohide; Kudo, Tomoyuki; Kusakabe, Nobuhiko; Hashimoto, Jun; Sato, Bun'ei; Abe, Lyu;

Border-oriented post-processing refinement on detected vehicle bounding box for ADAS

NASA Astrophysics Data System (ADS)

Chen, Xinyuan; Zhang, Zhaoning; Li, Minne; Li, Dongsheng

2018-04-01

We investigate a new approach for improving localization accuracy of detected vehicles for object detection in advanced driver assistance systems(ADAS). Specifically, we implement a bounding box refinement as a post-processing of the state-of-the-art object detectors (Faster R-CNN, YOLOv2, etc.). The bounding box refinement is achieved by individually adjusting each border of the detected bounding box to its target location using a regression method. We use HOG features which perform well on the edge detection of vehicles to train the regressor and the regressor is independent of the CNN-based object detectors. Experiment results on the KITTI 2012 benchmark show that we can achieve up to 6% improvements over YOLOv2 and Faster R-CNN object detectors on the IoU threshold of 0.8. Also, the proposed refinement framework is computationally light, allowing for processing one bounding box within a few milliseconds on CPU. Further, this refinement method can be added to any object detectors, especially those with high speed but less accuracy.

A system for learning statistical motion patterns.

PubMed

Hu, Weiming; Xiao, Xuejuan; Fu, Zhouyu; Xie, Dan; Tan, Tieniu; Maybank, Steve

2006-09-01

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction.

Asteroids in the High Cadence Transient Survey

NASA Astrophysics Data System (ADS)

Peña, J.; Fuentes, C.; Förster, F.; Maureira, J. C.; San Martín, J.; Littín, J.; Huijse, P.; Cabrera-Vives, G.; Estévez, P. A.; Galbany, L.; González-Gaitán, S.; Martínez, J.; de Jaeger, Th.; Hamuy, M.

2018-03-01

We report on the serendipitous observations of solar system objects imaged during the High cadence Transient Survey 2014 observation campaign. Data from this high-cadence wide-field survey was originally analyzed for finding variable static sources using machine learning to select the most-likely candidates. In this work, we search for moving transients consistent with solar system objects and derive their orbital parameters. We use a simple, custom motion detection algorithm to link trajectories and assume Keplerian motion to derive the asteroid’s orbital parameters. We use known asteroids from the Minor Planet Center database to assess the detection efficiency of the survey and our search algorithm. Trajectories have an average of nine detections spread over two days, and our fit yields typical errors of {σ }a∼ 0.07 {au}, σ e ∼ 0.07 and σ i ∼ 0.°5 in semimajor axis, eccentricity, and inclination, respectively, for known asteroids in our sample. We extract 7700 orbits from our trajectories, identifying 19 near-Earth objects, 6687 asteroids, 14 Centaurs, and 15 trans-Neptunian objects. This highlights the complementarity of supernova wide-field surveys for solar system research and the significance of machine learning to clean data of false detections. It is a good example of the data-driven science that Large Synoptic Survey Telescope will deliver.

Resonant frequency method for bearing ball inspection

DOEpatents

Khuri-Yakub, B. T.; Hsieh, Chung-Kao

1993-01-01

The present invention provides for an inspection system and method for detecting defects in test objects which includes means for generating expansion inducing energy focused upon the test object at a first location, such expansion being allowed to contract, thereby causing pressure wave within and on the surface of the test object. Such expansion inducing energy may be provided by, for example, a laser beam or ultrasonic energy. At a second location, the amplitudes and phases of the acoustic waves are detected and the resonant frequencies' quality factors are calculated and compared to predetermined quality factor data, such comparison providing information of whether the test object contains a defect. The inspection system and method also includes means for mounting the bearing ball for inspection.

Resonant frequency method for bearing ball inspection

DOEpatents

Khuri-Yakub, B.T.; Chungkao Hsieh.

1993-11-02

The present invention provides for an inspection system and method for detecting defects in test objects which includes means for generating expansion inducing energy focused upon the test object at a first location, such expansion being allowed to contract, thereby causing pressure wave within and on the surface of the test object. Such expansion inducing energy may be provided by, for example, a laser beam or ultrasonic energy. At a second location, the amplitudes and phases of the acoustic waves are detected and the resonant frequencies' quality factors are calculated and compared to predetermined quality factor data, such comparison providing information of whether the test object contains a defect. The inspection system and method also includes means for mounting the bearing ball for inspection. 5 figures.

The effect of a finite focal spot size on location dependent detectability in a fan beam CT system

NASA Astrophysics Data System (ADS)

Kim, Byeongjoon; Baek, Jongduk

2017-03-01

A finite focal spot size is one of the sources to degrade the resolution performance in a fan beam CT system. In this work, we investigated the effect of the finite focal spot size on signal detectability. For the evaluation, five spherical objects with diameters of 1 mm, 2 mm, 3 mm, 4 mm, and 5 mm were used. The optical focal spot size viewed at the iso-center was a 1 mm (height) × 1 mm (width) with a target angle of 7 degrees, corresponding to an 8.21 mm (i.e., 1 mm / sin (7°)) focal spot length. Simulated projection data were acquired using 8 × 8 source lets, and reconstructed by Hanning weighted filtered backprojection. For each spherical object, the detectability was calculated at (0 mm, 0 mm) and (0 mm, 200 mm) using two image quality metrics: pixel signal to noise ratio (SNR) and detection SNR. For all signal sizes, the pixel SNR is higher at the iso-center since the noise variance at the off-center is much higher than that at the iso-center due to the backprojection weightings used in direct fan beam reconstruction. In contrast, detection SNR shows similar values for different spherical objects except 1 mm and 2 mm diameter spherical objects. Overall, the results indicate the resolution loss caused by the finite focal spot size degrades the detection performance, especially for small objects with less than 2 mm diameter.

[Development of operation patient security detection system].

PubMed

Geng, Shu-Qin; Tao, Ren-Hai; Zhao, Chao; Wei, Qun

2008-11-01

This paper describes a patient security detection system developed with two dimensional bar codes, wireless communication and removal storage technique. Based on the system, nurses and correlative personnel check code wait operation patient to prevent the defaults. The tests show the system is effective. Its objectivity and currency are more scientific and sophisticated than current traditional method in domestic hospital.

A novel snapshot polarimetric imager

NASA Astrophysics Data System (ADS)

Wong, Gerald; McMaster, Ciaran; Struthers, Robert; Gorman, Alistair; Sinclair, Peter; Lamb, Robert; Harvey, Andrew R.

2012-10-01

Polarimetric imaging (PI) is of increasing importance in determining additional scene information beyond that of conventional images. For very long-range surveillance, image quality is degraded due to turbulence. Furthermore, the high magnification required to create images with sufficient spatial resolution suitable for object recognition and identification require long focal length optical systems. These are incompatible with the size and weight restrictions for aircraft. Techniques which allow detection and recognition of an object at the single pixel level are therefore likely to provide advance warning of approaching threats or long-range object cueing. PI is a technique that has the potential to detect object signatures at the pixel level. Early attempts to develop PI used rotating polarisers (and spectral filters) which recorded sequential polarized images from which the complete Stokes matrix could be derived. This approach has built-in latency between frames and requires accurate registration of consecutive frames to analyze real-time video of moving objects. Alternatively, multiple optical systems and cameras have been demonstrated to remove latency, but this approach increases cost and bulk of the imaging system. In our investigation we present a simplified imaging system that divides an image into two orthogonal polarimetric components which are then simultaneously projected onto a single detector array. Thus polarimetric data is recorded without latency on a single snapshot. We further show that, for pixel-level objects, the data derived from only two orthogonal states (H and V) is sufficient to increase the probability of detection whilst reducing false alarms compared to conventional unpolarised imaging.

A multispectral automatic target recognition application for maritime surveillance, search, and rescue

NASA Astrophysics Data System (ADS)

Schoonmaker, Jon; Reed, Scott; Podobna, Yuliya; Vazquez, Jose; Boucher, Cynthia

2010-04-01

Due to increased security concerns, the commitment to monitor and maintain security in the maritime environment is increasingly a priority. A country's coast is the most vulnerable area for the incursion of illegal immigrants, terrorists and contraband. This work illustrates the ability of a low-cost, light-weight, multi-spectral, multi-channel imaging system to handle the environment and see under difficult marine conditions. The system and its implemented detecting and tracking technologies should be organic to the maritime homeland security community for search and rescue, fisheries, defense, and law enforcement. It is tailored for airborne and ship based platforms to detect, track and monitor suspected objects (such as semi-submerged targets like marine mammals, vessels in distress, and drug smugglers). In this system, automated detection and tracking technology is used to detect, classify and localize potential threats or objects of interest within the imagery provided by the multi-spectral system. These algorithms process the sensor data in real time, thereby providing immediate feedback when features of interest have been detected. A supervised detection system based on Haar features and Cascade Classifiers is presented and results are provided on real data. The system is shown to be extendable and reusable for a variety of different applications.

Smart sensing surveillance video system

NASA Astrophysics Data System (ADS)

Hsu, Charles; Szu, Harold

2016-05-01

An intelligent video surveillance system is able to detect and identify abnormal and alarming situations by analyzing object movement. The Smart Sensing Surveillance Video (S3V) System is proposed to minimize video processing and transmission, thus allowing a fixed number of cameras to be connected on the system, and making it suitable for its applications in remote battlefield, tactical, and civilian applications including border surveillance, special force operations, airfield protection, perimeter and building protection, and etc. The S3V System would be more effective if equipped with visual understanding capabilities to detect, analyze, and recognize objects, track motions, and predict intentions. In addition, alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies. The S3V System capabilities and technologies have great potential for both military and civilian applications, enabling highly effective security support tools for improving surveillance activities in densely crowded environments. It would be directly applicable to solutions for emergency response personnel, law enforcement, and other homeland security missions, as well as in applications requiring the interoperation of sensor networks with handheld or body-worn interface devices.

Detection of foreign body using fast thermoacoustic tomography with a multielement linear transducer array

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nie Liming; Xing Da; Yang Diwu

2007-04-23

Current imaging modalities face challenges in clinical applications due to limitations in resolution or contrast. Microwave-induced thermoacoustic imaging may provide a complementary modality for medical imaging, particularly for detecting foreign objects due to their different absorption of electromagnetic radiation at specific frequencies. A thermoacoustic tomography system with a multielement linear transducer array was developed and used to detect foreign objects in tissue. Radiography and thermoacoustic images of objects with different electromagnetic properties, including glass, sand, and iron, were compared. The authors' results demonstrate that thermoacoustic imaging has the potential to become a fast method for surgical localization of occult foreignmore » objects.« less

Detecting of foreign object debris on airfield pavement using convolution neural network

NASA Astrophysics Data System (ADS)

Cao, Xiaoguang; Gu, Yufeng; Bai, Xiangzhi

2017-11-01

It is of great practical significance to detect foreign object debris (FOD) timely and accurately on the airfield pavement, because the FOD is a fatal threaten for runway safety in airport. In this paper, a new FOD detection framework based on Single Shot MultiBox Detector (SSD) is proposed. Two strategies include making the detection network lighter and using dilated convolution, which are proposed to better solve the FOD detection problem. The advantages mainly include: (i) the network structure becomes lighter to speed up detection task and enhance detection accuracy; (ii) dilated convolution is applied in network structure to handle smaller FOD. Thus, we get a faster and more accurate detection system.

Improving Cognitive Skills of the Industrial Robot

NASA Astrophysics Data System (ADS)

Bezák, Pavol

2015-08-01

At present, there are plenty of industrial robots that are programmed to do the same repetitive task all the time. Industrial robots doing such kind of job are not able to understand whether the action is correct, effective or good. Object detection, manipulation and grasping is challenging due to the hand and object modeling uncertainties, unknown contact type and object stiffness properties. In this paper, the proposal of an intelligent humanoid hand object detection and grasping model is presented assuming that the object properties are known. The control is simulated in the Matlab Simulink/ SimMechanics, Neural Network Toolbox and Computer Vision System Toolbox.

Fourier Domain Sensing

NASA Technical Reports Server (NTRS)

Feldkhun, Daniel (Inventor); Wagner, Kelvin H. (Inventor)

2013-01-01

Methods and systems are disclosed of sensing an object. A first radiation is spatially modulated to generate a structured second radiation. The object is illuminated with the structured second radiation such that the object produces a third radiation in response. Apart from any spatially dependent delay, a time variation of the third radiation is spatially independent. With a single-element detector, a portion of the third radiation is detected from locations on the object simultaneously. At least one characteristic of a sinusoidal spatial Fourier-transform component of the object is estimated from a time-varying signal from the detected portion of the third radiation.

F.I.D.O. Focused Integration for Debris Observation

NASA Astrophysics Data System (ADS)

Ploschnitznig, J.

2013-09-01

The fact that satellites play a growing role in our day-to-day live, contributes to the overall assessment that these assets must be protected. As more and more objects enter space and begin to clutter this apparently endless vacuum, we begin to realize that these objects and associated debris become a potential and recurring threat. The space surveillance community routinely attempts to catalog debris through broad area search collection profiles, hoping to detect and track smaller and smaller objects. There are technical limitations to each collection system, we propose there may be new ways to increase the detection capability, effectively "Teaching an old dog (FIDO), new tricks." Far too often, we are justly criticized for never "stepping out of the box". The philosophy of "if it's not broke, don't fix it" works great if you assume that we are not broke. The assumption that in order to "Find" new space junk we need to increase our surveillance windows and try to cover as much space as possible may be appropriate for Missile Defense, but inappropriate for finding small space debris. Currently, our Phased Array Early Warning Systems support this yearly search program to try to acquire and track space small debris. A phased array can electronically scan the horizons very quickly, but the radar does have limitations. There is a closed-loop resource management equation that must be satisfied. By increasing search volume, we effectively reduce our instantaneous sensitivity which will directly impact our ability to find smaller and smaller space debris. Our proposal will be to focus on increasing sensitivity by reducing the search volume to statistically high probability of detection volumes in space. There are two phases to this proposal, a theoretical and empirical. Theoretical: The first phase will be to investigate the current space catalog and use existing ephemeris data on all satellites in the Space Surveillance Catalog to identify volumes of space with a high likelihood of encountering transiting satellite. Also during this phase, candidate radar systems will be characterized to determine sensitivity levels necessary to detect certain sized objects. Data integration plays a critical role in lowering the noise floor of the collection area in order to detect smaller and smaller objects. Reducing the search volume to these high probability of intercept areas will allow the use of data integration to increase the likelihood of detection of small Radar Cross Section objects. Empirical: The next phase is to employ this technique using a legacy collection system. The collection community may choose any collection system. The goal will be to demonstrate how focusing on a very specific area and employing data integration will increase the likelihood of detection of smaller objects. This will result in the creation of an Inter Range Vector (IRV), which can be handed-off to downrange collection systems for additional tracking. The goal of FIDO will be demonstrate how these legacy systems can be better employed to help find smaller and smaller debris.

Extended depth of field imaging for high speed object analysis

NASA Technical Reports Server (NTRS)

Frost, Keith (Inventor); Ortyn, William (Inventor); Basiji, David (Inventor); Bauer, Richard (Inventor); Liang, Luchuan (Inventor); Hall, Brian (Inventor); Perry, David (Inventor)

2011-01-01

A high speed, high-resolution flow imaging system is modified to achieve extended depth of field imaging. An optical distortion element is introduced into the flow imaging system. Light from an object, such as a cell, is distorted by the distortion element, such that a point spread function (PSF) of the imaging system is invariant across an extended depth of field. The distorted light is spectrally dispersed, and the dispersed light is used to simultaneously generate a plurality of images. The images are detected, and image processing is used to enhance the detected images by compensating for the distortion, to achieve extended depth of field images of the object. The post image processing preferably involves de-convolution, and requires knowledge of the PSF of the imaging system, as modified by the optical distortion element.

Development of dual sensor hand-held detector

NASA Astrophysics Data System (ADS)

Sezgin, Mehmet

2010-04-01

In this paper hand-held dual sensor detector development requirements are considered dedicated to buried object detection. Design characteristics of such a system are categorized and listed. Hardware and software structures, ergonomics, user interface, environmental and EMC/EMI tests to be applied and performance test issues are studied. Main properties of the developed system (SEZER) are presented, which contains Metal Detector (MD) and Ground Penetrating Radar (GPR). The realized system has ergonomic structure and can detect both metallic and non-metallic buried objects. Moreover classification of target is possible if it was defined to the signal processing software in learning phase.

Shallow Water Imaging Sonar System for Environmental Surveying Final Report CRADA No. TC-1130-95

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ng, L. C.; Rosenbaum, H.

The scope of this research is to develop a shallow water sonar system designed to detect and map the location of objects such as hazardous wastes or discarded ordnance in coastal waters. The system will use high frequency wide-bandwidth imaging sonar, mounted on a moving platform towed behind a boat, to detect and identify objects on the sea bottom. Resolved images can be obtained even if the targets are buried in an overlayer of silt. Reference 1 ( also attached) summarized the statement of work and the scope of collaboration.

Feasibility studies on explosive detection and homeland security applications using a neutron and x-ray combined computed tomography system

NASA Astrophysics Data System (ADS)

Sinha, V.; Srivastava, A.; Lee, H. K.; Liu, X.

2013-05-01

The successful creation and operation of a neutron and X-ray combined computed tomography (NXCT) system has been demonstrated by researchers at the Missouri University of Science and Technology. The NXCT system has numerous applications in the field of material characterization and object identification in materials with a mixture of atomic numbers represented. Presently, the feasibility studies have been performed for explosive detection and homeland security applications, particularly in concealed material detection and determination of the light atomic number materials. These materials cannot be detected using traditional X-ray imaging. The new system has the capability to provide complete structural and compositional information due to the complementary nature of X-ray and neutron interactions with materials. The design of the NXCT system facilitates simultaneous and instantaneous imaging operation, promising enhanced detection capabilities of explosive materials, low atomic number materials and illicit materials for homeland security applications. In addition, a sample positioning system allowing the user to remotely and automatically manipulate the sample makes the system viable for commercial applications. Several explosives and weapon simulants have been imaged and the results are provided. The fusion algorithms which combine the data from the neutron and X-ray imaging produce superior images. This paper is a compete overview of the NXCT system for feasibility studies of explosive detection and homeland security applications. The design of the system, operation, algorithm development, and detection schemes are provided. This is the first combined neutron and X-ray computed tomography system in operation. Furthermore, the method of fusing neutron and X-ray images together is a new approach which provides high contrast images of the desired object. The system could serve as a standardized tool in nondestructive testing of many applications, especially in explosives detection and homeland security research.

Real-Time pedestrian detection : layered object recognition system for pedestrian collision sensing.

DOT National Transportation Integrated Search

2010-01-01

In 2005 alone, 64,000 pedestrians were injured and 4,882 were killed in the United States, with pedestrians accounting for 11 percent of all traffic fatalities and 2 percent of injuries. The focus of "Layered Object Recognition System for Pedestrian ...

On improving IED object detection by exploiting scene geometry using stereo processing

NASA Astrophysics Data System (ADS)

van de Wouw, Dennis W. J. M.; Dubbelman, Gijs; de With, Peter H. N.

2015-03-01

Detecting changes in the environment with respect to an earlier data acquisition is important for several applications, such as finding Improvised Explosive Devices (IEDs). We explore and evaluate the benefit of depth sensing in the context of automatic change detection, where an existing monocular system is extended with a second camera in a fixed stereo setup. We then propose an alternative frame registration that exploits scene geometry, in particular the ground plane. Furthermore, change characterization is applied to localized depth maps to distinguish between 3D physical changes and shadows, which solves one of the main challenges of a monocular system. The proposed system is evaluated on real-world acquisitions, containing geo-tagged test objects of 18 18 9 cm up to a distance of 60 meters. The proposed extensions lead to a significant reduction of the false-alarm rate by a factor of 3, while simultaneously improving the detection score with 5%.

Detection, Location and Grasping Objects Using a Stereo Sensor on UAV in Outdoor Environments.

PubMed

Ramon Soria, Pablo; Arrue, Begoña C; Ollero, Anibal

2017-01-07

The article presents a vision system for the autonomous grasping of objects with Unmanned Aerial Vehicles (UAVs) in real time. Giving UAVs the capability to manipulate objects vastly extends their applications, as they are capable of accessing places that are difficult to reach or even unreachable for human beings. This work is focused on the grasping of known objects based on feature models. The system runs in an on-board computer on a UAV equipped with a stereo camera and a robotic arm. The algorithm learns a feature-based model in an offline stage, then it is used online for detection of the targeted object and estimation of its position. This feature-based model was proved to be robust to both occlusions and the presence of outliers. The use of stereo cameras improves the learning stage, providing 3D information and helping to filter features in the online stage. An experimental system was derived using a rotary-wing UAV and a small manipulator for final proof of concept. The robotic arm is designed with three degrees of freedom and is lightweight due to payload limitations of the UAV. The system has been validated with different objects, both indoors and outdoors.

Image processing system and method for recognizing and removing shadows from the image of a monitored scene

DOEpatents

Osbourn, Gordon C.

1996-01-01

The shadow contrast sensitivity of the human vision system is simulated by configuring information obtained from an image sensor so that the information may be evaluated with multiple pixel widths in order to produce a machine vision system able to distinguish between shadow edges and abrupt object edges. A second difference of the image intensity for each line of the image is developed and this second difference is used to screen out high frequency noise contributions from the final edge detection signals. These edge detection signals are constructed from first differences of the image intensity where the screening conditions are satisfied. The positional coincidence of oppositely signed maxima in the first difference signal taken from the right and the second difference signal taken from the left is used to detect the presence of an object edge. Alternatively, the effective number of responding operators (ENRO) may be utilized to determine the presence of object edges.

Danger detection and escape behaviour in wood crickets.

PubMed

Dupuy, Fabienne; Casas, Jérôme; Body, Mélanie; Lazzari, Claudio R

2011-07-01

The wind-sensitive cercal system of Orthopteroid insects that mediates the detection of the approach of a predator is a very sensitive sensory system. It has been intensively analysed from a behavioural and neurobiological point of view, and constitutes a classical model system in neuroethology. The escape behaviour is triggered in orthopteroids by the detection of air-currents produced by approaching objects, allowing these insects to keep away from potential dangers. Nevertheless, escape behaviour has not been studied in terms of success. Moreover, an attacking predator is more than "air movement", it is also a visible moving entity. The sensory basis of predator detection is thus probably more complex than the perception of air movement by the cerci. We have used a piston mimicking an attacking running predator for a quantitative evaluation of the escape behaviour of wood crickets Nemobius sylvestris. The movement of the piston not only generates air movement, but it can be seen by the insect and can touch it as a natural predator. This procedure allowed us to study the escape behaviour in terms of detection and also in terms of success. Our results showed that 5-52% of crickets that detected the piston thrust were indeed touched. Crickets escaped to stimulation from behind better than to a stimulation from the front, even though they detected the approaching object similarly in both cases. After cerci ablation, 48% crickets were still able to detect a piston approaching from behind (compared with 79% of detection in intact insects) and 24% crickets escaped successfully (compared with 62% in the case of intact insects). So, cerci play a major role in the detection of an approaching object but other mechanoreceptors or sensory modalities are implicated in this detection. It is not possible to assure that other sensory modalities participate (in the case of intact animals) in the behaviour; rather, than in the absence of cerci other sensory modalities can partially mediate the behaviour. Nevertheless, neither antennae nor eyes seem to be used for detecting approaching objects, as their inactivation did not reduce their detection and escape abilities in the presence of cerci. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Novel Displacement and Tilt Detection Method Using Passive UHF RFID Technology.

PubMed

Lai, Xiaozheng; Cai, Zhirong; Xie, Zeming; Zhu, Hailong

2018-05-21

The displacement and tilt angle of an object are useful information for wireless monitoring applications. In this paper, a low-cost detection method based on passive radio frequency identification (RFID) technology is proposed. This method uses a standard ultrahigh-frequency (UHF) RFID reader to measure the phase variation of the tag response and detect the displacement and tilt angle of RFID tags attached to the targeted object. An accurate displacement result can be detected by the RFID system with a linearly polarized (LP) reader antenna. Based on the displacement results, an accurate tilt angle can also be detected by the RFID system with a circularly polarized (CP) reader antenna, which has been proved to have a linear relationship with the phase parameter of the tag’s backscattered wave. As far as accuracy is concerned, the mean absolute error (MAE) of displacement is less than 2 mm and the MAE of the tilt angle is less than 2.5° for an RFID system with 500 mm working range.

A new method for text detection and recognition in indoor scene for assisting blind people

NASA Astrophysics Data System (ADS)

Jabnoun, Hanen; Benzarti, Faouzi; Amiri, Hamid

2017-03-01

Developing assisting system of handicapped persons become a challenging ask in research projects. Recently, a variety of tools are designed to help visually impaired or blind people object as a visual substitution system. The majority of these tools are based on the conversion of input information into auditory or tactile sensory information. Furthermore, object recognition and text retrieval are exploited in the visual substitution systems. Text detection and recognition provides the description of the surrounding environments, so that the blind person can readily recognize the scene. In this work, we aim to introduce a method for detecting and recognizing text in indoor scene. The process consists on the detection of the regions of interest that should contain the text using the connected component. Then, the text detection is provided by employing the images correlation. This component of an assistive blind person should be simple, so that the users are able to obtain the most informative feedback within the shortest time.

A traffic situation analysis system

NASA Astrophysics Data System (ADS)

Sidla, Oliver; Rosner, Marcin

2011-01-01

The observation and monitoring of traffic with smart visions systems for the purpose of improving traffic safety has a big potential. For example embedded vision systems built into vehicles can be used as early warning systems, or stationary camera systems can modify the switching frequency of signals at intersections. Today the automated analysis of traffic situations is still in its infancy - the patterns of vehicle motion and pedestrian flow in an urban environment are too complex to be fully understood by a vision system. We present steps towards such a traffic monitoring system which is designed to detect potentially dangerous traffic situations, especially incidents in which the interaction of pedestrians and vehicles might develop into safety critical encounters. The proposed system is field-tested at a real pedestrian crossing in the City of Vienna for the duration of one year. It consists of a cluster of 3 smart cameras, each of which is built from a very compact PC hardware system in an outdoor capable housing. Two cameras run vehicle detection software including license plate detection and recognition, one camera runs a complex pedestrian detection and tracking module based on the HOG detection principle. As a supplement, all 3 cameras use additional optical flow computation in a low-resolution video stream in order to estimate the motion path and speed of objects. This work describes the foundation for all 3 different object detection modalities (pedestrians, vehi1cles, license plates), and explains the system setup and its design.

"SmartMonitor"--an intelligent security system for the protection of individuals and small properties with the possibility of home automation.

PubMed

Frejlichowski, Dariusz; Gościewska, Katarzyna; Forczmański, Paweł; Hofman, Radosław

2014-06-05

"SmartMonitor" is an intelligent security system based on image analysis that combines the advantages of alarm, video surveillance and home automation systems. The system is a complete solution that automatically reacts to every learned situation in a pre-specified way and has various applications, e.g., home and surrounding protection against unauthorized intrusion, crime detection or supervision over ill persons. The software is based on well-known and proven methods and algorithms for visual content analysis (VCA) that were appropriately modified and adopted to fit specific needs and create a video processing model which consists of foreground region detection and localization, candidate object extraction, object classification and tracking. In this paper, the "SmartMonitor" system is presented along with its architecture, employed methods and algorithms, and object analysis approach. Some experimental results on system operation are also provided. In the paper, focus is put on one of the aforementioned functionalities of the system, namely supervision over ill persons.

Development and Testing of a Prototype Connected Vehicle Wrong-Way Driving Detection and Management System

DOT National Transportation Integrated Search

2018-02-01

The primary objective of Phase II was to develop a prototype connected vehicle wrong-way driving detection and management system at the Texas A&M University Respect, Excellence, Leadership, Loyalty, Integrity, Selfless Service (RELLIS) campus. The pu...

Perspectives on the Meaning of Detectable Distribution System Residual and Implications for N. Fowleri Control

EPA Science Inventory

The objectives of this presentation are to: review history of distribution system chlorination regulations, raise awareness on the meaning of detectable residual as it relates to chloramines, and perhaps renew dialogue on the discussion of minimum disinfectant residuals.

Nature as a model for biomimetic sensors

NASA Astrophysics Data System (ADS)

Bleckmann, H.

2012-04-01

Mammals, like humans, rely mainly on acoustic, visual and olfactory information. In addition, most also use tactile and thermal cues for object identification and spatial orientation. Most non-mammalian animals also possess a visual, acoustic and olfactory system. However, besides these systems they have developed a large variety of highly specialized sensors. For instance, pyrophilous insects use infrared organs for the detection of forest fires while boas, pythons and pit vipers sense the infrared radiation emitted by prey animals. All cartilaginous and bony fishes as well as some amphibians have a mechnaosensory lateral line. It is used for the detection of weak water motions and pressure gradients. For object detection and spatial orientation many species of nocturnal fish employ active electrolocation. This review describes certain aspects of the detection and processing of infrared, mechano- and electrosensory information. It will be shown that the study of these seemingly exotic sensory systems can lead to discoveries that are useful for the construction of technical sensors and artificial control systems.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roy, Tushar, E-mail: tushar@barc.gov.in; Kashyap, Yogesh; Shukla, Mayank

Associated particle technique (APT) for detection of explosives is well established but has been implemented mostly for fixed portal systems. In certain situations, a portable system is required where the suspect object cannot be moved from site. This paper discusses the development of a portable APT system in single-sided geometry which can be transported to site and requires only one-sided access to the object. The system comprised D-T neutron source and bismuth germanate (BGO) detectors fixed on a portable module. Different aspects of the system have been discussed such as background contribution, time selection, and elemental signatures. The system wasmore » used to detect benign samples and explosive simulants under laboratory condition. The elemental ratios obtained by analyzing the gamma spectra show good match with the theoretical ratios.« less

A low cost automatic detection and ranging system for space surveillance in the medium Earth orbit region and beyond.

PubMed

Danescu, Radu; Ciurte, Anca; Turcu, Vlad

2014-02-11

The space around the Earth is filled with man-made objects, which orbit the planet at altitudes ranging from hundreds to tens of thousands of kilometers. Keeping an eye on all objects in Earth's orbit, useful and not useful, operational or not, is known as Space Surveillance. Due to cost considerations, the space surveillance solutions beyond the Low Earth Orbit region are mainly based on optical instruments. This paper presents a solution for real-time automatic detection and ranging of space objects of altitudes ranging from below the Medium Earth Orbit up to 40,000 km, based on two low cost observation systems built using commercial cameras and marginally professional telescopes, placed 37 km apart, operating as a large baseline stereovision system. The telescopes are pointed towards any visible region of the sky, and the system is able to automatically calibrate the orientation parameters using automatic matching of reference stars from an online catalog, with a very high tolerance for the initial guess of the sky region and camera orientation. The difference between the left and right image of a synchronized stereo pair is used for automatic detection of the satellite pixels, using an original difference computation algorithm that is capable of high sensitivity and a low false positive rate. The use of stereovision provides a strong means of removing false positives, and avoids the need for prior knowledge of the orbits observed, the system being able to detect at the same time all types of objects that fall within the measurement range and are visible on the image.

Improved Object Detection Using a Robotic Sensing Antenna with Vibration Damping Control

PubMed Central

Feliu-Batlle, Vicente; Feliu-Talegon, Daniel; Castillo-Berrio, Claudia Fernanda

2017-01-01

Some insects or mammals use antennae or whiskers to detect by the sense of touch obstacles or recognize objects in environments in which other senses like vision cannot work. Artificial flexible antennae can be used in robotics to mimic this sense of touch in these recognition tasks. We have designed and built a two-degree of freedom (2DOF) flexible antenna sensor device to perform robot navigation tasks. This device is composed of a flexible beam, two servomotors that drive the beam and a load cell sensor that detects the contact of the beam with an object. It is found that the efficiency of such a device strongly depends on the speed and accuracy achieved by the antenna positioning system. These issues are severely impaired by the vibrations that appear in the antenna during its movement. However, these antennae are usually moved without taking care of these undesired vibrations. This article proposes a new closed-loop control schema that cancels vibrations and improves the free movements of the antenna. Moreover, algorithms to estimate the 3D beam position and the instant and point of contact with an object are proposed. Experiments are reported that illustrate the efficiency of these proposed algorithms and the improvements achieved in object detection tasks using a control system that cancels beam vibrations. PMID:28406449

Improved Object Detection Using a Robotic Sensing Antenna with Vibration Damping Control.

PubMed

Feliu-Batlle, Vicente; Feliu-Talegon, Daniel; Castillo-Berrio, Claudia Fernanda

2017-04-13

Some insects or mammals use antennae or whiskers to detect by the sense of touch obstacles or recognize objects in environments in which other senses like vision cannot work. Artificial flexible antennae can be used in robotics to mimic this sense of touch in these recognition tasks. We have designed and built a two-degree of freedom (2DOF) flexible antenna sensor device to perform robot navigation tasks. This device is composed of a flexible beam, two servomotors that drive the beam and a load cell sensor that detects the contact of the beam with an object. It is found that the efficiency of such a device strongly depends on the speed and accuracy achieved by the antenna positioning system. These issues are severely impaired by the vibrations that appear in the antenna during its movement. However, these antennae are usually moved without taking care of these undesired vibrations. This article proposes a new closed-loop control schema that cancels vibrations and improves the free movements of the antenna. Moreover, algorithms to estimate the 3D beam position and the instant and point of contact with an object are proposed. Experiments are reported that illustrate the efficiency of these proposed algorithms and the improvements achieved in object detection tasks using a control system that cancels beam vibrations.

Development of Decision Making Algorithm for Control of Sea Cargo Containers by ``TAGGED'' Neutron Method

NASA Astrophysics Data System (ADS)

Anan'ev, A. A.; Belichenko, S. G.; Bogolyubov, E. P.; Bochkarev, O. V.; Petrov, E. V.; Polishchuk, A. M.; Udaltsov, A. Yu.

2009-12-01

Nowadays in Russia and abroad there are several groups of scientists, engaged in development of systems based on "tagged" neutron method (API method) and intended for detection of dangerous materials, including high explosives (HE). Particular attention is paid to possibility of detection of dangerous objects inside a sea cargo container. Energy gamma-spectrum, registered from object under inspection is used for determination of oxygen/carbon and nitrogen/carbon chemical ratios, according to which dangerous object is distinguished from not dangerous one. Material of filled container, however, gives rise to additional effects of rescattering and moderation of 14 MeV primary neutrons of generator, attenuation of secondary gamma-radiation from reactions of inelastic neutron scattering on objects under inspection. These effects lead to distortion of energy gamma-response from examined object and therefore prevent correct recognition of chemical ratios. These difficulties are taken into account in analytical method, presented in the paper. Method has been validated against experimental data, obtained by the system for HE detection in sea cargo, based on API method and developed in VNIIA. Influence of shielding materials on results of HE detection and identification is considered. Wood and iron were used as shielding materials. Results of method application for analysis of experimental data on HE simulator measurement (tetryl, trotyl, hexogen) are presented.

Flexible feature-space-construction architecture and its VLSI implementation for multi-scale object detection

NASA Astrophysics Data System (ADS)

Luo, Aiwen; An, Fengwei; Zhang, Xiangyu; Chen, Lei; Huang, Zunkai; Jürgen Mattausch, Hans

2018-04-01

Feature extraction techniques are a cornerstone of object detection in computer-vision-based applications. The detection performance of vison-based detection systems is often degraded by, e.g., changes in the illumination intensity of the light source, foreground-background contrast variations or automatic gain control from the camera. In order to avoid such degradation effects, we present a block-based L1-norm-circuit architecture which is configurable for different image-cell sizes, cell-based feature descriptors and image resolutions according to customization parameters from the circuit input. The incorporated flexibility in both the image resolution and the cell size for multi-scale image pyramids leads to lower computational complexity and power consumption. Additionally, an object-detection prototype for performance evaluation in 65 nm CMOS implements the proposed L1-norm circuit together with a histogram of oriented gradients (HOG) descriptor and a support vector machine (SVM) classifier. The proposed parallel architecture with high hardware efficiency enables real-time processing, high detection robustness, small chip-core area as well as low power consumption for multi-scale object detection.

42 CFR 37.42 - Chest radiograph specifications-digital radiography systems.

Code of Federal Regulations, 2014 CFR

2014-10-01

... resolution, modulation transfer function (MTF), image signal-to-noise and detective quantum efficiency must... Information Object Definitions, sections: Computed Radiography Image Information Object Definition; Digital X...

Electric fish as natural models for technical sensor systems

NASA Astrophysics Data System (ADS)

von der Emde, Gerhard; Bousack, Herbert; Huck, Christina; Mayekar, Kavita; Pabst, Michael; Zhang, Yi

2009-05-01

Instead of vision, many animals use alternative senses for object detection. Weakly electric fish employ "active electrolocation", during which they discharge an electric organ emitting electrical current pulses (electric organ discharges, EOD). Local EODs are sensed by electroreceptors in the fish's skin, which respond to changes of the signal caused by nearby objects. Fish can gain information about attributes of an object, such as size, shape, distance, and complex impedance. When close to the fish, each object projects an 'electric image' onto the fish's skin. In order to get information about an object, the fish has to analyze the object's electric image by sampling its voltage distribution with the electroreceptors. We now know a great deal about the mechanisms the fish use to gain information about objects in their environment. Inspired by the remarkable capabilities of weakly electric fish in detecting and recognizing objects with their electric sense, we are designing technical sensor systems that can solve similar sensing problems. We applied the principles of active electrolocation to devices that produce electrical current pulses in water and simultaneously sense local current densities. Depending on the specific task, sensors can be designed which detect an object, localize it in space, determine its distance, and measure certain object properties such as material properties, thickness, or material faults. We present first experiments and FEM simulations on the optimal sensor arrangement regarding the sensor requirements e. g. localization of objects or distance measurements. Different methods of the sensor read-out and signal processing are compared.

Very-Long-Distance Remote Hearing and Vibrometry

NASA Technical Reports Server (NTRS)

Maleki, Lute; Yu, Nan; Matsko, Andrey; Savchenkov, Anatoliy

2009-01-01

A proposed development of laser-based instrumentation systems would extend the art of laser Doppler vibrometry beyond the prior limits of laser-assisted remote hearing and industrial vibrometry for detecting defects in operating mechanisms. A system according to the proposal could covertly measure vibrations of objects at distances as large as thousands of kilometers and could process the measurement data to enable recognition of vibrations characteristic of specific objects of interest, thereby enabling recognition of the objects themselves. A typical system as envisioned would be placed in orbit around the Earth for use as a means of determining whether certain objects on or under the ground are of interest as potential military targets. Terrestrial versions of these instruments designed for airborne or land- or sea-based operation could be similarly useful for military or law-enforcement purposes. Prior laser-based remote-hearing systems are not capable of either covert operation or detecting signals beyond modest distances when operated at realistic laser power levels. The performances of prior systems for recognition of objects by remote vibrometry are limited by low signal-to-noise ratios and lack of filtering of optical signals returned from targets. The proposed development would overcome these limitations. A system as proposed would include a narrow-band laser as its target illuminator, a lock-in-detection receiver subsystem, and a laser-power-control subsystem that would utilize feedback of the intensity of background illumination of the target to adjust the laser power. The laser power would be set at a level high enough to enable the desired measurements but below the threshold of detectability by an imaginary typical modern photodetector located at the target and there exposed to the background illumination. The laser beam would be focused tightly on the distant target, such that the receiving optics would be exposed to only one speckle. The return signal would be extremely-narrow-band filtered (to sub-kilohertz bandwidth) in the optical domain by a whispering-gallery- mode filter so as to remove most of the background illumination. The filtered optical signal would be optically amplified. This combination of optical filtering and optical amplification would provide an optical signal that would be strong enough to be detectable but not so strong as to saturate the detector in the lock-in detection subsystem.

Smart sensing surveillance system

NASA Astrophysics Data System (ADS)

Hsu, Charles; Chu, Kai-Dee; O'Looney, James; Blake, Michael; Rutar, Colleen

2010-04-01

An effective public safety sensor system for heavily-populated applications requires sophisticated and geographically-distributed infrastructures, centralized supervision, and deployment of large-scale security and surveillance networks. Artificial intelligence in sensor systems is a critical design to raise awareness levels, improve the performance of the system and adapt to a changing scenario and environment. In this paper, a highly-distributed, fault-tolerant, and energy-efficient Smart Sensing Surveillance System (S4) is presented to efficiently provide a 24/7 and all weather security operation in crowded environments or restricted areas. Technically, the S4 consists of a number of distributed sensor nodes integrated with specific passive sensors to rapidly collect, process, and disseminate heterogeneous sensor data from near omni-directions. These distributed sensor nodes can cooperatively work to send immediate security information when new objects appear. When the new objects are detected, the S4 will smartly select the available node with a Pan- Tilt- Zoom- (PTZ) Electro-Optics EO/IR camera to track the objects and capture associated imagery. The S4 provides applicable advanced on-board digital image processing capabilities to detect and track the specific objects. The imaging detection operations include unattended object detection, human feature and behavior detection, and configurable alert triggers, etc. Other imaging processes can be updated to meet specific requirements and operations. In the S4, all the sensor nodes are connected with a robust, reconfigurable, LPI/LPD (Low Probability of Intercept/ Low Probability of Detect) wireless mesh network using Ultra-wide band (UWB) RF technology. This UWB RF technology can provide an ad-hoc, secure mesh network and capability to relay network information, communicate and pass situational awareness and messages. The Service Oriented Architecture of S4 enables remote applications to interact with the S4 network and use the specific presentation methods. In addition, the S4 is compliant with Open Geospatial Consortium - Sensor Web Enablement (OGC-SWE) standards to efficiently discover, access, use, and control heterogeneous sensors and their metadata. These S4 capabilities and technologies have great potential for both military and civilian applications, enabling highly effective security support tools for improving surveillance activities in densely crowded environments. The S4 system is directly applicable to solutions for emergency response personnel, law enforcement, and other homeland security missions, as well as in applications requiring the interoperation of sensor networks with handheld or body-worn interface devices.

Design and Evaluation of Perceptual-based Object Group Selection Techniques

NASA Astrophysics Data System (ADS)

Dehmeshki, Hoda

Selecting groups of objects is a frequent task in graphical user interfaces. It is required prior to many standard operations such as deletion, movement, or modification. Conventional selection techniques are lasso, rectangle selection, and the selection and de-selection of items through the use of modifier keys. These techniques may become time-consuming and error-prone when target objects are densely distributed or when the distances between target objects are large. Perceptual-based selection techniques can considerably improve selection tasks when targets have a perceptual structure, for example when arranged along a line. Current methods to detect such groups use ad hoc grouping algorithms that are not based on results from perception science. Moreover, these techniques do not allow selecting groups with arbitrary arrangements or permit modifying a selection. This dissertation presents two domain-independent perceptual-based systems that address these issues. Based on established group detection models from perception research, the proposed systems detect perceptual groups formed by the Gestalt principles of good continuation and proximity. The new systems provide gesture-based or click-based interaction techniques for selecting groups with curvilinear or arbitrary structures as well as clusters. Moreover, the gesture-based system is adapted for the graph domain to facilitate path selection. This dissertation includes several user studies that show the proposed systems outperform conventional selection techniques when targets form salient perceptual groups and are still competitive when targets are semi-structured.

Detection of hidden objects using a real-time 3-D millimeter-wave imaging system

NASA Astrophysics Data System (ADS)

Rozban, Daniel; Aharon, Avihai; Levanon, Assaf; Abramovich, Amir; Yitzhaky, Yitzhak; Kopeika, N. S.

2014-10-01

Millimeter (mm)and sub-mm wavelengths or terahertz (THz) band have several properties that motivate their use in imaging for security applications such as recognition of hidden objects, dangerous materials, aerosols, imaging through walls as in hostage situations, and also in bad weather conditions. There is no known ionization hazard for biological tissue, and atmospheric degradation of THz radiation is relatively low for practical imaging distances. We recently developed a new technology for the detection of THz radiation. This technology is based on very inexpensive plasma neon indicator lamps, also known as Glow Discharge Detector (GDD), that can be used as very sensitive THz radiation detectors. Using them, we designed and constructed a Focal Plane Array (FPA) and obtained recognizable2-dimensional THz images of both dielectric and metallic objects. Using THz wave it is shown here that even concealed weapons made of dielectric material can be detected. An example is an image of a knife concealed inside a leather bag and also under heavy clothing. Three-dimensional imaging using radar methods can enhance those images since it can allow the isolation of the concealed objects from the body and environmental clutter such as nearby furniture or other people. The GDDs enable direct heterodyning between the electric field of the target signal and the reference signal eliminating the requirement for expensive mixers, sources, and Low Noise Amplifiers (LNAs).We expanded the ability of the FPA so that we are able to obtain recognizable 2-dimensional THz images in real time. We show here that the THz detection of objects in three dimensions, using FMCW principles is also applicable in real time. This imaging system is also shown here to be capable of imaging objects from distances allowing standoff detection of suspicious objects and humans from large distances.

A Scientific Workflow Platform for Generic and Scalable Object Recognition on Medical Images

NASA Astrophysics Data System (ADS)

Möller, Manuel; Tuot, Christopher; Sintek, Michael

In the research project THESEUS MEDICO we aim at a system combining medical image information with semantic background knowledge from ontologies to give clinicians fully cross-modal access to biomedical image repositories. Therefore joint efforts have to be made in more than one dimension: Object detection processes have to be specified in which an abstraction is performed starting from low-level image features across landmark detection utilizing abstract domain knowledge up to high-level object recognition. We propose a system based on a client-server extension of the scientific workflow platform Kepler that assists the collaboration of medical experts and computer scientists during development and parameter learning.

Ejection of rocky and icy material from binary star systems: implications for the origin and composition of 1I/`Oumuamua

NASA Astrophysics Data System (ADS)

Jackson, Alan P.; Tamayo, Daniel; Hammond, Noah; Ali-Dib, Mohamad; Rein, Hanno

2018-06-01

In single-star systems like our own Solar system, comets dominate the mass budget of bodies ejected into interstellar space, since they form further away and are less tightly bound. However, 1I/`Oumuamua, the first interstellar object detected, appears asteroidal in its spectra and lack of detectable activity. We argue that the galactic budget of interstellar objects like 1I/`Oumuamua should be dominated by planetesimal material ejected during planet formation in circumbinary systems, rather than in single-star systems or widely separated binaries. We further show that in circumbinary systems, rocky bodies should be ejected in comparable numbers to icy ones. This suggests that a substantial fraction of interstellar objects discovered in future should display an active coma. We find that the rocky population, of which 1I/`Oumuamua seems to be a member, should be predominantly sourced from A-type and late B-star binaries.

Miniature objective lens for array digital pathology: design improvement based on clinical evaluation

NASA Astrophysics Data System (ADS)

McCall, Brian; Pierce, Mark; Graviss, Edward A.; Richards-Kortum, Rebecca R.; Tkaczyk, Tomasz S.

2016-03-01

A miniature objective designed for digital detection of Mycobacterium tuberculosis (MTB) was evaluated for diagnostic accuracy. The objective was designed for array microscopy, but fabricated and evaluated at this stage of development as a single objective. The counts and diagnoses of patient samples were directly compared for digital detection and standard microscopy. The results were found to be correlated and highly concordant. The evaluation of this lens by direct comparison to standard fluorescence sputum smear microscopy presented unique challenges and led to some new insights in the role played by the system parameters of the microscope. The design parameters and how they were developed are reviewed in light of these results. New system parameters are proposed with the goal of easing the challenges of evaluating the miniature objective and maintaining the optical performance that produced the agreeable results presented without over-optimizing. A new design is presented that meets and exceeds these criteria.

Fusion of Local Statistical Parameters for Buried Underwater Mine Detection in Sonar Imaging

NASA Astrophysics Data System (ADS)

Maussang, F.; Rombaut, M.; Chanussot, J.; Hétet, A.; Amate, M.

2008-12-01

Detection of buried underwater objects, and especially mines, is a current crucial strategic task. Images provided by sonar systems allowing to penetrate in the sea floor, such as the synthetic aperture sonars (SASs), are of great interest for the detection and classification of such objects. However, the signal-to-noise ratio is fairly low and advanced information processing is required for a correct and reliable detection of the echoes generated by the objects. The detection method proposed in this paper is based on a data-fusion architecture using the belief theory. The input data of this architecture are local statistical characteristics extracted from SAS data corresponding to the first-, second-, third-, and fourth-order statistical properties of the sonar images, respectively. The interest of these parameters is derived from a statistical model of the sonar data. Numerical criteria are also proposed to estimate the detection performances and to validate the method.

A proposed search on the solar neighborhood for substellar objects

NASA Technical Reports Server (NTRS)

Reynolds, R. T.; Walker, R. G.; Tarter, J. C.

1980-01-01

The Infrared Astronomical Satellite (IRAS) program will produce an extremely sensitive all-sky survey over the wavelength region 8 to 120 microns when the mission is flown in 1982. These data will provide a novel opportunity to detect planetary-sized objects having masses smaller than 0.08 solar masses in or near the solar system. The improved detection limit of the IRAS will greatly increase the volume of space searched for such objects, as compared with previous optical and infrared studies.

Design and Simulation of Horn Antenna Using CST Software for GPR System

NASA Astrophysics Data System (ADS)

Joret, Ariffuddin; Sulong, M. S.; Abdullah, M. F. L.; Madun, Aziman; Haimi Dahlan, Samsul

2018-04-01

Detection of underground object can be made using a GPR system. This system is classified as a non-destructive technique (NDT) where the ground areas need not to be excavated. The technique used by the GPR system is by measuring the reflection of electromagnetic wave signal produced and detected by antenna which is known as the transmitter and the receiver antenna. In this study, a GPR system was studied by means of simulation using a Horn antenna as a transceiver antenna. The electromagnetic wave signal in this simulation is produced by current signal of an antenna which having a shape of modulation of Gaussian pulse which is having spectrum from 8 GHz until 12 GHz. CST and MATLAB Software are used in this GPR system simulation. A model of a Horn antenna has been designed using the CST software before the GPR’s system simulation modeled by adding a model of background in front of the Horn antenna. The simulation results show that the output signal of the Horn antenna can be used in detecting embedded object which are made from material of wood and iron. In addition, the simulation result has successfully developed a 3D model image of the GPR system using output signal of the Horn antenna. The embedded iron object in the GPR system simulation can be seen clearly by using this 3D image.

An improved NSGA - II algorithm for mixed model assembly line balancing

NASA Astrophysics Data System (ADS)

Wu, Yongming; Xu, Yanxia; Luo, Lifei; Zhang, Han; Zhao, Xudong

2018-05-01

Aiming at the problems of assembly line balancing and path optimization for material vehicles in mixed model manufacturing system, a multi-objective mixed model assembly line (MMAL), which is based on optimization objectives, influencing factors and constraints, is established. According to the specific situation, an improved NSGA-II algorithm based on ecological evolution strategy is designed. An environment self-detecting operator, which is used to detect whether the environment changes, is adopted in the algorithm. Finally, the effectiveness of proposed model and algorithm is verified by examples in a concrete mixing system.

A Web Browsing System by Eye-gaze Input

NASA Astrophysics Data System (ADS)

Abe, Kiyohiko; Owada, Kosuke; Ohi, Shoichi; Ohyama, Minoru

We have developed an eye-gaze input system for people with severe physical disabilities, such as amyotrophic lateral sclerosis (ALS) patients. This system utilizes a personal computer and a home video camera to detect eye-gaze under natural light. The system detects both vertical and horizontal eye-gaze by simple image analysis, and does not require special image processing units or sensors. We also developed the platform for eye-gaze input based on our system. In this paper, we propose a new web browsing system for physically disabled computer users as an application of the platform for eye-gaze input. The proposed web browsing system uses a method of direct indicator selection. The method categorizes indicators by their function. These indicators are hierarchized relations; users can select the felicitous function by switching indicators group. This system also analyzes the location of selectable object on web page, such as hyperlink, radio button, edit box, etc. This system stores the locations of these objects, in other words, the mouse cursor skips to the object of candidate input. Therefore it enables web browsing at a faster pace.

Fly Eye radar: detection through high scattered media

NASA Astrophysics Data System (ADS)

Molchanov, Pavlo; Gorwara, Ashok

2017-05-01

Longer radio frequency waves better penetrating through high scattered media than millimeter waves, but imaging resolution limited by diffraction at longer wavelength. Same time frequency and amplitudes of diffracted waves (frequency domain measurement) provides information of object. Phase shift of diffracted waves (phase front in time domain) consists information about shape of object and can be applied for reconstruction of object shape or even image by recording of multi-frequency digital hologram. Spectrum signature or refracted waves allows identify the object content. Application of monopulse method with overlap closely spaced antenna patterns provides high accuracy measurement of amplitude, phase, and direction to signal source. Digitizing of received signals separately in each antenna relative to processor time provides phase/frequency independence. Fly eye non-scanning multi-frequency radar system provides simultaneous continuous observation of multiple targets and wide possibilities for stepped frequency, simultaneous frequency, chaotic frequency sweeping waveform (CFS), polarization modulation for reliable object detection. Proposed c-band fly eye radar demonstrated human detection through 40 cm concrete brick wall with human and wall material spectrum signatures and can be applied for through wall human detection, landmines, improvised explosive devices detection, underground or camouflaged object imaging.

Groups of adjacent contour segments for object detection.

PubMed

Ferrari, V; Fevrier, L; Jurie, F; Schmid, C

2008-01-01

We present a family of scale-invariant local shape features formed by chains of k connected, roughly straight contour segments (kAS), and their use for object class detection. kAS are able to cleanly encode pure fragments of an object boundary, without including nearby clutter. Moreover, they offer an attractive compromise between information content and repeatability, and encompass a wide variety of local shape structures. We also define a translation and scale invariant descriptor encoding the geometric configuration of the segments within a kAS, making kAS easy to reuse in other frameworks, for example as a replacement or addition to interest points. Software for detecting and describing kAS is released on lear.inrialpes.fr/software. We demonstrate the high performance of kAS within a simple but powerful sliding-window object detection scheme. Through extensive evaluations, involving eight diverse object classes and more than 1400 images, we 1) study the evolution of performance as the degree of feature complexity k varies and determine the best degree; 2) show that kAS substantially outperform interest points for detecting shape-based classes; 3) compare our object detector to the recent, state-of-the-art system by Dalal and Triggs [4].

Inspection and analysis of the walls of fluid filled tubes by active electrolocation: a biomimetic approach

NASA Astrophysics Data System (ADS)

Gottwald, Martin; Mayekar, Kavita; Reiswich, Vladislav; Bousack, Herbert; Damalla, Deepak; Biswas, Shubham; Metzen, Michael G.; von der Emde, Gerhard

2011-04-01

During their nocturnal activity period, weakly electric fish employ a process called "active electrolocation" for navigation and object detection. They discharge an electric organ in their tail, which emits electrical current pulses, called electric organ discharges (EOD). Local EODs are sensed by arrays of electroreceptors in the fish's skin, which respond to modulations of the signal caused by nearby objects. Fish thus gain information about the size, shape, complex impedance and distance of objects. Inspired by these remarkable capabilities, we have designed technical sensor systems which employ active electrolocation to detect and analyse the walls of small, fluid filled pipes. Our sensor systems emit pulsed electrical signals into the conducting medium and simultaneously sense local current densities with an array of electrodes. Sensors can be designed which (i) analyse the tube wall, (ii) detect and localize material faults, (iii) identify wall inclusions or objects blocking the tube (iv) and find leakages. Here, we present first experiments and FEM simulations on the optimal sensor arrangement for different types of sensor systems and different types of tubes. In addition, different methods for sensor read-out and signal processing are compared. Our biomimetic sensor systems promise to be relatively insensitive to environmental disturbances such as heat, pressure, turbidity or muddiness. They could be used in a wide range of tubes and pipes including water pipes, hydraulic systems, and biological systems. Medical applications include catheter based sensors which inspect blood vessels, urethras and similar ducts in the human body.

A multi-camera system for real-time pose estimation

NASA Astrophysics Data System (ADS)

Savakis, Andreas; Erhard, Matthew; Schimmel, James; Hnatow, Justin

2007-04-01

This paper presents a multi-camera system that performs face detection and pose estimation in real-time and may be used for intelligent computing within a visual sensor network for surveillance or human-computer interaction. The system consists of a Scene View Camera (SVC), which operates at a fixed zoom level, and an Object View Camera (OVC), which continuously adjusts its zoom level to match objects of interest. The SVC is set to survey the whole filed of view. Once a region has been identified by the SVC as a potential object of interest, e.g. a face, the OVC zooms in to locate specific features. In this system, face candidate regions are selected based on skin color and face detection is accomplished using a Support Vector Machine classifier. The locations of the eyes and mouth are detected inside the face region using neural network feature detectors. Pose estimation is performed based on a geometrical model, where the head is modeled as a spherical object that rotates upon the vertical axis. The triangle formed by the mouth and eyes defines a vertical plane that intersects the head sphere. By projecting the eyes-mouth triangle onto a two dimensional viewing plane, equations were obtained that describe the change in its angles as the yaw pose angle increases. These equations are then combined and used for efficient pose estimation. The system achieves real-time performance for live video input. Testing results assessing system performance are presented for both still images and video.

Methods, systems and devices for detecting and locating ferromagnetic objects

DOEpatents

Roybal, Lyle Gene [Idaho Falls, ID; Kotter, Dale Kent [Shelley, ID; Rohrbaugh, David Thomas [Idaho Falls, ID; Spencer, David Frazer [Idaho Falls, ID

2010-01-26

Methods for detecting and locating ferromagnetic objects in a security screening system. One method includes a step of acquiring magnetic data that includes magnetic field gradients detected during a period of time. Another step includes representing the magnetic data as a function of the period of time. Another step includes converting the magnetic data to being represented as a function of frequency. Another method includes a step of sensing a magnetic field for a period of time. Another step includes detecting a gradient within the magnetic field during the period of time. Another step includes identifying a peak value of the gradient detected during the period of time. Another step includes identifying a portion of time within the period of time that represents when the peak value occurs. Another step includes configuring the portion of time over the period of time to represent a ratio.

78 FR 76860 - Contraband Screening for Criminal Justice Applications

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-19

... detection (e.g., transmission x-ray, active millimeter wave). 3. Size Class of the system/device: Fixed... traditional metal detectors will also be accepted. The NIJ Sensor, Surveillance and Biometric Technologies.... Whether the system/device Detects Metal objects. a. If YES, whether there are any types of metals that are...

Detection of cracks on tomatoes using hyperspectral near-infrared reflectance imaging system

USDA-ARS?s Scientific Manuscript database

The objective of this study was to evaluate the use of hyperspectral near-infrared (NIR) reflectance imaging techniques for detection of cuticle cracks on tomatoes. A hyperspectral near-infrared reflectance imaging system in the region of 1000-1700 nm was used to obtain hyperspectral reflectance ima...

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.

PubMed

Ren, Shaoqing; He, Kaiming; Girshick, Ross; Sun, Jian

2017-06-01

State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. Advances like SPPnet [1] and Fast R-CNN [2] have reduced the running time of these detection networks, exposing region proposal computation as a bottleneck. In this work, we introduce a Region Proposal Network (RPN) that shares full-image convolutional features with the detection network, thus enabling nearly cost-free region proposals. An RPN is a fully convolutional network that simultaneously predicts object bounds and objectness scores at each position. The RPN is trained end-to-end to generate high-quality region proposals, which are used by Fast R-CNN for detection. We further merge RPN and Fast R-CNN into a single network by sharing their convolutional features-using the recently popular terminology of neural networks with 'attention' mechanisms, the RPN component tells the unified network where to look. For the very deep VGG-16 model [3] , our detection system has a frame rate of 5 fps (including all steps) on a GPU, while achieving state-of-the-art object detection accuracy on PASCAL VOC 2007, 2012, and MS COCO datasets with only 300 proposals per image. In ILSVRC and COCO 2015 competitions, Faster R-CNN and RPN are the foundations of the 1st-place winning entries in several tracks. Code has been made publicly available.

Detecting and Analyzing Multiple Moving Objects in Crowded Environments with Coherent Motion Regions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cheriyadat, Anil M.

Understanding the world around us from large-scale video data requires vision systems that can perform automatic interpretation. While human eyes can unconsciously perceive independent objects in crowded scenes and other challenging operating environments, automated systems have difficulty detecting, counting, and understanding their behavior in similar scenes. Computer scientists at ORNL have a developed a technology termed as "Coherent Motion Region Detection" that invloves identifying multiple indepedent moving objects in crowded scenes by aggregating low-level motion cues extracted from moving objects. Humans and other species exploit such low-level motion cues seamlessely to perform perceptual grouping for visual understanding. The algorithm detectsmore » and tracks feature points on moving objects resulting in partial trajectories that span coherent 3D region in the space-time volume defined by the video. In the case of multi-object motion, many possible coherent motion regions can be constructed around the set of trajectories. The unique approach in the algorithm is to identify all possible coherent motion regions, then extract a subset of motion regions based on an innovative measure to automatically locate moving objects in crowded environments.The software reports snapshot of the object, count, and derived statistics ( count over time) from input video streams. The software can directly process videos streamed over the internet or directly from a hardware device (camera).« less

UAS Integration in the NAS Project: Flight Test 3 Data Analysis of JADEM-Autoresolver Detect and Avoid System

NASA Technical Reports Server (NTRS)

Gong, Chester; Wu, Minghong G.; Santiago, Confesor

2016-01-01

The Unmanned Aircraft Systems Integration in the National Airspace System project, or UAS Integration in the NAS, aims to reduce technical barriers related to safety and operational challenges associated with enabling routine UAS access to the NAS. The UAS Integration in the NAS Project conducted a flight test activity, referred to as Flight Test 3 (FT3), involving several Detect-and-Avoid (DAA) research prototype systems between June 15, 2015 and August 12, 2015 at the Armstrong Flight Research Center (AFRC). This report documents the flight testing and analysis results for the NASA Ames-developed JADEM-Autoresolver DAA system, referred to as 'Autoresolver' herein. Four flight test days (June 17, 18, 22, and July 22) were dedicated to Autoresolver testing. The objectives of this test were as follows: 1. Validate CPA prediction accuracy and detect-and-avoid (DAA, formerly known as self-separation) alerting logic in realistic flight conditions. 2. Validate DAA trajectory model including maneuvers. 3. Evaluate TCAS/DAA interoperability. 4. Inform final Minimum Operating Performance Standards (MOPS). Flight test scenarios were designed to collect data to directly address the objectives 1-3. Objective 4, inform final MOPS, was a general objective applicable to the UAS in the NAS project as a whole, of which flight test is a subset. This report presents analysis results completed in support of the UAS in the NAS project FT3 data review conducted on October 20, 2015. Due to time constraints and, to a lesser extent, TCAS data collection issues, objective 3 was not evaluated in this analysis.

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

NASA Technical Reports Server (NTRS)

Tescher, Andrew G. (Editor)

1989-01-01

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.

A brief visit from a red and extremely elongated interstellar asteroid.

PubMed

Meech, Karen J; Weryk, Robert; Micheli, Marco; Kleyna, Jan T; Hainaut, Olivier R; Jedicke, Robert; Wainscoat, Richard J; Chambers, Kenneth C; Keane, Jacqueline V; Petric, Andreea; Denneau, Larry; Magnier, Eugene; Berger, Travis; Huber, Mark E; Flewelling, Heather; Waters, Chris; Schunova-Lilly, Eva; Chastel, Serge

2017-12-21

None of the approximately 750,000 known asteroids and comets in the Solar System is thought to have originated outside it, despite models of the formation of planetary systems suggesting that orbital migration of giant planets ejects a large fraction of the original planetesimals into interstellar space. The high predicted number density of icy interstellar objects (2.4 × 10 -4 per cubic astronomical unit) suggests that some should have been detected, yet hitherto none has been seen. Many decades of asteroid and comet characterization have yielded formation models that explain the mass distribution, chemical abundances and planetary configuration of the Solar System today, but there has been no way of telling whether the Solar System is typical of planetary systems. Here we report observations and analysis of the object 1I/2017 U1 ('Oumuamua) that demonstrate its extrasolar trajectory, and that thus enable comparisons to be made between material from another planetary system and from our own. Our observations during the brief visit by the object to the inner Solar System reveal it to be asteroidal, with no hint of cometary activity despite an approach within 0.25 astronomical units of the Sun. Spectroscopic measurements show that the surface of the object is spectrally red, consistent with comets or organic-rich asteroids that reside within the Solar System. Light-curve observations indicate that the object has an extremely oblong shape, with a length about ten times its width, and a mean radius of about 102 metres assuming an albedo of 0.04. No known objects in the Solar System have such extreme dimensions. The presence of 'Oumuamua in the Solar System suggests that previous estimates of the number density of interstellar objects, based on the assumption that all such objects were cometary, were pessimistically low. Planned upgrades to contemporary asteroid survey instruments and improved data processing techniques are likely to result in the detection of more interstellar objects in the coming years.

Note: Reliable and non-contact 6D motion tracking system based on 2D laser scanners for cargo transportation.

PubMed

Kim, Young-Keun; Kim, Kyung-Soo

2014-10-01

Maritime transportation demands an accurate measurement system to track the motion of oscillating container boxes in real time. However, it is a challenge to design a sensor system that can provide both reliable and non-contact methods of 6-DOF motion measurements of a remote object for outdoor applications. In the paper, a sensor system based on two 2D laser scanners is proposed for detecting the relative 6-DOF motion of a crane load in real time. Even without implementing a camera, the proposed system can detect the motion of a remote object using four laser beam points. Because it is a laser-based sensor, the system is expected to be highly robust to sea weather conditions.

Note: Reliable and non-contact 6D motion tracking system based on 2D laser scanners for cargo transportation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Young-Keun, E-mail: ykkim@handong.edu; Kim, Kyung-Soo

Maritime transportation demands an accurate measurement system to track the motion of oscillating container boxes in real time. However, it is a challenge to design a sensor system that can provide both reliable and non-contact methods of 6-DOF motion measurements of a remote object for outdoor applications. In the paper, a sensor system based on two 2D laser scanners is proposed for detecting the relative 6-DOF motion of a crane load in real time. Even without implementing a camera, the proposed system can detect the motion of a remote object using four laser beam points. Because it is a laser-basedmore » sensor, the system is expected to be highly robust to sea weather conditions.« less

Note: Reliable and non-contact 6D motion tracking system based on 2D laser scanners for cargo transportation

NASA Astrophysics Data System (ADS)

Kim, Young-Keun; Kim, Kyung-Soo

2014-10-01

Maritime transportation demands an accurate measurement system to track the motion of oscillating container boxes in real time. However, it is a challenge to design a sensor system that can provide both reliable and non-contact methods of 6-DOF motion measurements of a remote object for outdoor applications. In the paper, a sensor system based on two 2D laser scanners is proposed for detecting the relative 6-DOF motion of a crane load in real time. Even without implementing a camera, the proposed system can detect the motion of a remote object using four laser beam points. Because it is a laser-based sensor, the system is expected to be highly robust to sea weather conditions.

Biases in the OSSOS Detection of Large Semimajor Axis Trans-Neptunian Objects

NASA Astrophysics Data System (ADS)

Gladman, Brett; Shankman, Cory; OSSOS Collaboration

2017-10-01

The accumulating but small set of large semimajor axis trans-Neptunian objects (TNOs) shows an apparent clustering in the orientations of their orbits. This clustering must either be representative of the intrinsic distribution of these TNOs, or else have arisen as a result of observation biases and/or statistically expected variations for such a small set of detected objects. The clustered TNOs were detected across different and independent surveys, which has led to claims that the detections are therefore free of observational bias. This apparent clustering has led to the so-called “Planet 9” hypothesis that a super-Earth currently resides in the distant solar system and causes this clustering. The Outer Solar System Origins Survey (OSSOS) is a large program that ran on the Canada-France-Hawaii Telescope from 2013 to 2017, discovering more than 800 new TNOs. One of the primary design goals of OSSOS was the careful determination of observational biases that would manifest within the detected sample. We demonstrate the striking and non-intuitive biases that exist for the detection of TNOs with large semimajor axes. The eight large semimajor axis OSSOS detections are an independent data set, of comparable size to the conglomerate samples used in previous studies. We conclude that the orbital distribution of the OSSOS sample is consistent with being detected from a uniform underlying angular distribution.

OSSOS. VI. Striking Biases in the Detection of Large Semimajor Axis Trans-Neptunian Objects

NASA Astrophysics Data System (ADS)

Shankman, Cory; Kavelaars, J. J.; Bannister, Michele T.; Gladman, Brett J.; Lawler, Samantha M.; Chen, Ying-Tung; Jakubik, Marian; Kaib, Nathan; Alexandersen, Mike; Gwyn, Stephen D. J.; Petit, Jean-Marc; Volk, Kathryn

2017-08-01

The accumulating but small set of large semimajor axis trans-Neptunian objects (TNOs) shows an apparent clustering in the orientations of their orbits. This clustering must either be representative of the intrinsic distribution of these TNOs, or else have arisen as a result of observation biases and/or statistically expected variations for such a small set of detected objects. The clustered TNOs were detected across different and independent surveys, which has led to claims that the detections are therefore free of observational bias. This apparent clustering has led to the so-called “Planet 9” hypothesis that a super-Earth currently resides in the distant solar system and causes this clustering. The Outer Solar System Origins Survey (OSSOS) is a large program that ran on the Canada–France–Hawaii Telescope from 2013 to 2017, discovering more than 800 new TNOs. One of the primary design goals of OSSOS was the careful determination of observational biases that would manifest within the detected sample. We demonstrate the striking and non-intuitive biases that exist for the detection of TNOs with large semimajor axes. The eight large semimajor axis OSSOS detections are an independent data set, of comparable size to the conglomerate samples used in previous studies. We conclude that the orbital distribution of the OSSOS sample is consistent with being detected from a uniform underlying angular distribution.

Optical system for object detection and delineation in space

NASA Astrophysics Data System (ADS)

Handelman, Amir; Shwartz, Shoam; Donitza, Liad; Chaplanov, Loran

2018-01-01

Object recognition and delineation is an important task in many environments, such as in crime scenes and operating rooms. Marking evidence or surgical tools and attracting the attention of the surrounding staff to the marked objects can affect people's lives. We present an optical system comprising a camera, computer, and small laser projector that can detect and delineate objects in the environment. To prove the optical system's concept, we show that it can operate in a hypothetical crime scene in which a pistol is present and automatically recognize and segment it by various computer-vision algorithms. Based on such segmentation, the laser projector illuminates the actual boundaries of the pistol and thus allows the persons in the scene to comfortably locate and measure the pistol without holding any intermediator device, such as an augmented reality handheld device, glasses, or screens. Using additional optical devices, such as diffraction grating and a cylinder lens, the pistol size can be estimated. The exact location of the pistol in space remains static, even after its removal. Our optical system can be fixed or dynamically moved, making it suitable for various applications that require marking of objects in space.

Improved segmentation of occluded and adjoining vehicles in traffic surveillance videos

NASA Astrophysics Data System (ADS)

Juneja, Medha; Grover, Priyanka

2013-12-01

Occlusion in image processing refers to concealment of any part of the object or the whole object from view of an observer. Real time videos captured by static cameras on roads often encounter overlapping and hence, occlusion of vehicles. Occlusion in traffic surveillance videos usually occurs when an object which is being tracked is hidden by another object. This makes it difficult for the object detection algorithms to distinguish all the vehicles efficiently. Also morphological operations tend to join the close proximity vehicles resulting in formation of a single bounding box around more than one vehicle. Such problems lead to errors in further video processing, like counting of vehicles in a video. The proposed system brings forward efficient moving object detection and tracking approach to reduce such errors. The paper uses successive frame subtraction technique for detection of moving objects. Further, this paper implements the watershed algorithm to segment the overlapped and adjoining vehicles. The segmentation results have been improved by the use of noise and morphological operations.

A Low Cost Automatic Detection and Ranging System for Space Surveillance in the Medium Earth Orbit Region and Beyond

PubMed Central

Danescu, Radu; Ciurte, Anca; Turcu, Vlad

2014-01-01

The space around the Earth is filled with man-made objects, which orbit the planet at altitudes ranging from hundreds to tens of thousands of kilometers. Keeping an eye on all objects in Earth's orbit, useful and not useful, operational or not, is known as Space Surveillance. Due to cost considerations, the space surveillance solutions beyond the Low Earth Orbit region are mainly based on optical instruments. This paper presents a solution for real-time automatic detection and ranging of space objects of altitudes ranging from below the Medium Earth Orbit up to 40,000 km, based on two low cost observation systems built using commercial cameras and marginally professional telescopes, placed 37 km apart, operating as a large baseline stereovision system. The telescopes are pointed towards any visible region of the sky, and the system is able to automatically calibrate the orientation parameters using automatic matching of reference stars from an online catalog, with a very high tolerance for the initial guess of the sky region and camera orientation. The difference between the left and right image of a synchronized stereo pair is used for automatic detection of the satellite pixels, using an original difference computation algorithm that is capable of high sensitivity and a low false positive rate. The use of stereovision provides a strong means of removing false positives, and avoids the need for prior knowledge of the orbits observed, the system being able to detect at the same time all types of objects that fall within the measurement range and are visible on the image. PMID:24521941

Detection, Location and Grasping Objects Using a Stereo Sensor on UAV in Outdoor Environments

PubMed Central

Ramon Soria, Pablo; Arrue, Begoña C.; Ollero, Anibal

2017-01-01

The article presents a vision system for the autonomous grasping of objects with Unmanned Aerial Vehicles (UAVs) in real time. Giving UAVs the capability to manipulate objects vastly extends their applications, as they are capable of accessing places that are difficult to reach or even unreachable for human beings. This work is focused on the grasping of known objects based on feature models. The system runs in an on-board computer on a UAV equipped with a stereo camera and a robotic arm. The algorithm learns a feature-based model in an offline stage, then it is used online for detection of the targeted object and estimation of its position. This feature-based model was proved to be robust to both occlusions and the presence of outliers. The use of stereo cameras improves the learning stage, providing 3D information and helping to filter features in the online stage. An experimental system was derived using a rotary-wing UAV and a small manipulator for final proof of concept. The robotic arm is designed with three degrees of freedom and is lightweight due to payload limitations of the UAV. The system has been validated with different objects, both indoors and outdoors. PMID:28067851

Electronic imaging system and technique

DOEpatents

Bolstad, J.O.

1984-06-12

A method and system for viewing objects obscurred by intense plasmas or flames (such as a welding arc) includes a pulsed light source to illuminate the object, the peak brightness of the light reflected from the object being greater than the brightness of the intense plasma or flame; an electronic image sensor for detecting a pulsed image of the illuminated object, the sensor being operated as a high-speed shutter; and electronic means for synchronizing the shutter operation with the pulsed light source.

Electronic imaging system and technique

DOEpatents

Bolstad, Jon O.

1987-01-01

A method and system for viewing objects obscurred by intense plasmas or flames (such as a welding arc) includes a pulsed light source to illuminate the object, the peak brightness of the light reflected from the object being greater than the brightness of the intense plasma or flame; an electronic image sensor for detecting a pulsed image of the illuminated object, the sensor being operated as a high-speed shutter; and electronic means for synchronizing the shutter operation with the pulsed light source.

Creating Usage Context-Based Object Similarities to Boost Recommender Systems in Technology Enhanced Learning

ERIC Educational Resources Information Center

Niemann, Katja; Wolpers, Martin

2015-01-01

In this paper, we introduce a new way of detecting semantic similarities between learning objects by analysing their usage in web portals. Our approach relies on the usage-based relations between the objects themselves rather then on the content of the learning objects or on the relations between users and learning objects. We then take this new…

Close-in detection system for the Mine Hunter/Killer program

NASA Astrophysics Data System (ADS)

Bishop, Steven S.; Campana, Stephen B.; Lang, David A.; Wiggins, Carl M.

2000-08-01

The Close-in Detection (CID) System is the vehicle-mounted multisensor landmine detection system for the Army CECOM Night Vision Electronic Sensors Directorate (NVESD) Mine Hunter/Killer (MH/K) Program. The CID System is being developed by BAE Systems in San Diego, CA. TRW Systems and Information Technology Group in Arlington, VA and a team of specialists for ERIM, E-OIR, SNL, and APL/JHU support NVESD in the development, analysis and testing of the CID and associated signal and data processing. The CID System includes tow down-looking sensor arrays: a ground- penetrating radar (GPR) array, and a set of Electro-Magnetic Induction (EMI) coils for metal detection. These arrays span a 3-meter wide swath in front of a high mobility, multipurpose wheeled vehicle. The system also includes a forward looking IR imaging system mounted on the roof of the vehicle and covering a swath of the road ahead of the vehicle. Signals from each sensor are processed separately to detect and localize objects of interest. Features of candidate objects are integrated in a processor that uses them to discriminates between anti-tank miens and clutter. Mine locations are passed to the neutralization subsystem of MH/K. This paper reviews the design of the sensors and signal processing of the CID system and gives examples and analysis of recent test results at the NVESD mine lanes. The strengths and weaknesses of each sensor are discussed, and the application of multisensor fusion is illustrated.

Gated frequency-resolved optical imaging with an optical parametric amplifier

DOEpatents

Cameron, S.M.; Bliss, D.E.; Kimmel, M.W.; Neal, D.R.

1999-08-10

A system for detecting objects in a turbid media utilizes an optical parametric amplifier as an amplifying gate for received light from the media. An optical gating pulse from a second parametric amplifier permits the system to respond to and amplify only ballistic photons from the object in the media. 13 figs.

Gated frequency-resolved optical imaging with an optical parametric amplifier

DOEpatents

Cameron, Stewart M.; Bliss, David E.; Kimmel, Mark W.; Neal, Daniel R.

1999-01-01

A system for detecting objects in a turbid media utilizes an optical parametric amplifier as an amplifying gate for received light from the media. An optical gating pulse from a second parametric amplifier permits the system to respond to and amplify only ballistic photons from the object in the media.

DEVELOPMENT OF DECISION MAKING ALGORITHM FOR CONTROL OF SEA CARGO CONTAINERS BY 'TAGGED' NEUTRON METHOD

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anan'ev, A. A.; Belichenko, S. G.; Bogolyubov, E. P.

Nowadays in Russia and abroad there are several groups of scientists, engaged in development of systems based on 'tagged' neutron method (API method) and intended for detection of dangerous materials, including high explosives (HE). Particular attention is paid to possibility of detection of dangerous objects inside a sea cargo container. Energy gamma-spectrum, registered from object under inspection is used for determination of oxygen/carbon and nitrogen/carbon chemical ratios, according to which dangerous object is distinguished from not dangerous one. Material of filled container, however, gives rise to additional effects of rescattering and moderation of 14 MeV primary neutrons of generator, attenuationmore » of secondary gamma-radiation from reactions of inelastic neutron scattering on objects under inspection. These effects lead to distortion of energy gamma-response from examined object and therefore prevent correct recognition of chemical ratios. These difficulties are taken into account in analytical method, presented in the paper. Method has been validated against experimental data, obtained by the system for HE detection in sea cargo, based on API method and developed in VNIIA. Influence of shielding materials on results of HE detection and identification is considered. Wood and iron were used as shielding materials. Results of method application for analysis of experimental data on HE simulator measurement (tetryl, trotyl, hexogen) are presented.« less

Small Arrays for Seismic Intruder Detections: A Simulation Based Experiment

NASA Astrophysics Data System (ADS)

Pitarka, A.

2014-12-01

Seismic sensors such as geophones and fiber optic have been increasingly recognized as promising technologies for intelligence surveillance, including intruder detection and perimeter defense systems. Geophone arrays have the capability to provide cost effective intruder detection in protecting assets with large perimeters. A seismic intruder detection system uses one or multiple arrays of geophones design to record seismic signals from footsteps and ground vehicles. Using a series of real-time signal processing algorithms the system detects, classify and monitors the intruder's movement. We have carried out numerical experiments to demonstrate the capability of a seismic array to detect moving targets that generate seismic signals. The seismic source is modeled as a vertical force acting on the ground that generates continuous impulsive seismic signals with different predominant frequencies. Frequency-wave number analysis of the synthetic array data was used to demonstrate the array's capability at accurately determining intruder's movement direction. The performance of the array was also analyzed in detecting two or more objects moving at the same time. One of the drawbacks of using a single array system is its inefficiency at detecting seismic signals deflected by large underground objects. We will show simulation results of the effect of an underground concrete block at shielding the seismic signal coming from an intruder. Based on simulations we found that multiple small arrays can greatly improve the system's detection capability in the presence of underground structures. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344

Object tracking using multiple camera video streams

NASA Astrophysics Data System (ADS)

Mehrubeoglu, Mehrube; Rojas, Diego; McLauchlan, Lifford

2010-05-01

Two synchronized cameras are utilized to obtain independent video streams to detect moving objects from two different viewing angles. The video frames are directly correlated in time. Moving objects in image frames from the two cameras are identified and tagged for tracking. One advantage of such a system involves overcoming effects of occlusions that could result in an object in partial or full view in one camera, when the same object is fully visible in another camera. Object registration is achieved by determining the location of common features in the moving object across simultaneous frames. Perspective differences are adjusted. Combining information from images from multiple cameras increases robustness of the tracking process. Motion tracking is achieved by determining anomalies caused by the objects' movement across frames in time in each and the combined video information. The path of each object is determined heuristically. Accuracy of detection is dependent on the speed of the object as well as variations in direction of motion. Fast cameras increase accuracy but limit the speed and complexity of the algorithm. Such an imaging system has applications in traffic analysis, surveillance and security, as well as object modeling from multi-view images. The system can easily be expanded by increasing the number of cameras such that there is an overlap between the scenes from at least two cameras in proximity. An object can then be tracked long distances or across multiple cameras continuously, applicable, for example, in wireless sensor networks for surveillance or navigation.

Berkeley UXO Discriminator (BUD)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gasperikova, Erika; Smith, J. Torquil; Morrison, H. Frank

2007-01-01

The Berkeley UXO Discriminator (BUD) is an optimally designed active electromagnetic system that not only detects but also characterizes UXO. The system incorporates three orthogonal transmitters and eight pairs of differenced receivers. it has two modes of operation: (1) search mode, in which BUD moves along a profile and exclusively detects targets in its vicinity, providing target depth and horizontal location, and (2) discrimination mode, in which BUD, stationary above a target, from a single position, determines three discriminating polarizability responses together with the object location and orientation. The performance of the system is governed by a target size-depth curve.more » Maximum detection depth is 1.5 m. While UXO objects have a single major polarizability coincident with the long axis of the object and two equal transverse polarizabilities, scrap metal has three different principal polarizabilities. The results clearly show that there are very clear distinctions between symmetric intact UXO and irregular scrap metal, and that BUD can resolve the intrinsic polarizabilities of the target. The field survey at the Yuma Proving Ground in Arizona showed excellent results within the predicted size-depth range.« less

Ophthalmological OCT measuring arm design

NASA Astrophysics Data System (ADS)

Xu, Xiaonan; Gao, Jiansong; Guo, Jihua; Xue, Ping

2002-06-01

This paper presents a novel ophthamological optical coherence tomography detecting instrument that we design and introduces measuring arm emphatically. For the glaucoma is very common in the orient, this system can achieve both the eyeground detection and the canthus detection. And it combines the cranny lamp's conventional detection with optical coherence tomography. In order to gain the best resolution and the largest scanning range in the OCT detection, we find the optical system should obey these principles in the measuring arm design: (i) the parallel light from the collimator goes through the lens and focuses on the slot of the cranny lamp. The movement of the scanning point produced by the scanner is carrying on along the slot. (Ii) In the whole light route, the scanner images on the laser object lens of the OCT. The center light of the infrared goes through the center of the object lens all the time. Considering all the system, this design has a longitudinal resolution of 15micrometers , and a transverse resolution of 20micrometers at imaging velocity of 4 frames per second.

WE-G-204-05: Relative Object Detectability Evaluation of a New High Resolution A-Se Direct Detection System Compared to Indirect Micro-Angiographic Fluoroscopic (MAF) Detectors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Russ, M; Nagesh, S Setlur; Ionita, C

2015-06-15

Purpose: To evaluate the task specific imaging performance of a new 25µm pixel pitch, 1000µm thick amorphous selenium direct detection system with CMOS readout for typical angiographic exposure parameters using the relative object detectability (ROD) metric. Methods: The ROD metric uses a simulated object function weighted at each spatial frequency by the detectors’ detective quantum efficiency (DQE), which is an intrinsic performance metric. For this study, the simulated objects were aluminum spheres of varying diameter (0.05–0.6mm). The weighted object function is then integrated over the full range of detectable frequencies inherent to each detector, and a ratio is taken ofmore » the resulting value for two detectors. The DQE for the 25µm detector was obtained from a simulation of a proposed a-Se detector using an exposure of 200µR for a 50keV x-ray beam. This a-Se detector was compared to two microangiographic fluoroscope (MAF) detectors [the MAF-CCD with pixel size of 35µm and Nyquist frequency of 14.2 cycles/mm and the MAF-CMOS with pixel size of 75µm and Nyquist frequency of 6.6 cycles/mm] and a standard flat-panel detector (FPD with pixel size of 194µm and Nyquist frequency of 2.5cycles/mm). Results: ROD calculations indicated vastly superior performance by the a-Se detector in imaging small aluminum spheres. For the 50µm diameter sphere, the ROD values for the a-Se detector compared to the MAF-CCD, the MAF-CMOS, and the FPD were 7.3, 9.3 and 58, respectively. Detector performance in the low frequency regime was dictated by each detector’s DQE(0) value. Conclusion: The a-Se with CMOS readout is unique and appears to have distinctive advantages of incomparable high resolution, low noise, no readout lag, and expandable design. The a-Se direct detection system will be a powerful imaging tool in angiography, with potential break-through applications in diagnosis and treatment of neuro-vascular disease. Supported by NIH Grant: 2R01EB002873 and an equipment grant from Toshiba Medical Systems Corporation.« less

“SmartMonitor” — An Intelligent Security System for the Protection of Individuals and Small Properties with the Possibility of Home Automation

PubMed Central

Frejlichowski, Dariusz; Gościewska, Katarzyna; Forczmański, Paweł; Hofman, Radosław

2014-01-01

“SmartMonitor” is an intelligent security system based on image analysis that combines the advantages of alarm, video surveillance and home automation systems. The system is a complete solution that automatically reacts to every learned situation in a pre-specified way and has various applications, e.g., home and surrounding protection against unauthorized intrusion, crime detection or supervision over ill persons. The software is based on well-known and proven methods and algorithms for visual content analysis (VCA) that were appropriately modified and adopted to fit specific needs and create a video processing model which consists of foreground region detection and localization, candidate object extraction, object classification and tracking. In this paper, the “SmartMonitor” system is presented along with its architecture, employed methods and algorithms, and object analysis approach. Some experimental results on system operation are also provided. In the paper, focus is put on one of the aforementioned functionalities of the system, namely supervision over ill persons. PMID:24905854

Shallow water imaging sonar system for environmental surveying. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1998-05-01

The scope of this research is to develop a shallow water sonar system designed to detect and map the location of objects such as hazardous wastes or discarded ordnance in coastal waters. The system will use high frequency wide-bandwidth imaging sonar, mounted on a moving platform towed behind a boat, to detect and identify objects on the sea bottom. Resolved images can be obtained even if the targets are buried in an overlayer of silt. The specific technical objective of this research was to develop and test a prototype system that is capable of (1) scan at high speeds (upmore » to 10m/s), even in shallow water (depth to ten meters), without motion blurring or loss of resolution; (2) produce images of the bottom structure that are detailed enough for unambiguous detection of objects as small as 15cm, even if they are buried up to 30cm deep in silt or sand. The critical technology involved uses an linear FM (LFM) or similar complex waveform, which has a high bandwidth for good range resolution, with a long pulse length for similar Dopper resolution. The lone duration signal deposits more energy on target than a narrower pulse, which increases the signal-to-noise ratio and signal-to-clutter ratio. This in turn allows the use of cheap, lightweight, low power, piezoelectric transducers at the 30--500 kHz range.« less

Detection of incipient defects in cables by partial discharge signal analysis

NASA Astrophysics Data System (ADS)

Martzloff, F. D.; Simmon, E.; Steiner, J. P.; Vanbrunt, R. J.

1992-07-01

As one of the objectives of a program aimed at assessing test methods for in-situ detection of incipient defects in cables due to aging, a laboratory test system was implemented to demonstrate that the partial discharge analysis method can be successfully applied to low-voltage cables. Previous investigations generally involved cables rated 5 kV or higher, while the objective of the program focused on the lower voltages associated with the safety systems of nuclear power plants. The defect detection system implemented for the project was based on commercially available signal analysis hardware and software packages, customized for the specific purposes of the project. The test specimens included several cables of the type found in nuclear power plants, including artificial defects introduced at various points of the cable. The results indicate that indeed, partial discharge analysis is capable of detecting incipient defects in low-voltage cables. There are, however, some limitations of technical and non-technical nature that need further exploration before this method can be accepted in the industry.

[The hazards of hospitals and selected public buildings of Legionella pneumophila].

PubMed

Sikora, Agnieszka; Kozioł-Montewka, Maria; Wójtowicz-Bobin, Małgorzata; Gładysz, Iwona; Dobosz, Paulina

2013-11-01

The registered infection and outbreaks of epidemic tend to monitor potential reservoirs of Legionella infection. According to the Act of 29 March 2007 on the requirements for the quality of water intended for human consumption are required to test for the presence and number of Legionella in the water system of hospitals. In case of detection of L. pneumophila serogroup 1 (SG 1) or increased above normal number other serogroups of bacteria it is necessary to eradicate these bacteria from the water system. The aim of this study was to assess the degree of contamination of the water supply system of selected public buildings and analyze the effectiveness of disinfection methods for the elimination of L. pneumophila in hot water systems. The materials for this study were hot and cold water samples which were collected from the water supply system of 23 different objects. Enumeration of Legionella bacteria in water samples was determined by membrane filtration (FM) and/or by surface inoculation methods according to the standards: PN-ISO 11731: 2002: "The quality of the water. Detection and enumeration of Legionella" and PN-EN ISO 11731-2: 2008: "Water quality--Detection and enumeration of Legionella--Part 2: Methodology of membrane filtration for water with a small number of bacteria". L. pneumophila was present in 164 samples of hot water, which accounted for 76.99%. In all tested water samples L. pneumophila SG 2-14 strains were detected. The most virulent strain--L. pneumophila SG 1 was not detected. In examined 23 objects in 12 of L. pneumophila exceed acceptable levels > 100 CFU/100 ml. The presence of L. pneumophila SG 2-14 demonstrated in all examined objects, indicating the risk of infection, and the need for permanent monitoring of the water system supply. The thermal disinfection is the most common, inexpensive, and effective method of control of L. pneumophila used in examined objects, but does not eliminate bacterial biofilm. Disinfection using the filters stopped of L. pneumophila, and was the method of complementary thermal disinfection. Chlorine dioxide is a very effective biocide for large numbers of L. pneumophila in water systems.

Advanced detection, isolation and accommodation of sensor failures: Real-time evaluation

NASA Technical Reports Server (NTRS)

Merrill, Walter C.; Delaat, John C.; Bruton, William M.

1987-01-01

The objective of the Advanced Detection, Isolation, and Accommodation (ADIA) Program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines by using analytical redundacy to detect sensor failures. The results of a real time hybrid computer evaluation of the ADIA algorithm are presented. Minimum detectable levels of sensor failures for an F100 engine control system are determined. Also included are details about the microprocessor implementation of the algorithm as well as a description of the algorithm itself.

Comet/Asteroid Protection System (CAPS): Preliminary Space-Based Concept and Study Results

NASA Technical Reports Server (NTRS)

Mazanek, Daniel D.; Roithmayr, Carlos M.; Antol, Jeffrey; Park, Sang-Young; Koons, Robert H.; Bremer, James C.; Murphy, Douglas G.; Hoffman, James A.; Kumar, Renjith R.; Seywald, Hans

2005-01-01

There exists an infrequent, but significant hazard to life and property due to impacting asteroids and comets. There is currently no specific search for long-period comets, smaller near-Earth asteroids, or smaller short-period comets. These objects represent a threat with potentially little or no warning time using conventional ground-based telescopes. These planetary bodies also represent a significant resource for commercial exploitation, long-term sustained space exploration, and scientific research. The Comet/Asteroid Protection System (CAPS) is a future space-based system concept that provides permanent, continuous asteroid and comet monitoring, and rapid, controlled modification of the orbital trajectories of selected bodies. CAPS would expand the current detection effort to include long-period comets, as well as small asteroids and short-period comets capable of regional destruction. A space-based detection system, despite being more costly and complex than Earth-based initiatives, is the most promising way of expanding the range of detectable objects, and surveying the entire celestial sky on a regular basis. CAPS would provide an orbit modification system capable of diverting kilometer class objects, and modifying the orbits of smaller asteroids for impact defense and resource utilization. This Technical Memorandum provides a compilation of key related topics and analyses performed during the CAPS study, which was performed under the Revolutionary Aerospace Systems Concepts (RASC) program, and discusses technologies that could enable the implementation of this future system.

Community detection in complex networks by using membrane algorithm

NASA Astrophysics Data System (ADS)

Liu, Chuang; Fan, Linan; Liu, Zhou; Dai, Xiang; Xu, Jiamei; Chang, Baoren

Community detection in complex networks is a key problem of network analysis. In this paper, a new membrane algorithm is proposed to solve the community detection in complex networks. The proposed algorithm is based on membrane systems, which consists of objects, reaction rules, and a membrane structure. Each object represents a candidate partition of a complex network, and the quality of objects is evaluated according to network modularity. The reaction rules include evolutionary rules and communication rules. Evolutionary rules are responsible for improving the quality of objects, which employ the differential evolutionary algorithm to evolve objects. Communication rules implement the information exchanged among membranes. Finally, the proposed algorithm is evaluated on synthetic, real-world networks with real partitions known and the large-scaled networks with real partitions unknown. The experimental results indicate the superior performance of the proposed algorithm in comparison with other experimental algorithms.

Design and Deployment of a Pediatric Cardiac Arrest Surveillance System

PubMed Central

Newton, Heather Marie; McNamara, Leann; Engorn, Branden Michael; Jones, Kareen; Bernier, Meghan; Dodge, Pamela; Salamone, Cheryl; Bhalala, Utpal; Jeffers, Justin M.; Engineer, Lilly; Diener-West, Marie; Hunt, Elizabeth Anne

2018-01-01

Objective We aimed to increase detection of pediatric cardiopulmonary resuscitation (CPR) events and collection of physiologic and performance data for use in quality improvement (QI) efforts. Materials and Methods We developed a workflow-driven surveillance system that leveraged organizational information technology systems to trigger CPR detection and analysis processes. We characterized detection by notification source, type, location, and year, and compared it to previous methods of detection. Results From 1/1/2013 through 12/31/2015, there were 2,986 unique notifications associated with 2,145 events, 317 requiring CPR. PICU and PEDS-ED accounted for 65% of CPR events, whereas floor care areas were responsible for only 3% of events. 100% of PEDS-OR and >70% of PICU CPR events would not have been included in QI efforts. Performance data from both defibrillator and bedside monitor increased annually. (2013: 1%; 2014: 18%; 2015: 27%). Discussion After deployment of this system, detection has increased ∼9-fold and performance data collection increased annually. Had the system not been deployed, 100% of PEDS-OR and 50–70% of PICU, NICU, and PEDS-ED events would have been missed. Conclusion By leveraging hospital information technology and medical device data, identification of pediatric cardiac arrest with an associated increased capture in the proportion of objective performance data is possible. PMID:29854451

Change blindness and visual memory: visual representations get rich and act poor.

PubMed

Varakin, D Alexander; Levin, Daniel T

2006-02-01

Change blindness is often taken as evidence that visual representations are impoverished, while successful recognition of specific objects is taken as evidence that they are richly detailed. In the current experiments, participants performed cover tasks that required each object in a display to be attended. Change detection trials were unexpectedly introduced and surprise recognition tests were given for nonchanging displays. For both change detection and recognition, participants had to distinguish objects from the same basic-level category, making it likely that specific visual information had to be used for successful performance. Although recognition was above chance, incidental change detection usually remained at floor. These results help reconcile demonstrations of poor change detection with demonstrations of good memory because they suggest that the capability to store visual information in memory is not reflected by the visual system's tendency to utilize these representations for purposes of detecting unexpected changes.

A fast automatic target detection method for detecting ships in infrared scenes

NASA Astrophysics Data System (ADS)

Özertem, Kemal Arda

2016-05-01

Automatic target detection in infrared scenes is a vital task for many application areas like defense, security and border surveillance. For anti-ship missiles, having a fast and robust ship detection algorithm is crucial for overall system performance. In this paper, a straight-forward yet effective ship detection method for infrared scenes is introduced. First, morphological grayscale reconstruction is applied to the input image, followed by an automatic thresholding onto the suppressed image. For the segmentation step, connected component analysis is employed to obtain target candidate regions. At this point, it can be realized that the detection is defenseless to outliers like small objects with relatively high intensity values or the clouds. To deal with this drawback, a post-processing stage is introduced. For the post-processing stage, two different methods are used. First, noisy detection results are rejected with respect to target size. Second, the waterline is detected by using Hough transform and the detection results that are located above the waterline with a small margin are rejected. After post-processing stage, there are still undesired holes remaining, which cause to detect one object as multi objects or not to detect an object as a whole. To improve the detection performance, another automatic thresholding is implemented only to target candidate regions. Finally, two detection results are fused and post-processing stage is repeated to obtain final detection result. The performance of overall methodology is tested with real world infrared test data.

Vehicle Localization by LIDAR Point Correlation Improved by Change Detection

NASA Astrophysics Data System (ADS)

Schlichting, A.; Brenner, C.

2016-06-01

LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or even construction sites could lead to wrong localization results, we use a change detection algorithm to detect these objects in the reference data. If an object occurs in a certain number of measurements at the same position, we mark it and every containing point as static. In the next step, we merge the data of the single measurement epochs to one reference dataset, whereby we only use static points. Further, we also use a classification algorithm to detect trees. For the online localization of the vehicle, we use simulated data of a vertical aligned automotive LiDAR sensor. As we only want to use static objects in this case as well, we use a random forest classifier to detect dynamic scan points online. Since the automotive data is derived from the LiDAR Mobile Mapping System, we are able to use the labelled objects from the reference data generation step to create the training data and further to detect dynamic objects online. The localization then can be done by a point to image correlation method using only static objects. We achieved a localization standard deviation of about 5 cm (position) and 0.06° (heading), and were able to successfully localize the vehicle in about 93 % of the cases along a trajectory of 13 km in Hannover, Germany.

Tracking Objects with Networked Scattered Directional Sensors

NASA Astrophysics Data System (ADS)

Plarre, Kurt; Kumar, P. R.

2007-12-01

We study the problem of object tracking using highly directional sensors—sensors whose field of vision is a line or a line segment. A network of such sensors monitors a certain region of the plane. Sporadically, objects moving in straight lines and at a constant speed cross the region. A sensor detects an object when it crosses its line of sight, and records the time of the detection. No distance or angle measurements are available. The task of the sensors is to estimate the directions and speeds of the objects, and the sensor lines, which are unknown a priori. This estimation problem involves the minimization of a highly nonconvex cost function. To overcome this difficulty, we introduce an algorithm, which we call "adaptive basis algorithm." This algorithm is divided into three phases: in the first phase, the algorithm is initialized using data from six sensors and four objects; in the second phase, the estimates are updated as data from more sensors and objects are incorporated. The third phase is an optional coordinated transformation. The estimation is done in an "ad-hoc" coordinate system, which we call "adaptive coordinate system." When more information is available, for example, the location of six sensors, the estimates can be transformed to the "real-world" coordinate system. This constitutes the third phase.

Automated Micro-Object Detection for Mobile Diagnostics Using Lens-Free Imaging Technology

PubMed Central

Roy, Mohendra; Seo, Dongmin; Oh, Sangwoo; Chae, Yeonghun; Nam, Myung-Hyun; Seo, Sungkyu

2016-01-01

Lens-free imaging technology has been extensively used recently for microparticle and biological cell analysis because of its high throughput, low cost, and simple and compact arrangement. However, this technology still lacks a dedicated and automated detection system. In this paper, we describe a custom-developed automated micro-object detection method for a lens-free imaging system. In our previous work (Roy et al.), we developed a lens-free imaging system using low-cost components. This system was used to generate and capture the diffraction patterns of micro-objects and a global threshold was used to locate the diffraction patterns. In this work we used the same setup to develop an improved automated detection and analysis algorithm based on adaptive threshold and clustering of signals. For this purpose images from the lens-free system were then used to understand the features and characteristics of the diffraction patterns of several types of samples. On the basis of this information, we custom-developed an automated algorithm for the lens-free imaging system. Next, all the lens-free images were processed using this custom-developed automated algorithm. The performance of this approach was evaluated by comparing the counting results with standard optical microscope results. We evaluated the counting results for polystyrene microbeads, red blood cells, HepG2, HeLa, and MCF7 cells lines. The comparison shows good agreement between the systems, with a correlation coefficient of 0.91 and linearity slope of 0.877. We also evaluated the automated size profiles of the microparticle samples. This Wi-Fi-enabled lens-free imaging system, along with the dedicated software, possesses great potential for telemedicine applications in resource-limited settings. PMID:27164146

Design and Efficiency Analysis of Operational Scenarios for Space Situational Awareness Radar System

NASA Astrophysics Data System (ADS)

Choi, E. J.; Cho, S.; Jo, J. H.; Park, J.; Chung, T.; Park, J.; Jeon, H.; Yun, A.; Lee, Y.

In order to perform the surveillance and tracking of space objects, optical and radar sensors are the technical components for space situational awareness system. Especially, space situational awareness radar system in combination with optical sensors network plays an outstanding role for space situational awareness. At present, OWL-Net(Optical Wide Field patrol Network) optical system, which is the only infra structures for tracking of space objects in Korea is very limited in all-weather and observation time. Therefore, the development of radar system capable of continuous operation is becoming an essential space situational awareness element. Therefore, for an efficient space situational awareness at the current state, the strategy of the space situational awareness radar development should be considered. The purpose of this paper is to analyze the efficiency of radar system for detection and tracking of space objects. The detection capabilities are limited to an altitude of 2,000 km with debris size of 1 m2 in radar cross section (RCS) for the radar operating frequencies of L, S, C, X, and Ku-band. The power budget analysis results showed that the maximum detection range of 2,000km can be achieved with the transmitted power of 900 kW, transmit and receive antenna gains of 40 dB and 43 dB, respectively, pulse width of 2 ms, and a signal processing gain of 13.3dB, at frequency of 1.3GHz. The required signal-to-noise ratio (SNR) was assumed to be 12.6 dB for probability of detection of 80% with false alarm rate 10-6. Through the efficiency analysis and trade-off study, the key parameters of the radar system are designed. As a result, this research will provide the guideline for the conceptual design of space situational awareness system.

Object Detection using the Kinect

DTIC Science & Technology

2012-03-01

Kinect camera and point cloud data from the Kinect’s structured light stereo system (figure 1). We obtain reasonable results using a single prototype...same manner we present in this report. For example, at Willow Garage , Steder uses a 3-D feature he developed to classify objects directly from point...detecting backpacks using the data available from the Kinect sensor. 4 3.1 Point Cloud Filtering Dense point clouds derived from stereo are notoriously

History and Evolution of the Johnson Criteria.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sjaardema, Tracy A.; Smith, Collin S.; Birch, Gabriel Carisle

The Johnson Criteria metric calculates probability of detection of an object imaged by an optical system, and was created in 1958 by John Johnson. As understanding of target detection has improved, detection models have evolved to better model additional factors such as weather, scene content, and object placement. The initial Johnson Criteria, while sufficient for technology and understanding at the time, does not accurately reflect current research into target acquisition and technology. Even though current research shows a dependence on human factors, there appears to be a lack of testing and modeling of human variability.

Pattern recognition for passive polarimetric data using nonparametric classifiers

NASA Astrophysics Data System (ADS)

Thilak, Vimal; Saini, Jatinder; Voelz, David G.; Creusere, Charles D.

2005-08-01

Passive polarization based imaging is a useful tool in computer vision and pattern recognition. A passive polarization imaging system forms a polarimetric image from the reflection of ambient light that contains useful information for computer vision tasks such as object detection (classification) and recognition. Applications of polarization based pattern recognition include material classification and automatic shape recognition. In this paper, we present two target detection algorithms for images captured by a passive polarimetric imaging system. The proposed detection algorithms are based on Bayesian decision theory. In these approaches, an object can belong to one of any given number classes and classification involves making decisions that minimize the average probability of making incorrect decisions. This minimum is achieved by assigning an object to the class that maximizes the a posteriori probability. Computing a posteriori probabilities requires estimates of class conditional probability density functions (likelihoods) and prior probabilities. A Probabilistic neural network (PNN), which is a nonparametric method that can compute Bayes optimal boundaries, and a -nearest neighbor (KNN) classifier, is used for density estimation and classification. The proposed algorithms are applied to polarimetric image data gathered in the laboratory with a liquid crystal-based system. The experimental results validate the effectiveness of the above algorithms for target detection from polarimetric data.

Capability of long distance 100  GHz FMCW using a single GDD lamp sensor.

PubMed

Levanon, Assaf; Rozban, Daniel; Aharon Akram, Avihai; Kopeika, Natan S; Yitzhaky, Yitzhak; Abramovich, Amir

2014-12-20

Millimeter wave (MMW)-based imaging systems are required for applications in medicine, homeland security, concealed weapon detection, and space technology. The lack of inexpensive room temperature imaging sensors makes it difficult to provide a suitable MMW system for many of the above applications. A 3D MMW imaging system based on chirp radar was studied previously using a scanning imaging system of a single detector. The radar system requires that the millimeter wave detector will be able to operate as a heterodyne detector. Since the source of radiation is a frequency modulated continuous wave (FMCW), the detected signal as a result of heterodyne detection gives the object's depth information according to value of difference frequency, in addition to the reflectance of the 2D image. New experiments show the capability of long distance FMCW detection by using a large scale Cassegrain projection system, described first (to our knowledge) in this paper. The system presents the capability to employ a long distance of at least 20 m with a low-cost plasma-based glow discharge detector (GDD) focal plane array (FPA). Each point on the object corresponds to a point in the image and includes the distance information. This will enable relatively inexpensive 3D MMW imaging.

WISE Observations of Comets, Centaurs, & Scattered Disk Objects

NASA Technical Reports Server (NTRS)

Bauer, J.; Walker, R.; Mainzer, A.; Masiero, J.; Grav, T.; Cutri, R.; Dailey, J.; McMillan, R.; Lisse, C. M.; Fernandez, Y. R.;

Real-time moving objects detection and tracking from airborne infrared camera

NASA Astrophysics Data System (ADS)

Zingoni, Andrea; Diani, Marco; Corsini, Giovanni

2017-10-01

Detecting and tracking moving objects in real-time from an airborne infrared (IR) camera offers interesting possibilities in video surveillance, remote sensing and computer vision applications, such as monitoring large areas simultaneously, quickly changing the point of view on the scene and pursuing objects of interest. To fully exploit such a potential, versatile solutions are needed, but, in the literature, the majority of them works only under specific conditions about the considered scenario, the characteristics of the moving objects or the aircraft movements. In order to overcome these limitations, we propose a novel approach to the problem, based on the use of a cheap inertial navigation system (INS), mounted on the aircraft. To exploit jointly the information contained in the acquired video sequence and the data provided by the INS, a specific detection and tracking algorithm has been developed. It consists of three main stages performed iteratively on each acquired frame. The detection stage, in which a coarse detection map is computed, using a local statistic both fast to calculate and robust to noise and self-deletion of the targeted objects. The registration stage, in which the position of the detected objects is coherently reported on a common reference frame, by exploiting the INS data. The tracking stage, in which the steady objects are rejected, the moving objects are tracked, and an estimation of their future position is computed, to be used in the subsequent iteration. The algorithm has been tested on a large dataset of simulated IR video sequences, recreating different environments and different movements of the aircraft. Promising results have been obtained, both in terms of detection and false alarm rate, and in terms of accuracy in the estimation of position and velocity of the objects. In addition, for each frame, the detection and tracking map has been generated by the algorithm, before the acquisition of the subsequent frame, proving its capability to work in real-time.

Biophysics of object segmentation in a collision-detecting neuron

PubMed Central

Dewell, Richard Burkett

2018-01-01

Collision avoidance is critical for survival, including in humans, and many species possess visual neurons exquisitely sensitive to objects approaching on a collision course. Here, we demonstrate that a collision-detecting neuron can detect the spatial coherence of a simulated impending object, thereby carrying out a computation akin to object segmentation critical for proper escape behavior. At the cellular level, object segmentation relies on a precise selection of the spatiotemporal pattern of synaptic inputs by dendritic membrane potential-activated channels. One channel type linked to dendritic computations in many neural systems, the hyperpolarization-activated cation channel, HCN, plays a central role in this computation. Pharmacological block of HCN channels abolishes the neuron's spatial selectivity and impairs the generation of visually guided escape behaviors, making it directly relevant to survival. Additionally, our results suggest that the interaction of HCN and inactivating K+ channels within active dendrites produces neuronal and behavioral object specificity by discriminating between complex spatiotemporal synaptic activation patterns. PMID:29667927

Development of a computer-aided detection system for lung cancer diagnosis

NASA Astrophysics Data System (ADS)

Suzuki, Hideo; Inaoka, Noriko; Takabatake, Hirotsugu; Mori, Masaki; Sasaoka, Soichi; Natori, Hiroshi; Suzuki, Akira

1992-06-01

This paper describes a modified system for automatic detection of lung nodules by means of chest x ray image processing techniques. The objective of the system is to help radiologists to improve their accuracy in cancer detection. It is known from retrospective studies of chest x- ray images that radiologists fail to detect about 30 percent of lung cancer cases. A computerized method for detecting lung nodules would be very useful for decreasing the proportion of such oversights. Our proposed system consists of five sub-systems, for image input, lung region determination, nodule detection, rule-based false-positive elimination, and statistical false-positive elimination. In an experiment with the modified system, using 30 lung cancer cases and 78 normal control cases, we obtained figures of 73.3 percent and 89.7 percent for the sensitivity and specificity of the system, respectively. The system has been developed to run on the IBM* PS/55* and IBM RISC System/6000* (RS/6000), and we give the processing time for each platform.

Supporting the Development and Adoption of Automatic Lameness Detection Systems in Dairy Cattle: Effect of System Cost and Performance on Potential Market Shares.

PubMed

Van De Gucht, Tim; Van Weyenberg, Stephanie; Van Nuffel, Annelies; Lauwers, Ludwig; Vangeyte, Jürgen; Saeys, Wouter

2017-10-08

Most automatic lameness detection system prototypes have not yet been commercialized, and are hence not yet adopted in practice. Therefore, the objective of this study was to simulate the effect of detection performance (percentage missed lame cows and percentage false alarms) and system cost on the potential market share of three automatic lameness detection systems relative to visual detection: a system attached to the cow, a walkover system, and a camera system. Simulations were done using a utility model derived from survey responses obtained from dairy farmers in Flanders, Belgium. Overall, systems attached to the cow had the largest market potential, but were still not competitive with visual detection. Increasing the detection performance or lowering the system cost led to higher market shares for automatic systems at the expense of visual detection. The willingness to pay for extra performance was €2.57 per % less missed lame cows, €1.65 per % less false alerts, and €12.7 for lame leg indication, respectively. The presented results could be exploited by system designers to determine the effect of adjustments to the technology on a system's potential adoption rate.

Automatic Reacquisition of Satellite Positions by Detecting Their Expected Streaks in Astronomical Images

NASA Astrophysics Data System (ADS)

Levesque, M.

Artificial satellites, and particularly space junk, drift continuously from their known orbits. In the surveillance-of-space context, they must be observed frequently to ensure that the corresponding orbital parameter database entries are up-to-date. Autonomous ground-based optical systems are periodically tasked to observe these objects, calculate the difference between their predicted and real positions and update object orbital parameters. The real satellite positions are provided by the detection of the satellite streaks in the astronomical images specifically acquired for this purpose. This paper presents the image processing techniques used to detect and extract the satellite positions. The methodology includes several processing steps including: image background estimation and removal, star detection and removal, an iterative matched filter for streak detection, and finally false alarm rejection algorithms. This detection methodology is able to detect very faint objects. Simulated data were used to evaluate the methodology's performance and determine the sensitivity limits where the algorithm can perform detection without false alarm, which is essential to avoid corruption of the orbital parameter database.

Standardized UXO Technology Demonstration Site Scoring Record NO. 934 Technology Type/Platform: EM61 MKII/Towed

DTIC Science & Technology

2009-07-01

nonferrous metallic objects. The applicability of the instrument for ordnance and explosives (OE) detection has been widely demonstrated at sites...was cleared of all metallic items. This clearing of the metallic anomalies from the 2 acre Active Response Demonstration Site was broken into three...with their Multiple Towed Array Detection System (MTADS). This system is known for its effectiveness and ability to detect metallic items. Once the

Experimental evaluation of a system for human life detection under debris

NASA Astrophysics Data System (ADS)

Joju, Reshma; Konica, Pimplapure Ramya T.; Alex, Zachariah C.

2017-11-01

It is difficult to for the human beings to be found under debris or behind the walls in case of military applications. Due to which several rescue techniques such as robotic systems, optical devices, and acoustic devices were used. But if victim was unconscious then these rescue system failed. We conducted an experimental analysis on whether the microwaves could detect heart beat and breathing signals of human beings trapped under collapsed debris. For our analysis we used RADAR based on by Doppler shift effect. We calculated the minimum speed that the RADAR could detect. We checked the frequency variation by placing the RADAR at a fixed position and placing the object in motion at different distances. We checked the frequency variation by using objects of different materials as debris behind which the motion was made. The graphs of different analysis were plotted.

Physical Watermarking for Securing Cyber-Physical Systems via Packet Drop Injections

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ozel, Omur; Weekrakkody, Sean; Sinopoli, Bruno

Physical watermarking is a well known solution for detecting integrity attacks on Cyber-Physical Systems (CPSs) such as the smart grid. Here, a random control input is injected into the system in order to authenticate physical dynamics and sensors which may have been corrupted by adversaries. Packet drops may naturally occur in a CPS due to network imperfections. To our knowledge, previous work has not considered the role of packet drops in detecting integrity attacks. In this paper, we investigate the merit of injecting Bernoulli packet drops into the control inputs sent to actuators as a new physical watermarking scheme. Withmore » the classical linear quadratic objective function and an independent and identically distributed packet drop injection sequence, we study the effect of packet drops on meeting security and control objectives. Our results indicate that the packet drops could act as a potential physical watermark for attack detection in CPSs.« less

GASPS—A Herschel Survey of Gas and Dust in Protoplanetary Disks: Summary and Initial Statistics

NASA Astrophysics Data System (ADS)

Dent, W. R. F.; Thi, W. F.; Kamp, I.; Williams, J. P.; Menard, F.; Andrews, S.; Ardila, D.; Aresu, G.; Augereau, J.-C.; Barrado y Navascues, D.; Brittain, S.; Carmona, A.; Ciardi, D.; Danchi, W.; Donaldson, J.; Duchene, G.; Eiroa, C.; Fedele, D.; Grady, C.; de Gregorio-Molsalvo, I.; Howard, C.; Huélamo, N.; Krivov, A.; Lebreton, J.; Liseau, R.; Martin-Zaidi, C.; Mathews, G.; Meeus, G.; Mendigutía, I.; Montesinos, B.; Morales-Calderon, M.; Mora, A.; Nomura, H.; Pantin, E.; Pascucci, I.; Phillips, N.; Pinte, C.; Podio, L.; Ramsay, S. K.; Riaz, B.; Riviere-Marichalar, P.; Roberge, A.; Sandell, G.; Solano, E.; Tilling, I.; Torrelles, J. M.; Vandenbusche, B.; Vicente, S.; White, G. J.; Woitke, P.

2013-05-01

We describe a large-scale far-infrared line and continuum survey of protoplanetary disk through to young debris disk systems carried out using the ACS instrument on the Herschel Space Observatory. This Open Time Key program, known as GASPS (Gas Survey of Protoplanetary Systems), targeted ~250 young stars in narrow wavelength regions covering the [OI] fine structure line at 63 μm the brightest far-infrared line in such objects. A subset of the brightest targets were also surveyed in [OI]145 μm, [CII] at 157 μm, as well as several transitions of H2O and high-excitation CO lines at selected wavelengths between 78 and 180 μm. Additionally, GASPS included continuum photometry at 70, 100 and 160 μm, around the peak of the dust emission. The targets were SED Class II-III T Tauri stars and debris disks from seven nearby young associations, along with a comparable sample of isolated Herbig AeBe stars. The aim was to study the global gas and dust content in a wide sample of circumstellar disks, combining the results with models in a systematic way. In this overview paper we review the scientific aims, target selection and observing strategy of the program. We summarise some of the initial results, showing line identifications, listing the detections, and giving a first statistical study of line detectability. The [OI] line at 63 μm was the brightest line seen in almost all objects, by a factor of ~10. Overall [OI]63 μm detection rates were 49%, with 100% of HAeBe stars and 43% of T Tauri stars detected. A comparison with published disk dust masses (derived mainly from sub-mm continuum, assuming standard values of the mm mass opacity) shows a dust mass threshold for [OI]63 μm detection of ~10-5 Msolar. Normalising to a distance of 140 pc, 84% of objects with dust masses >=10-5 Msolar can be detected in this line in the present survey; 32% of those of mass 10-6-10-5 Msolar, and only a very small number of unusual objects with lower masses can be detected. This is consistent with models with a moderate UV excess and disk flaring. For a given disk mass, [OI] detectability is lower for M stars compared with earlier spectral types. Both the continuum and line emission was, in most systems, spatially and spectrally unresolved and centred on the star, suggesting that emission in most cases was from the disk. Approximately 10 objects showed resolved emission, most likely from outflows. In the GASPS sample, [OI] detection rates in T Tauri associations in the 0.3-4 Myr age range were ~50%. For each association in the 5-20 Myr age range, ~2 stars remain detectable in [OI]63 μm, and no systems were detected in associations with age >20 Myr. Comparing with the total number of young stars in each association, and assuming a ISM-like gas/dust ratio, this indicates that ~18% of stars retain a gas-rich disk of total mass ~1 MJupiter for 1-4 Myr, 1-7% keep such disks for 5-10 Myr, but none are detected beyond 10-20 Myr. The brightest [OI] objects from GASPS were also observed in [OI]145 μm, [CII]157 μm and CO J = 18 - 17, with detection rates of 20-40%. Detection of the [CII] line was not correlated with disk mass, suggesting it arises more commonly from a compact remnant envelope.

A microsensor for the detection of a single pathogenic bacterium using magnetotactic bacteria-based bio-carriers: simulations and preliminary experiments.

PubMed

Denomme, Ryan C; Lu, Zhao; Martel, Sylvain

2007-01-01

The proposed Magnetotactic Bacteria (MTB) based bio-carrier has the potential to greatly improve pathogenic bacteria detection time, specificity, and sensitivity. Microbeads are attached to the MTB and are modified with a coating of an antibody or phage that is specific to the target pathogenic bacteria. Using magnetic fields, the modified MTB are swept through a solution and the target bacteria present become attached to the microbeads (due to the coating). Then, the MTB are brought to the detection region and the number of pathogenic bacteria is determined. The high swimming speed and controllability of the MTB make this method ideal for the fast detection of small concentrations of specific bacteria. This paper focuses on an impedimetric detection system that will be used to identify if a target bacterium is attached to the microbead. The proposed detection system measures changes in electrical impedance as objects (MTB, microbeads, and pathogenic bacteria) pass through a set of microelectrodes embedded in a microfluidic device. FEM simulation is used to acquire the optimized parameters for the design of such a system. Specifically, factors such as electrode/detection channel geometry, object size and position, which have direct effects on the detection sensitivity for a single bacterium or microparticle, are investigated. Polymer microbeads and the MTB system with an E. coli bacterium are considered to investigate their impedance variations. Furthermore, preliminary experimental data using a microfabricated microfluidic device connected to an impedance analyzer are presented.

Using pattern recognition to automatically localize reflection hyperbolas in data from ground penetrating radar

NASA Astrophysics Data System (ADS)

Maas, Christian; Schmalzl, Jörg

2013-08-01

Ground Penetrating Radar (GPR) is used for the localization of supply lines, land mines, pipes and many other buried objects. These objects can be recognized in the recorded data as reflection hyperbolas with a typical shape depending on depth and material of the object and the surrounding material. To obtain the parameters, the shape of the hyperbola has to be fitted. In the last years several methods were developed to automate this task during post-processing. In this paper we show another approach for the automated localization of reflection hyperbolas in GPR data by solving a pattern recognition problem in grayscale images. In contrast to other methods our detection program is also able to immediately mark potential objects in real-time. For this task we use a version of the Viola-Jones learning algorithm, which is part of the open source library "OpenCV". This algorithm was initially developed for face recognition, but can be adapted to any other simple shape. In our program it is used to narrow down the location of reflection hyperbolas to certain areas in the GPR data. In order to extract the exact location and the velocity of the hyperbolas we apply a simple Hough Transform for hyperbolas. Because the Viola-Jones Algorithm reduces the input for the computational expensive Hough Transform dramatically the detection system can also be implemented on normal field computers, so on-site application is possible. The developed detection system shows promising results and detection rates in unprocessed radargrams. In order to improve the detection results and apply the program to noisy radar images more data of different GPR systems as input for the learning algorithm is necessary.

DDC Systems for Searching for Near-Earth Asteroids

NASA Technical Reports Server (NTRS)

Harris, A.

1994-01-01

Large format CCD systems are superior to photographic systems in terms of quantum efficiency and that they yield digital output directly, which can be computer analyzed to detect moving objects and to obtain astrometric measurements.

Fusion of an Ensemble of Augmented Image Detectors for Robust Object Detection

PubMed Central

Wei, Pan; Anderson, Derek T.

2018-01-01

A significant challenge in object detection is accurate identification of an object’s position in image space, whereas one algorithm with one set of parameters is usually not enough, and the fusion of multiple algorithms and/or parameters can lead to more robust results. Herein, a new computational intelligence fusion approach based on the dynamic analysis of agreement among object detection outputs is proposed. Furthermore, we propose an online versus just in training image augmentation strategy. Experiments comparing the results both with and without fusion are presented. We demonstrate that the augmented and fused combination results are the best, with respect to higher accuracy rates and reduction of outlier influences. The approach is demonstrated in the context of cone, pedestrian and box detection for Advanced Driver Assistance Systems (ADAS) applications. PMID:29562609

Nondestructive testing based on scanning-from-heating approach: application to nonthrough defect detection and fiber orientation assessment

NASA Astrophysics Data System (ADS)

Belkacemi, Mohamed; Stolz, Christophe; Mathieu, Alexandre; Lemaitre, Guillaume; Massich, Joan; Aubreton, Olivier

2015-11-01

Today, industries ensure the quality of their manufactured products through computer vision techniques and nonconventional imaging. Three-dimensional (3-D) scanners and nondestructive testing (NDT) systems are commonly used independently for such applications. Furthermore, these approaches combined constitute hybrid systems, providing a 3-D reconstruction and NDT analysis. These systems, however, suffer from drawbacks such as errors during the data fusion and higher cost for manufacturers. In an attempt to solve these problems, a single active thermography system based on scanning-from-heating is proposed in this paper. In addition to 3-D digitization of the object, our contributions are twofold: (1) the nonthrough defect detection for a homogeneous metallic object and (2) fiber orientation assessment for a long fiber composite material. The experiments on steel and aluminum plates show that our method achieves the detection of nonthrough defects. Additionally, the estimation of the fiber orientation is evaluated on carbon-fiber composite material.

Testing of Hand-Held Mine Detection Systems

DTIC Science & Technology

2015-01-08

ITOP 04-2-5208 for guidance on software testing . Testing software is necessary to ensure that safety is designed into the software algorithm, and that...sensor verification areas or target lanes. F.2. TESTING OBJECTIVES. a. Testing objectives will impact on the test design . Some examples of...overall safety, performance, and reliability of the system. It describes activities necessary to ensure safety is designed into the system under test

Edge detection

NASA Astrophysics Data System (ADS)

Hildreth, E. C.

1985-09-01

For both biological systems and machines, vision begins with a large and unwieldly array of measurements of the amount of light reflected from surfaces in the environment. The goal of vision is to recover physical properties of objects in the scene such as the location of object boundaries and the structure, color and texture of object surfaces, from the two-dimensional image that is projected onto the eye or camera. This goal is not achieved in a single step: vision proceeds in stages, with each stage producing increasingly more useful descriptions of the image and then the scene. The first clues about the physical properties of the scene are provided by the changes of intensity in the image. The importance of intensity changes and edges in early visual processing has led to extensive research on their detection, description and use, both in computer and biological vision systems. This article reviews some of the theory that underlies the detection of edges, and the methods used to carry out this analysis.

Automatic landslide detection from LiDAR DTM derivatives by geographic-object-based image analysis based on open-source software

NASA Astrophysics Data System (ADS)

Knevels, Raphael; Leopold, Philip; Petschko, Helene

2017-04-01

With high-resolution airborne Light Detection and Ranging (LiDAR) data more commonly available, many studies have been performed to facilitate the detailed information on the earth surface and to analyse its limitation. Specifically in the field of natural hazards, digital terrain models (DTM) have been used to map hazardous processes such as landslides mainly by visual interpretation of LiDAR DTM derivatives. However, new approaches are striving towards automatic detection of landslides to speed up the process of generating landslide inventories. These studies usually use a combination of optical imagery and terrain data, and are designed in commercial software packages such as ESRI ArcGIS, Definiens eCognition, or MathWorks MATLAB. The objective of this study was to investigate the potential of open-source software for automatic landslide detection based only on high-resolution LiDAR DTM derivatives in a study area within the federal state of Burgenland, Austria. The study area is very prone to landslides which have been mapped with different methodologies in recent years. The free development environment R was used to integrate open-source geographic information system (GIS) software, such as SAGA (System for Automated Geoscientific Analyses), GRASS (Geographic Resources Analysis Support System), or TauDEM (Terrain Analysis Using Digital Elevation Models). The implemented geographic-object-based image analysis (GEOBIA) consisted of (1) derivation of land surface parameters, such as slope, surface roughness, curvature, or flow direction, (2) finding optimal scale parameter by the use of an objective function, (3) multi-scale segmentation, (4) classification of landslide parts (main scarp, body, flanks) by k-mean thresholding, (5) assessment of the classification performance using a pre-existing landslide inventory, and (6) post-processing analysis for the further use in landslide inventories. The results of the developed open-source approach demonstrated good success rates to objectively detect landslides in high-resolution topography data by GEOBIA.

Commissioning and field tests of a van-mounted system for the detection of radioactive sources and Special Nuclear Material

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cester, D.; Lunardon, M.; Stevanato, L.

2015-07-01

MODES SNM project aimed to carry out technical research in order to develop a prototype for a mobile, modular detection system for radioactive sources and Special Nuclear Materials (SNM). Its main goal was to deliver a tested prototype of a modular mobile system capable of passively detecting weak or shielded radioactive sources with accuracy higher than that of currently available systems. By the end of the project all the objectives have been successfully achieved. Results from the laboratory commissioning and the field tests will be presented. (authors)

Biological object recognition in μ-radiography images

NASA Astrophysics Data System (ADS)

Prochazka, A.; Dammer, J.; Weyda, F.; Sopko, V.; Benes, J.; Zeman, J.; Jandejsek, I.

2015-03-01

This study presents an applicability of real-time microradiography to biological objects, namely to horse chestnut leafminer, Cameraria ohridella (Insecta: Lepidoptera, Gracillariidae) and following image processing focusing on image segmentation and object recognition. The microradiography of insects (such as horse chestnut leafminer) provides a non-invasive imaging that leaves the organisms alive. The imaging requires a high spatial resolution (micrometer scale) radiographic system. Our radiographic system consists of a micro-focus X-ray tube and two types of detectors. The first is a charge integrating detector (Hamamatsu flat panel), the second is a pixel semiconductor detector (Medipix2 detector). The latter allows detection of single quantum photon of ionizing radiation. We obtained numerous horse chestnuts leafminer pupae in several microradiography images easy recognizable in automatic mode using the image processing methods. We implemented an algorithm that is able to count a number of dead and alive pupae in images. The algorithm was based on two methods: 1) noise reduction using mathematical morphology filters, 2) Canny edge detection. The accuracy of the algorithm is higher for the Medipix2 (average recall for detection of alive pupae =0.99, average recall for detection of dead pupae =0.83), than for the flat panel (average recall for detection of alive pupae =0.99, average recall for detection of dead pupae =0.77). Therefore, we conclude that Medipix2 has lower noise and better displays contours (edges) of biological objects. Our method allows automatic selection and calculation of dead and alive chestnut leafminer pupae. It leads to faster monitoring of the population of one of the world's important insect pest.

Slip detection with accelerometer and tactile sensors in a robotic hand model

NASA Astrophysics Data System (ADS)

Al-Shanoon, Abdulrahman Abdulkareem S.; Anom Ahmad, Siti; Hassan, Mohd. Khair b.

2015-11-01

Grasp planning is an interesting issue in studies that dedicated efforts to investigate tactile sensors. This study investigated the physical force interaction between a tactile pressure sensor and a particular object. It also characterized object slipping during gripping operations and presented secure regripping of an object. Acceleration force was analyzed using an accelerometer sensor to establish a completely autonomous robotic hand model. An automatic feedback control system was applied to regrip the particular object when it commences to slip. Empirical findings were presented in consideration of the detection and subsequent control of the slippage situation. These findings revealed the correlation between the distance of the object slipping and the required force to regrip the object safely. This approach is similar to Hooke's law formula.

A group filter algorithm for sea mine detection

NASA Astrophysics Data System (ADS)

Cobb, J. Tory; An, Myoung; Tolimieri, Richard

2005-06-01

Automatic detection of sea mines in coastal regions is a difficult task due to the highly variable sea bottom conditions present in the underwater environment. Detection systems must be able to discriminate objects which vary in size, shape, and orientation from naturally occurring and man-made clutter. Additionally, these automated systems must be computationally efficient to be incorporated into unmanned underwater vehicle (UUV) sensor systems characterized by high sensor data rates and limited processing abilities. Using noncommutative group harmonic analysis, a fast, robust sea mine detection system is created. A family of unitary image transforms associated to noncommutative groups is generated and applied to side scan sonar image files supplied by Naval Surface Warfare Center Panama City (NSWC PC). These transforms project key image features, geometrically defined structures with orientations, and localized spectral information into distinct orthogonal components or feature subspaces of the image. The performance of the detection system is compared against the performance of an independent detection system in terms of probability of detection (Pd) and probability of false alarm (Pfa).

Aircraft Engine On-Line Diagnostics Through Dual-Channel Sensor Measurements: Development of a Baseline System

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2008-01-01

In this paper, a baseline system which utilizes dual-channel sensor measurements for aircraft engine on-line diagnostics is developed. This system is composed of a linear on-board engine model (LOBEM) and fault detection and isolation (FDI) logic. The LOBEM provides the analytical third channel against which the dual-channel measurements are compared. When the discrepancy among the triplex channels exceeds a tolerance level, the FDI logic determines the cause of the discrepancy. Through this approach, the baseline system achieves the following objectives: (1) anomaly detection, (2) component fault detection, and (3) sensor fault detection and isolation. The performance of the baseline system is evaluated in a simulation environment using faults in sensors and components.

Parallel computation of level set method for 500 Hz visual servo control

NASA Astrophysics Data System (ADS)

Fei, Xianfeng; Igarashi, Yasunobu; Hashimoto, Koichi

2008-11-01

We propose a 2D microorganism tracking system using a parallel level set method and a column parallel vision system (CPV). This system keeps a single microorganism in the middle of the visual field under a microscope by visual servoing an automated stage. We propose a new energy function for the level set method. This function constrains an amount of light intensity inside the detected object contour to control the number of the detected objects. This algorithm is implemented in CPV system and computational time for each frame is 2 [ms], approximately. A tracking experiment for about 25 s is demonstrated. Also we demonstrate a single paramecium can be kept tracking even if other paramecia appear in the visual field and contact with the tracked paramecium.

Nanosatellite Maneuver Planning for Point Cloud Generation With a Rangefinder

DTIC Science & Technology

2015-06-05

aided active vision systems [11], dense stereo [12], and TriDAR [13]. However, these systems are unsuitable for a nanosatellite system from power, size...command profiles as well as improving the fidelity of gap detection with better filtering methods for background objects . For example, attitude...application of a single beam laser rangefinder (LRF) to point cloud generation, shape detection , and shape reconstruction for a space-based space

Particle detection systems and methods

DOEpatents

Morris, Christopher L.; Makela, Mark F.

2010-05-11

Techniques, apparatus and systems for detecting particles such as muons and neutrons. In one implementation, a particle detection system employs a plurality of drift cells, which can be for example sealed gas-filled drift tubes, arranged on sides of a volume to be scanned to track incoming and outgoing charged particles, such as cosmic ray-produced muons. The drift cells can include a neutron sensitive medium to enable concurrent counting of neutrons. The system can selectively detect devices or materials, such as iron, lead, gold, uranium, plutonium, and/or tungsten, occupying the volume from multiple scattering of the charged particles passing through the volume and can concurrently detect any unshielded neutron sources occupying the volume from neutrons emitted therefrom. If necessary, the drift cells can be used to also detect gamma rays. The system can be employed to inspect occupied vehicles at border crossings for nuclear threat objects.

Multispectral THz-VIS passive imaging system for hidden threats visualization

NASA Astrophysics Data System (ADS)

Kowalski, Marcin; Palka, Norbert; Szustakowski, Mieczyslaw

2013-10-01

Terahertz imaging, is the latest entry into the crowded field of imaging technologies. Many applications are emerging for the relatively new technology. THz radiation penetrates deep into nonpolar and nonmetallic materials such as paper, plastic, clothes, wood, and ceramics that are usually opaque at optical wavelengths. The T-rays have large potential in the field of hidden objects detection because it is not harmful to humans. The main difficulty in the THz imaging systems is low image quality thus it is justified to combine THz images with the high-resolution images from a visible camera. An imaging system is usually composed of various subsystems. Many of the imaging systems use imaging devices working in various spectral ranges. Our goal is to build a system harmless to humans for screening and detection of hidden objects using a THz and VIS cameras.

Unmanned Aircraft Systems (UAS) Sensor and Targeting

DTIC Science & Technology

2010-07-27

4.7.1 Objective. The objective of this subtest is to determine the detection performance of the Synthetic Aperture Radar (SAR) with the radar...Detection SAR – Synthetic Aperture Radar 4.7.3 Data Required. Section 5.1 outlines general test data required. The following additional data may...m – meter No. – Number PC – Probability of Classification SAR – Synthetic Aperture Radar 4.8.3 Data Required. Section 5.1 outlines

Relative Navigation Light Detection and Ranging (LIDAR) Sensor Development Test Objective (DTO) Performance Verification

NASA Technical Reports Server (NTRS)

Dennehy, Cornelius J.

2013-01-01

The NASA Engineering and Safety Center (NESC) received a request from the NASA Associate Administrator (AA) for Human Exploration and Operations Mission Directorate (HEOMD), to quantitatively evaluate the individual performance of three light detection and ranging (LIDAR) rendezvous sensors flown as orbiter's development test objective on Space Transportation System (STS)-127, STS-133, STS-134, and STS-135. This document contains the outcome of the NESC assessment.

Real-time detection of moving objects from moving vehicles using dense stereo and optical flow

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2004-01-01

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time, dense stereo system to include realtime, dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identify & other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6-DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop, computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

Real-time detection of moving objects from moving vehicles using dense stereo and optical flow

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2004-01-01

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time, dense stereo system to include real-time, dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identity other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6-DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop, computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

Real-time Detection of Moving Objects from Moving Vehicles Using Dense Stereo and Optical Flow

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2004-01-01

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time. dense stereo system to include realtime. dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identify other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop. computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

Two-view information fusion for improvement of computer-aided detection (CAD) of breast masses on mammograms

NASA Astrophysics Data System (ADS)

Wei, Jun; Sahiner, Berkman; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Helvie, Mark A.; Roubidoux, Marilyn A.; Zhou, Chuan; Ge, Jun; Zhang, Yiheng

2006-03-01

We are developing a two-view information fusion method to improve the performance of our CAD system for mass detection. Mass candidates on each mammogram were first detected with our single-view CAD system. Potential object pairs on the two-view mammograms were then identified by using the distance between the object and the nipple. Morphological features, Hessian feature, correlation coefficients between the two paired objects and texture features were used as input to train a similarity classifier that estimated a similarity scores for each pair. Finally, a linear discriminant analysis (LDA) classifier was used to fuse the score from the single-view CAD system and the similarity score. A data set of 475 patients containing 972 mammograms with 475 biopsy-proven masses was used to train and test the CAD system. All cases contained the CC view and the MLO or LM view. We randomly divided the data set into two independent sets of 243 cases and 232 cases. The training and testing were performed using the 2-fold cross validation method. The detection performance of the CAD system was assessed by free response receiver operating characteristic (FROC) analysis. The average test FROC curve was obtained from averaging the FP rates at the same sensitivity along the two corresponding test FROC curves from the 2-fold cross validation. At the case-based sensitivities of 90%, 85% and 80% on the test set, the single-view CAD system achieved an FP rate of 2.0, 1.5, and 1.2 FPs/image, respectively. With the two-view fusion system, the FP rates were reduced to 1.7, 1.3, and 1.0 FPs/image, respectively, at the corresponding sensitivities. The improvement was found to be statistically significant (p<0.05) by the AFROC method. Our results indicate that the two-view fusion scheme can improve the performance of mass detection on mammograms.

Data fusion concept in multispectral system for perimeter protection of stationary and moving objects

NASA Astrophysics Data System (ADS)

Ciurapiński, Wieslaw; Dulski, Rafal; Kastek, Mariusz; Szustakowski, Mieczyslaw; Bieszczad, Grzegorz; Życzkowski, Marek; Trzaskawka, Piotr; Piszczek, Marek

2009-09-01

The paper presents the concept of multispectral protection system for perimeter protection for stationary and moving objects. The system consists of active ground radar, thermal and visible cameras. The radar allows the system to locate potential intruders and to control an observation area for system cameras. The multisensor construction of the system ensures significant improvement of detection probability of intruder and reduction of false alarms. A final decision from system is worked out using image data. The method of data fusion used in the system has been presented. The system is working under control of FLIR Nexus system. The Nexus offers complete technology and components to create network-based, high-end integrated systems for security and surveillance applications. Based on unique "plug and play" architecture, system provides unmatched flexibility and simplistic integration of sensors and devices in TCP/IP networks. Using a graphical user interface it is possible to control sensors and monitor streaming video and other data over the network, visualize the results of data fusion process and obtain detailed information about detected intruders over a digital map. System provides high-level applications and operator workload reduction with features such as sensor to sensor cueing from detection devices, automatic e-mail notification and alarm triggering.

Detection and Classification of Pole-Like Objects from Mobile Mapping Data

NASA Astrophysics Data System (ADS)

Fukano, K.; Masuda, H.

2015-08-01

Laser scanners on a vehicle-based mobile mapping system can capture 3D point-clouds of roads and roadside objects. Since roadside objects have to be maintained periodically, their 3D models are useful for planning maintenance tasks. In our previous work, we proposed a method for detecting cylindrical poles and planar plates in a point-cloud. However, it is often required to further classify pole-like objects into utility poles, streetlights, traffic signals and signs, which are managed by different organizations. In addition, our previous method may fail to extract low pole-like objects, which are often observed in urban residential areas. In this paper, we propose new methods for extracting and classifying pole-like objects. In our method, we robustly extract a wide variety of poles by converting point-clouds into wireframe models and calculating cross-sections between wireframe models and horizontal cutting planes. For classifying pole-like objects, we subdivide a pole-like object into five subsets by extracting poles and planes, and calculate feature values of each subset. Then we apply a supervised machine learning method using feature variables of subsets. In our experiments, our method could achieve excellent results for detection and classification of pole-like objects.

Communications and tracking expert systems study

NASA Technical Reports Server (NTRS)

Leibfried, T. F.; Feagin, Terry; Overland, David

1987-01-01

The original objectives of the study consisted of five broad areas of investigation: criteria and issues for explanation of communication and tracking system anomaly detection, isolation, and recovery; data storage simplification issues for fault detection expert systems; data selection procedures for decision tree pruning and optimization to enhance the abstraction of pertinent information for clear explanation; criteria for establishing levels of explanation suited to needs; and analysis of expert system interaction and modularization. Progress was made in all areas, but to a lesser extent in the criteria for establishing levels of explanation suited to needs. Among the types of expert systems studied were those related to anomaly or fault detection, isolation, and recovery.

The Feasibility and Benefits of In Situ Exploration of ‘Oumuamua-like Objects

NASA Astrophysics Data System (ADS)

Seligman, Darryl; Laughlin, Gregory

2018-05-01

A rapid accumulation of observations and interpretation has followed in the wake of 1I ‘Oumuamua’s passage through the inner solar system. We briefly outline the consequences that this first detection of an interstellar asteroid implies for the planet-forming process, and we assess the near-term prospects for detecting and observing (both remotely and in situ) future solar system visitors of this type. Drawing on detailed heat-transfer calculations that take both ‘Oumuamua’s unusual shape and its chaotic tumbling into account, we affirm that the lack of a detectable coma in deep images of the object very likely arises from the presence of a radiation-modified coating of high molecular weight material (rather than a refractory bulk composition). Assuming that ‘Oumuamua is a typical representative of a larger population with a kinematic distribution similar to Population I stars in the local galactic neighborhood, we calculate expected arrival rates, impact parameters, and velocities of similar objects and assess their prospects for detection using operational and forthcoming facilities. Using ‘Oumuamua as a proof of concept, we assess the prospects for missions that intercept interstellar objects using conventional chemical propulsion. Using a “launch on detection” paradigm, we estimate wait times of order of 10 years between favorable mission opportunities with the detection capabilities of the Large-scale Synoptic Survey Telescope, a figure that will be refined as the population of interstellar asteroids becomes observationally better constrained.

Research on the system scheme and experiment for the active laser polarization imaging

NASA Astrophysics Data System (ADS)

Fu, Qiang; Duan, Jin; Zhao, Rui; Li, Zheng; Zhang, Su; Zhan, Juntong; Zhu, Yong; Jiang, Hui-Lin

2015-10-01

The polarization imaging detection technology increased the polarization information on the basis of the intensity imaging, which is extensive application in the military and civil and other fields. The research present and development trend of polarization imaging detection technology was introduce, the system scheme of the active polarization imaging detection was put forward, and the key technologies such as the polarization information detection, optical system design, polarization radiation calibration and image fusion approach was analyzed. On this basis, detection system by existing equipment of laboratory was set up, and on the different materials such as wood, metal, plastic and goal was detected by polarization imaging to realize the active polarization imaging detection. The results show that image contrast of the metal and man-made objects is higher, the polarization effect is better, which provided the basis on the better performance of the polarization imaging instruments.

Human care system for heart-rate and human-movement trajectory in home and its application to detect mental disease

NASA Astrophysics Data System (ADS)

Hata, Yutaka; Kanazawa, Seigo; Endo, Maki; Tsuchiya, Naoki; Nakajima, Hiroshi

2012-06-01

This paper proposes a heart rate monitoring system for detecting autonomic nervous system by the heart rate variability using an air pressure sensor to diagnose mental disease. Moreover, we propose a human behavior monitoring system for detecting the human trajectory in home by an infrared camera. In day and night times, the human behavior monitoring system detects the human movement in home. The heart rate monitoring system detects the heart rate in bed in night time. The air pressure sensor consists of a rubber tube, cushion cover and pressure sensor, and it detects the heart rate by setting it to bed. It unconstraintly detects the RR-intervals; thereby the autonomic nervous system can be assessed. The autonomic nervous system analysis can examine the mental disease. While, the human behavior monitoring system obtains distance distribution image by an infrared camera. It classifies adult, child and the other object from distance distribution obtained by the camera, and records their trajectories. This behavior, i.e., trajectory in home, strongly corresponds to cognitive disorders. Thus, the total system can detect mental disease and cognitive disorders by uncontacted sensors to human body.

Performance Analysis of Sensor Systems for Space Situational Awareness

NASA Astrophysics Data System (ADS)

Choi, Eun-Jung; Cho, Sungki; Jo, Jung Hyun; Park, Jang-Hyun; Chung, Taejin; Park, Jaewoo; Jeon, Hocheol; Yun, Ami; Lee, Yonghui

2017-12-01

With increased human activity in space, the risk of re-entry and collision between space objects is constantly increasing. Hence, the need for space situational awareness (SSA) programs has been acknowledged by many experienced space agencies. Optical and radar sensors, which enable the surveillance and tracking of space objects, are the most important technical components of SSA systems. In particular, combinations of radar systems and optical sensor networks play an outstanding role in SSA programs. At present, Korea operates the optical wide field patrol network (OWL-Net), the only optical system for tracking space objects. However, due to their dependence on weather conditions and observation time, it is not reasonable to use optical systems alone for SSA initiatives, as they have limited operational availability. Therefore, the strategies for developing radar systems should be considered for an efficient SSA system using currently available technology. The purpose of this paper is to analyze the performance of a radar system in detecting and tracking space objects. With the radar system investigated, the minimum sensitivity is defined as detection of a 1-m2 radar cross section (RCS) at an altitude of 2,000 km, with operating frequencies in the L, S, C, X or Ku-band. The results of power budget analysis showed that the maximum detection range of 2,000 km, which includes the low earth orbit (LEO) environment, can be achieved with a transmission power of 900 kW, transmit and receive antenna gains of 40 dB and 43 dB, respectively, a pulse width of 2 ms, and a signal processing gain of 13.3 dB, at a frequency of 1.3 GHz. We defined the key parameters of the radar following a performance analysis of the system. This research can thus provide guidelines for the conceptual design of radar systems for national SSA initiatives.

Automatic detection of red lesions in digital color fundus photographs.

PubMed

Niemeijer, Meindert; van Ginneken, Bram; Staal, Joes; Suttorp-Schulten, Maria S A; Abràmoff, Michael D

2005-05-01

The robust detection of red lesions in digital color fundus photographs is a critical step in the development of automated screening systems for diabetic retinopathy. In this paper, a novel red lesion detection method is presented based on a hybrid approach, combining prior works by Spencer et al. (1996) and Frame et al. (1998) with two important new contributions. The first contribution is a new red lesion candidate detection system based on pixel classification. Using this technique, vasculature and red lesions are separated from the background of the image. After removal of the connected vasculature the remaining objects are considered possible red lesions. Second, an extensive number of new features are added to those proposed by Spencer-Frame. The detected candidate objects are classified using all features and a k-nearest neighbor classifier. An extensive evaluation was performed on a test set composed of images representative of those normally found in a screening set. When determining whether an image contains red lesions the system achieves a sensitivity of 100% at a specificity of 87%. The method is compared with several different automatic systems and is shown to outperform them all. Performance is close to that of a human expert examining the images for the presence of red lesions.

Increased Fire and Toxic Contaminant Detection Responsibility by Use of Distributed, Aspirating Sensors

NASA Technical Reports Server (NTRS)

Youngblood, Wallace W.

1990-01-01

Viewgraphs of increased fire and toxic contaminant detection responsivity by use of distributed, aspirating sensors for space station are presented. Objectives of the concept described are (1) to enhance fire and toxic contaminant detection responsivity in habitable regions of space station; (2) to reduce system weight and complexity through centralized detector/monitor systems; (3) to increase fire signature information from selected locations in a space station module; and (4) to reduce false alarms.

The Feasibility and Benefits of In Situ Exploration of `Oumuamua-like objects

NASA Astrophysics Data System (ADS)

Seligman, Darryl; Laughlin, Gregory

2018-04-01

A rapid accumulation of observations and interpretation have followed in the wake of 1I `Oumuamua's passage through the inner Solar System. We outline the consequences that this first detection of an interstellar asteroid implies for the planet-forming process, and we assess the near-term prospects for detecting and observing (both remotely and \\textit{in situ}) future Solar System visitors of this type. Drawing on detailed heat-transfer calculations that take both `Oumuamua's unusual shape and its chaotic tumbling into account, we affirm that the lack of a detectable coma in deep images of the object very likely arises from the presence of a radiation-modified coating of high molecular weight material (rather than a refractory bulk composition). Assuming that `Oumuamua is a typical representative of a larger population with a kinematic distribution similar to Population I stars in the local galactic neighborhood, we calculate expected arrival rates, impact parameters and velocities of similar objects and assess their prospects for detection using operational and forthcoming facilities. Using `Oumuamua as a proof-of-concept, we assess the prospects for missions that intercept ISOs using conventional chemical propulsion. Using a ``launch on detection'' paradigm, we estimate wait times of order a year between favorable mission opportunities with the detection capabilities of the Large-Scale Synoptic Survey Telescope (LSST), a figure that will be refined as the population of interstellar asteroids becomes observationally better constrained.

Nondestructive Crack Detection in a Fuel System Component

NASA Technical Reports Server (NTRS)

Koshti, Ajay; Ruffino, Norman; Wincheski, Russell; Prosser, William; Winfree, William; Russell, Richard; Bryson, Craig; Devries, Robert; Engel, James; Landy, James

2010-01-01

The presentation examines the background and objective of nondestructive crack detection, flow control valve assembly and poppet post flight evaluation, poppet properties. magnetic property characterization of lab data, NDE, eddy current inspection, simulation, eddy current criteria, poppet cycle testing and NDE criteria, and the use of ultrasonic surface wave for crack detection.

Relative Saliency in Change Signals Affects Perceptual Comparison and Decision Processes in Change Detection

ERIC Educational Resources Information Center

Yang, Cheng-Ta

2011-01-01

Change detection requires perceptual comparison and decision processes on different features of multiattribute objects. How relative salience between two feature-changes influences the processes has not been addressed. This study used the systems factorial technology to investigate the processes when detecting changes in a Gabor patch with visual…

Parametric boundary reconstruction algorithm for industrial CT metrology application.

PubMed

Yin, Zhye; Khare, Kedar; De Man, Bruno

2009-01-01

High-energy X-ray computed tomography (CT) systems have been recently used to produce high-resolution images in various nondestructive testing and evaluation (NDT/NDE) applications. The accuracy of the dimensional information extracted from CT images is rapidly approaching the accuracy achieved with a coordinate measuring machine (CMM), the conventional approach to acquire the metrology information directly. On the other hand, CT systems generate the sinogram which is transformed mathematically to the pixel-based images. The dimensional information of the scanned object is extracted later by performing edge detection on reconstructed CT images. The dimensional accuracy of this approach is limited by the grid size of the pixel-based representation of CT images since the edge detection is performed on the pixel grid. Moreover, reconstructed CT images usually display various artifacts due to the underlying physical process and resulting object boundaries from the edge detection fail to represent the true boundaries of the scanned object. In this paper, a novel algorithm to reconstruct the boundaries of an object with uniform material composition and uniform density is presented. There are three major benefits in the proposed approach. First, since the boundary parameters are reconstructed instead of image pixels, the complexity of the reconstruction algorithm is significantly reduced. The iterative approach, which can be computationally intensive, will be practical with the parametric boundary reconstruction. Second, the object of interest in metrology can be represented more directly and accurately by the boundary parameters instead of the image pixels. By eliminating the extra edge detection step, the overall dimensional accuracy and process time can be improved. Third, since the parametric reconstruction approach shares the boundary representation with other conventional metrology modalities such as CMM, boundary information from other modalities can be directly incorporated as prior knowledge to improve the convergence of an iterative approach. In this paper, the feasibility of parametric boundary reconstruction algorithm is demonstrated with both simple and complex simulated objects. Finally, the proposed algorithm is applied to the experimental industrial CT system data.

Automated multiple target detection and tracking in UAV videos

NASA Astrophysics Data System (ADS)

Mao, Hongwei; Yang, Chenhui; Abousleman, Glen P.; Si, Jennie

2010-04-01

In this paper, a novel system is presented to detect and track multiple targets in Unmanned Air Vehicles (UAV) video sequences. Since the output of the system is based on target motion, we first segment foreground moving areas from the background in each video frame using background subtraction. To stabilize the video, a multi-point-descriptor-based image registration method is performed where a projective model is employed to describe the global transformation between frames. For each detected foreground blob, an object model is used to describe its appearance and motion information. Rather than immediately classifying the detected objects as targets, we track them for a certain period of time and only those with qualified motion patterns are labeled as targets. In the subsequent tracking process, a Kalman filter is assigned to each tracked target to dynamically estimate its position in each frame. Blobs detected at a later time are used as observations to update the state of the tracked targets to which they are associated. The proposed overlap-rate-based data association method considers the splitting and merging of the observations, and therefore is able to maintain tracks more consistently. Experimental results demonstrate that the system performs well on real-world UAV video sequences. Moreover, careful consideration given to each component in the system has made the proposed system feasible for real-time applications.

Flight elements: Fault detection and fault management

NASA Technical Reports Server (NTRS)

Lum, H.; Patterson-Hine, A.; Edge, J. T.; Lawler, D.

1990-01-01

Fault management for an intelligent computational system must be developed using a top down integrated engineering approach. An approach proposed includes integrating the overall environment involving sensors and their associated data; design knowledge capture; operations; fault detection, identification, and reconfiguration; testability; causal models including digraph matrix analysis; and overall performance impacts on the hardware and software architecture. Implementation of the concept to achieve a real time intelligent fault detection and management system will be accomplished via the implementation of several objectives, which are: Development of fault tolerant/FDIR requirement and specification from a systems level which will carry through from conceptual design through implementation and mission operations; Implementation of monitoring, diagnosis, and reconfiguration at all system levels providing fault isolation and system integration; Optimize system operations to manage degraded system performance through system integration; and Lower development and operations costs through the implementation of an intelligent real time fault detection and fault management system and an information management system.

Two objects in Neptune's 9:1 resonance -- implications for resonance sticking in the scattering population

NASA Astrophysics Data System (ADS)

Volk, Kathryn; Murray-Clay, Ruth; Gladman, Brett; Lawler, Samantha; Yu, Tze Yeung Mathew; Alexandersen, Mike; Bannister, Michele; Chen, Ying-Yung; Dawson, Rebekah; Greenstreet, Sarah; Gwyn, Stephen; Kavelaars, J. J.; Lin, Hsing Wen; Lykawka, Patryk; Petit, Jean-Marc

2018-04-01

We discuss the detection in the Outer Solar System Origins Survey (OSSOS) of two objects in Neptune's distant 9:1 mean motion resonance at semimajor axis a≈130 au. Both objects are securely resonant on 10 Myr timescales, with one securely in the 9:1 resonance's leading asymmetric libration island and the other in either the symmetric or trailing asymmetric island. These two objects are the largest semimajor axis objects known with secure resonant classifications, and their detection in a carefully characterized survey allows for the first robust population estimate for a resonance beyond 100 au. The detection of these two objects implies a population in the 9:1 resonance of 1.1×104 objects with Hr<8.66 (D > 100 km) on similar orbits, with 95% confidence range of ∼0.4‑3×104. Integrations over 4 Gyr of an ensemble of clones chosen from within the orbit fit uncertainties for these objects reveal that they both have median resonance occupation timescales of ∼1 Gyr. These timescales are consistent with the hypothesis that these two objects originate in the scattering population but became transiently stuck to Neptune's 9:1 resonance within the last ∼1 Gyr of solar system evolution. Based on simulations of a model of the current scattering population, we estimate the expected resonance sticking population in the 9:1 resonance to be 1000--5000 objects with Hr<8.66 this is marginally consistent with the OSSOS 9:1 population estimate. We conclude that resonance sticking is a plausible explanation for the observed 9:1 population, but we also discuss the possibility of a primordial 9:1 population, which would have interesting implications for the Kuiper belt's dynamical history.

Laser beam monitoring system

DOEpatents

Weil, Bradley S.; Wetherington, Jr., Grady R.

1985-01-01

Laser beam monitoring systems include laser-transparent plates set at an angle to the laser beam passing therethrough and light sensor for detecting light reflected from an object on which the laser beam impinges.

Laser beam monitoring system

DOEpatents

Weil, B.S.; Wetherington, G.R. Jr.

Laser beam monitoring systems include laser-transparent plates set at an angle to the laser beam passing therethrough and light sensor for detecting light reflected from an object on which the laser beam impinges.

Space imaging infrared optical guidance for autonomous ground vehicle

NASA Astrophysics Data System (ADS)

Akiyama, Akira; Kobayashi, Nobuaki; Mutoh, Eiichiro; Kumagai, Hideo; Yamada, Hirofumi; Ishii, Hiromitsu

2008-08-01

We have developed the Space Imaging Infrared Optical Guidance for Autonomous Ground Vehicle based on the uncooled infrared camera and focusing technique to detect the objects to be evaded and to set the drive path. For this purpose we made servomotor drive system to control the focus function of the infrared camera lens. To determine the best focus position we use the auto focus image processing of Daubechies wavelet transform technique with 4 terms. From the determined best focus position we transformed it to the distance of the object. We made the aluminum frame ground vehicle to mount the auto focus infrared unit. Its size is 900mm long and 800mm wide. This vehicle mounted Ackerman front steering system and the rear motor drive system. To confirm the guidance ability of the Space Imaging Infrared Optical Guidance for Autonomous Ground Vehicle we had the experiments for the detection ability of the infrared auto focus unit to the actual car on the road and the roadside wall. As a result the auto focus image processing based on the Daubechies wavelet transform technique detects the best focus image clearly and give the depth of the object from the infrared camera unit.

Studies of the field-of-view resolution tradeoff in virtual-reality systems

NASA Technical Reports Server (NTRS)

Piantanida, Thomas P.; Boman, Duane; Larimer, James; Gille, Jennifer; Reed, Charles

1992-01-01

Most virtual-reality systems use LCD-based displays that achieve a large field-of-view at the expense of resolution. A typical display will consist of approximately 86,000 pixels uniformly distributed over an 80-degree by 60-degree image. Thus, each pixel subtends about 13 minutes of arc at the retina; about the same as the resolvable features of the 20/200 line of a Snellen Eye Chart. The low resolution of LCD-based systems limits task performance in some applications. We have examined target-detection performance in a low-resolution virtual world. Our synthesized three-dimensional virtual worlds consisted of target objects that could be positioned at a fixed distance from the viewer, but at random azimuth and constrained elevation. A virtual world could be bounded by chromatic walls or by wire-frame, or it could be unbounded. Viewers scanned these worlds and indicated by appropriate gestures when they had detected the target object. By manipulating the viewer's field size and the chromatic and luminance contrast of annuli surrounding the field-of-view, we were able to assess the effect of field size on the detection of virtual objects in low-resolution synthetic worlds.

Target recognition in passive terahertz image of human body

NASA Astrophysics Data System (ADS)

Zhao, Ran; Zhao, Yuan-meng; Deng, Chao; Zhang, Cun-lin; Li, Yue

2014-11-01

THz radiation can penetrate through many nonpolar dielectric materials and can be used for nondestructive/noninvasive sensing and imaging of targets under nonpolar, nonmetallic covers or containers. Thus using THz systems to "see through" concealing barriers (i.e. packaging, corrugated cardboard, clothing) has been proposed as a new security screening method. Objects that can be detected by THz include concealed weapons, explosives, and chemical agents under clothing. Passive THz imaging system can detect THz wave from human body without transmit any electromagnetic wave, and the suspicious objects will become visible because the THz wave is blocked by this items. We can find out whether or not someone is carrying dangerous objects through this image. In this paper, the THz image enhancement, segmentation and contour extraction algorithms were studied to achieve effective target image detection. First, the terahertz images are enhanced and their grayscales are stretched. Then we apply global threshold segmentation to extract the target, and finally the targets are marked on the image. Experimental results showed that the algorithm proposed in this paper can extract and mark targets effectively, so that people can identify suspicious objects under clothing quickly. The algorithm can significantly improve the usefulness of the terahertz security apparatus.

Safe trajectory estimation at a pedestrian crossing to assist visually impaired people.

PubMed

Alghamdi, Saleh; van Schyndel, Ron; Khalil, Ibrahim

2012-01-01

The aim of this paper is to present a service for blind and people with low vision to assist them to cross the street independently. The presented approach provides the user with significant information such as detection of pedestrian crossing signal from any point of view, when the pedestrian crossing signal light is green, the detection of dynamic and fixed obstacles, predictions of the movement of fellow pedestrians and information on objects which may intersect his path. Our approach is based on capturing multiple frames using a depth camera which is attached to a user's headgear. Currently a testbed system is built on a helmet and is connected to a laptop in the user's backpack. In this paper, we discussed efficiency of using Speeded-Up Robust Features (SURF) algorithm for object recognition for purposes of blind people assistance. The system predicts the movement of objects of interest to provide the user with information on the safest path to navigate and information on the surrounding area. Evaluation of this approach on real sequence video frames provides 90% of human detection and more than 80% for recognition of other related objects.

X-raying a galactic gravitational lense

NASA Astrophysics Data System (ADS)

Garmire, Gordon

2016-09-01

It can be very difficult to detect compact objects that are not accreting in binary systems. Therefore we know very little about such objects and likely would not notice them even if they are very nearby. Two most obvious examples are very old isolated neutron stars (those that may be beyond the death line and hence are lacking pulsed radio or gamma-ray emission) and isolated stellar-mass black holes (none have been identified so far). OGLE3-ULENSPAR-05 is one of the few massive objects identified in microlensing searches for dark massive objects by the OGLE collaboration. We propose to detect the source or set stringent limit on its X-ray luminosity.

An Intelligent Systems Approach to Automated Object Recognition: A Preliminary Study

USGS Publications Warehouse

Maddox, Brian G.; Swadley, Casey L.

2002-01-01

Attempts at fully automated object recognition systems have met with varying levels of success over the years. However, none of the systems have achieved high enough accuracy rates to be run unattended. One of the reasons for this may be that they are designed from the computer's point of view and rely mainly on image-processing methods. A better solution to this problem may be to make use of modern advances in computational intelligence and distributed processing to try to mimic how the human brain is thought to recognize objects. As humans combine cognitive processes with detection techniques, such a system would combine traditional image-processing techniques with computer-based intelligence to determine the identity of various objects in a scene.

Raman Life Detection Instrument Development for Icy Worlds

NASA Technical Reports Server (NTRS)

Thomson, Seamus; Allen, A'Lester; Gutierrez, Daniel; Quinn, Richard C.; Chen, Bin; Koehne, Jessica E.

2017-01-01

The objective of this project is to develop a compact, high sensitivity Raman sensor for detection of life signatures in a flow cell configuration to enable bio-exploration and life detection during future mission to our Solar Systems Icy Worlds. The specific project objectives are the following: 1) Develop a Raman spectroscopy liquid analysis sensor for biosignatures; 2) Demonstrate applicability towards a future Enceladus or other Icy Worlds missions; 3) Establish key parameters for integration with the ARC Sample Processor for Life on Icy Worlds (SPLIce); 4) Position ARC for a successful response to upcoming Enceladus or other Icy World mission instrument opportunities.

Rendering visual events as sounds: Spatial attention capture by auditory augmented reality.

PubMed

Stone, Scott A; Tata, Matthew S

2017-01-01

Many salient visual events tend to coincide with auditory events, such as seeing and hearing a car pass by. Information from the visual and auditory senses can be used to create a stable percept of the stimulus. Having access to related coincident visual and auditory information can help for spatial tasks such as localization. However not all visual information has analogous auditory percepts, such as viewing a computer monitor. Here, we describe a system capable of detecting and augmenting visual salient events into localizable auditory events. The system uses a neuromorphic camera (DAVIS 240B) to detect logarithmic changes of brightness intensity in the scene, which can be interpreted as salient visual events. Participants were blindfolded and asked to use the device to detect new objects in the scene, as well as determine direction of motion for a moving visual object. Results suggest the system is robust enough to allow for the simple detection of new salient stimuli, as well accurately encoding direction of visual motion. Future successes are probable as neuromorphic devices are likely to become faster and smaller in the future, making this system much more feasible.

Rendering visual events as sounds: Spatial attention capture by auditory augmented reality

PubMed Central

Tata, Matthew S.

2017-01-01

Many salient visual events tend to coincide with auditory events, such as seeing and hearing a car pass by. Information from the visual and auditory senses can be used to create a stable percept of the stimulus. Having access to related coincident visual and auditory information can help for spatial tasks such as localization. However not all visual information has analogous auditory percepts, such as viewing a computer monitor. Here, we describe a system capable of detecting and augmenting visual salient events into localizable auditory events. The system uses a neuromorphic camera (DAVIS 240B) to detect logarithmic changes of brightness intensity in the scene, which can be interpreted as salient visual events. Participants were blindfolded and asked to use the device to detect new objects in the scene, as well as determine direction of motion for a moving visual object. Results suggest the system is robust enough to allow for the simple detection of new salient stimuli, as well accurately encoding direction of visual motion. Future successes are probable as neuromorphic devices are likely to become faster and smaller in the future, making this system much more feasible. PMID:28792518

Railway clearance intrusion detection method with binocular stereo vision

NASA Astrophysics Data System (ADS)

Zhou, Xingfang; Guo, Baoqing; Wei, Wei

2018-03-01

In the stage of railway construction and operation, objects intruding railway clearance greatly threaten the safety of railway operation. Real-time intrusion detection is of great importance. For the shortcomings of depth insensitive and shadow interference of single image method, an intrusion detection method with binocular stereo vision is proposed to reconstruct the 3D scene for locating the objects and judging clearance intrusion. The binocular cameras are calibrated with Zhang Zhengyou's method. In order to improve the 3D reconstruction speed, a suspicious region is firstly determined by background difference method of a single camera's image sequences. The image rectification, stereo matching and 3D reconstruction process are only executed when there is a suspicious region. A transformation matrix from Camera Coordinate System(CCS) to Track Coordinate System(TCS) is computed with gauge constant and used to transfer the 3D point clouds into the TCS, then the 3D point clouds are used to calculate the object position and intrusion in TCS. The experiments in railway scene show that the position precision is better than 10mm. It is an effective way for clearance intrusion detection and can satisfy the requirement of railway application.

Detectability of radiological images: the influence of anatomical noise

NASA Astrophysics Data System (ADS)

Bochud, Francois O.; Verdun, Francis R.; Hessler, Christian; Valley, Jean-Francois

1995-04-01

Radiological image quality can be objectively quantified by the statistical decision theory. This theory is commonly applied with the noise of the imaging system alone (quantum, screen and film noises) whereas the actual noise present on the image is the 'anatomical noise' (sum of the system noise and the anatomical texture). This anatomical texture should play a role in the detection task. This paper compares these two kinds of noises by performing 2AFC experiments and computing the area under the ROC-curve. It is shown that the 'anatomical noise' cannot be considered as a noise in the sense of Wiener spectrum approach and that the detectability performance is the same as the one obtained with the system noise alone in the case of a small object to be detected. Furthermore, the statistical decision theory and the non- prewhitening observer does not match the experimental results. This is especially the case in the low contrast values for which the theory predicts an increase of the detectability as soon as the contrast is different from zero whereas the experimental result demonstrates an offset of the contrast value below which the detectability is purely random. The theory therefore needs to be improved in order to take this result into account.

Development of a sonar-based object recognition system

NASA Astrophysics Data System (ADS)

Ecemis, Mustafa Ihsan

2001-02-01

Sonars are used extensively in mobile robotics for obstacle detection, ranging and avoidance. However, these range-finding applications do not exploit the full range of information carried in sonar echoes. In addition, mobile robots need robust object recognition systems. Therefore, a simple and robust object recognition system using ultrasonic sensors may have a wide range of applications in robotics. This dissertation develops and analyzes an object recognition system that uses ultrasonic sensors of the type commonly found on mobile robots. Three principal experiments are used to test the sonar recognition system: object recognition at various distances, object recognition during unconstrained motion, and softness discrimination. The hardware setup, consisting of an inexpensive Polaroid sonar and a data acquisition board, is described first. The software for ultrasound signal generation, echo detection, data collection, and data processing is then presented. Next, the dissertation describes two methods to extract information from the echoes, one in the frequency domain and the other in the time domain. The system uses the fuzzy ARTMAP neural network to recognize objects on the basis of the information content of their echoes. In order to demonstrate that the performance of the system does not depend on the specific classification method being used, the K- Nearest Neighbors (KNN) Algorithm is also implemented. KNN yields a test accuracy similar to fuzzy ARTMAP in all experiments. Finally, the dissertation describes a method for extracting features from the envelope function in order to reduce the dimension of the input vector used by the classifiers. Decreasing the size of the input vectors reduces the memory requirements of the system and makes it run faster. It is shown that this method does not affect the performance of the system dramatically and is more appropriate for some tasks. The results of these experiments demonstrate that sonar can be used to develop a low-cost, low-computation system for real-time object recognition tasks on mobile robots. This system differs from all previous approaches in that it is relatively simple, robust, fast, and inexpensive.

DDDAS for space applications

NASA Astrophysics Data System (ADS)

Blasch, Erik; Pham, Khanh D.; Shen, Dan; Chen, Genshe

2018-05-01

The dynamic data-driven applications systems (DDDAS) paradigm is meant to inject measurements into the execution model for enhanced systems performance. One area off interest in DDDAS is for space situation awareness (SSA). For SSA, data is collected about the space environment to determine object motions, environments, and model updates. Dynamically coupling between the data and models enhances the capabilities of each system by complementing models with data for system control, execution, and sensor management. The paper overviews some of the recent developments in SSA made possible from DDDAS techniques which are for object detection, resident space object tracking, atmospheric models for enhanced sensing, cyber protection, and information management.

Discriminating ultrasonic proximity detection system

DOEpatents

Annala, Wayne C.

1989-01-01

This invention uses an ultrasonic transmitter and receiver and a microprocessor to detect the presence of an object. In the reset mode the invention uses a plurality of echoes from each ultrasonic burst to create a reference table of the echo-burst-signature of the empty monitored environment. The invention then processes the reference table so that it only uses the most reliable data. In the detection mode the invention compares the echo-burst-signature of the present environment with the reference table, detecting an object if there is a consistent difference between the echo-burst-signature of the empty monitored environment recorded in the reference table and the echo-burst-signature of the present environment.

A Real Time AI Approach to Discrimination Boost Phase Optical Sensor Systems in SDI Architectures

NASA Astrophysics Data System (ADS)

Sloggett, David R.

1990-04-01

Interest has been rekindled in the potential utility of Ballistic Missile Defence (BMD) systems 1,2 and their ability to enhance the existing NATO strategic defence posture 3,4. Whereas in the past BMD systems have been thought to be vulnerable to relatively simple offence countermeasures, technological developments that have occurred over the past 20 years offer the potential to solve some of the main criticisms that have bedeviled BMD research since its inception in the early 1950s. One of the key areas where dramatic developments have taken place is in the field of electro-optic sensor technologies where developments in device sensitivity and packing density offer new solutions to threat detection, tracking and discrimination that complement data traditionally associated with radar based systems. Analysis has shown 5 that optical sensor systems can make a significant contribution to threat analysis in the boost and mid course phases of flight of ballistic missile systems. In the Boost phase the large amounts of energy contained within the plume of a ballistic missile system provides a signature that must be detected against cloud and earth backgrounds - necessitating viewing from space. The process of detection is complicated by reflected sunlight and other sources of false alarms. The optical sensor systems must therefore be adaptable and capable of reasoning about the location of the signatures, their persistence and temporal variations. Much of this processing is ideally carried out at the sensor system - in order to eliminate false alarms and reduce the communications bandwidths required to transfer the sensor data to centralised early warning and battle management facilities. In the mid course phase optical sensor systems can be used to detect warm objects against the background of deep space. These sensor systems can form tracks on these objects that can be merged into 3D tracks as data from individual sensor systems are combined. As closely spaced objects are resolved by sensor systems feature data can be extracted on individual objects that can be used by the defence system to attempt to discriminate between warheads, decoys and other penetration aids. This paper reviews work that has arisen from joint US SDIO and UK MOD research programmes into the feasibility of Theatre Missile Defence (TMD) systems that would be suitable for deploy ment and operation in a European theatre. The paper focuses on the problems of threat classification and discrimination in TtD systems and highlights the role of optical sensors. The paper discusses the integration of data derived from optical and radar sensors 6 and expands upon work previously reported into the use of an Artificial Intelligence (AI) approach to object classification and discrimination.

Debris mapping sensor technology project summary: Technology flight experiments program area of the space platforms technology program

NASA Technical Reports Server (NTRS)

1991-01-01

The topics presented are covered in viewgraph form. Programmatic objectives are: (1) to improve characterization of the orbital debris environment; and (2) to provide a passive sensor test bed for debris collision detection systems. Technical objectives are: (1) to study LEO debris altitude, size and temperature distribution down to 1 mm particles; (2) to quantify ground based radar and optical data ambiguities; and (3) to optimize debris detection strategies.

McDonald Observatory Planetary Search - A high precision stellar radial velocity survey for other planetary systems

NASA Technical Reports Server (NTRS)

Cochran, William D.; Hatzes, Artie P.

1993-01-01

The McDonald Observatory Planetary Search program surveyed a sample of 33 nearby F, G, and K stars since September 1987 to search for substellar companion objects. Measurements of stellar radial velocity variations to a precision of better than 10 m/s were performed as routine observations to detect Jovian planets in orbit around solar type stars. Results confirm the detection of a companion object to HD114762.

MACS-Mar: a real-time remote sensing system for maritime security applications

NASA Astrophysics Data System (ADS)

Brauchle, Jörg; Bayer, Steven; Hein, Daniel; Berger, Ralf; Pless, Sebastian

2018-04-01

The modular aerial camera system (MACS) is a development platform for optical remote sensing concepts, algorithms and special environments. For real-time services for maritime security (EMSec joint project), a new multi-sensor configuration MACS-Mar was realized. It consists of four co-aligned sensor heads in the visible RGB, near infrared (NIR, 700-950 nm), hyperspectral (HS, 450-900 nm) and thermal infrared (TIR, 7.5-14 µm) spectral range, a mid-cost navigation system, a processing unit and two data links. On-board image projection, cropping of redundant data and compression enable the instant generation of direct-georeferenced high-resolution image mosaics, automatic object detection, vectorization and annotation of floating objects on the water surface. The results were transmitted over a distance up to 50 km in real-time via narrow and broadband data links and were visualized in a maritime situation awareness system. For the automatic onboard detection of floating objects, a segmentation and classification workflow based on RGB, IR and TIR information was developed and tested. The completeness of the object detection in the experiment resulted in 95%, the correctness in 53%. Mostly, bright backwash of ships lead to an overestimation of the number of objects, further refinement using water homogeneity in the TIR, as implemented in the workflow, couldn't be carried out due to problems with the TIR sensor, else distinctly better results could have been expected. The absolute positional accuracy of the projected real-time imagery resulted in 2 m without postprocessing of images or navigation data, the relative measurement accuracy of distances is in the range of the image resolution, which is about 12 cm for RGB imagery in the EMSec experiment.

Improving Child Maltreatment Detection Systems: A Large-Scale Case Study Involving Health, Social Services, and School Professionals

ERIC Educational Resources Information Center

Cerezo, M.A.; Pons-Salvador, G.

2004-01-01

Objectives:: The purpose of this 5-year study was to improve detection in two consecutive phases: (a) To close the gap between the number of identified cases and the actual number of cases of child abuse by increasing detection; and (b) To increase the possibility of a broader spectrum of detection. Method:: The Balearic Islands (one of the…

Motion measurement of acoustically levitated object

NASA Technical Reports Server (NTRS)

Watkins, John L. (Inventor); Barmatz, Martin B. (Inventor)

1993-01-01

A system is described for determining motion of an object that is acoustically positioned in a standing wave field in a chamber. Sonic energy in the chamber is sensed, and variation in the amplitude of the sonic energy is detected, which is caused by linear motion, rotational motion, or drop shape oscillation of the object. Apparatus for detecting object motion can include a microphone coupled to the chamber and a low pass filter connected to the output of the microphone, which passes only frequencies below the frequency of sound produced by a transducer that maintains the acoustic standing wave field. Knowledge about object motion can be useful by itself, can be useful to determine surface tension, viscosity, and other information about the object, and can be useful to determine the pressure and other characteristics of the acoustic field.

The combination design for open and endoscopic surgery using fluorescence molecular imaging technology

NASA Astrophysics Data System (ADS)

Mao, Yamin; Jiang, Shixin; Ye, Jinzuo; An, Yu; Yang, Xin; Chi, Chongwei; Tian, Jie

2015-03-01

For clinical surgery, it is still a challenge to objectively determine tumor margins during surgery. With the development of medical imaging technology, fluorescence molecular imaging (FMI) method can provide real-time intraoperative tumor margin information. Furthermore, surgical navigation system based on FMI technology plays an important role for the aid of surgeons' precise tumor margin decision. However, detection depth is the most limitation exists in the FMI technique and the method convenient for either macro superficial detection or micro deep tissue detection is needed. In this study, we combined advantages of both open surgery and endoscopic imaging systems with FMI technology. Indocyanine green (ICG) experiments were performed to confirm the feasibility of fluorescence detection in our system. Then, the ICG signal was photographed in the detection area with our system. When the system connected with endoscope lens, the minimum quantity of ICG detected by our system was 0.195 ug. For aspect of C mount lens, the sensitivity of ICG detection with our system was 0.195ug. Our experiments results proved that it was feasible to detect fluorescence images with this combination method. Our system shows great potential in the clinical applications of precise dissection of various tumors

Computed radiography utilizing laser-stimulated luminescence: detectability of simulated low-contrast radiographic objects.

PubMed

Higashida, Y; Moribe, N; Hirata, Y; Morita, K; Doudanuki, S; Sonoda, Y; Katsuda, N; Hiai, Y; Misumi, W; Matsumoto, M

1988-01-01

Threshold contrasts of low-contrast objects with computed radiography (CR) images were compared with those of blue and green emitting screen-film systems by employing the 18-alternative forced choice (18-AFC) procedure. The dependence of the threshold contrast on the incident X-ray exposure and also the object size was studied. The results indicated that the threshold contrasts of CR system were comparable to those of blue and green screen-film systems and decreased with increasing object size, and increased with decreasing incident X-ray exposure. The increase in threshold contrasts was small when the relative incident exposure decreased from 1 to 1/4, and was large when incident exposure was decreased further.

Human Location Detection System Using Micro-Electromechanical Sensor for Intelligent Fan

NASA Astrophysics Data System (ADS)

Parnin, S.; Rahman, M. M.

2017-03-01

This paper presented the development of sensory system for detection of both the presence and the location of human in a room spaces using MEMS Thermal sensor. The system is able to detect the surface temperature of occupants by a non-contact detection at the maximum of 6 meters far. It can be integrated to any swing type of electrical appliances such as standing fan or a similar devices. Differentiating human from other moving and or static object by heat variable is nearly impossible since human, animals and electrical appliances produce heat. The uncontrollable heat properties which can change and transfer will add to the detection issue. Integrating the low cost MEMS based thermal sensor can solve the first of human sensing problem by its ability to detect human in stationary. Further discrimination and analysis must therefore be made to the measured temperature data to distinguish human from other objects. In this project, the fan is properly designed and program in such a way that it can adapt to different events starting from the human sensing stage to its dynamic and mechanical moving parts. Up to this stage initial testing to the Omron D6T microelectromechanical thermal sensor is currently under several experimental stages. Experimental result of the sensor tested on stationary and motion state of human are behaviorally differentiable and successfully locate the human position by detecting the maximum temperature of each sensor reading.

Object Locating System

NASA Technical Reports Server (NTRS)

Arndt, G. Dickey (Inventor); Carl, James R. (Inventor)

2000-01-01

A portable system is provided that is operational for determining, with three dimensional resolution, the position of a buried object or approximately positioned object that may move in space or air or gas. The system has a plurality of receivers for detecting the signal front a target antenna and measuring the phase thereof with respect to a reference signal. The relative permittivity and conductivity of the medium in which the object is located is used along with the measured phase signal to determine a distance between the object and each of the plurality of receivers. Knowing these distances. an iteration technique is provided for solving equations simultaneously to provide position coordinates. The system may also be used for tracking movement of an object within close range of the system by sampling and recording subsequent position of the object. A dipole target antenna. when positioned adjacent to a buried object, may be energized using a separate transmitter which couples energy to the target antenna through the medium. The target antenna then preferably resonates at a different frequency, such as a second harmonic of the transmitter frequency.

A serendipitous all sky survey for bright objects in the outer solar system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, M. E.; Drake, A. J.; Djorgovski, S. G.

2015-02-01

We use seven year's worth of observations from the Catalina Sky Survey and the Siding Spring Survey covering most of the northern and southern hemisphere at galactic latitudes higher than 20° to search for serendipitously imaged moving objects in the outer solar system. These slowly moving objects would appear as stationary transients in these fast cadence asteroids surveys, so we develop methods to discover objects in the outer solar system using individual observations spaced by months, rather than spaced by hours, as is typically done. While we independently discover eight known bright objects in the outer solar system, the faintestmore » having V=19.8±0.1, no new objects are discovered. We find that the survey is nearly 100% efficient at detecting objects beyond 25 AU for V≲19.1 (V≲18.6 in the southern hemisphere) and that the probability that there is one or more remaining outer solar system object of this brightness left to be discovered in the unsurveyed regions of the galactic plane is approximately 32%.« less

Vision System Measures Motions of Robot and External Objects

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2008-01-01

A prototype of an advanced robotic vision system both (1) measures its own motion with respect to a stationary background and (2) detects other moving objects and estimates their motions, all by use of visual cues. Like some prior robotic and other optoelectronic vision systems, this system is based partly on concepts of optical flow and visual odometry. Whereas prior optoelectronic visual-odometry systems have been limited to frame rates of no more than 1 Hz, a visual-odometry subsystem that is part of this system operates at a frame rate of 60 to 200 Hz, given optical-flow estimates. The overall system operates at an effective frame rate of 12 Hz. Moreover, unlike prior machine-vision systems for detecting motions of external objects, this system need not remain stationary: it can detect such motions while it is moving (even vibrating). The system includes a stereoscopic pair of cameras mounted on a moving robot. The outputs of the cameras are digitized, then processed to extract positions and velocities. The initial image-data-processing functions of this system are the same as those of some prior systems: Stereoscopy is used to compute three-dimensional (3D) positions for all pixels in the camera images. For each pixel of each image, optical flow between successive image frames is used to compute the two-dimensional (2D) apparent relative translational motion of the point transverse to the line of sight of the camera. The challenge in designing this system was to provide for utilization of the 3D information from stereoscopy in conjunction with the 2D information from optical flow to distinguish between motion of the camera pair and motions of external objects, compute the motion of the camera pair in all six degrees of translational and rotational freedom, and robustly estimate the motions of external objects, all in real time. To meet this challenge, the system is designed to perform the following image-data-processing functions: The visual-odometry subsystem (the subsystem that estimates the motion of the camera pair relative to the stationary background) utilizes the 3D information from stereoscopy and the 2D information from optical flow. It computes the relationship between the 3D and 2D motions and uses a least-mean-squares technique to estimate motion parameters. The least-mean-squares technique is suitable for real-time implementation when the number of external-moving-object pixels is smaller than the number of stationary-background pixels.

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors.

PubMed

Villaverde, Monica; Perez, David; Moreno, Felix

2015-11-17

The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

A semantic autonomous video surveillance system for dense camera networks in Smart Cities.

PubMed

Calavia, Lorena; Baladrón, Carlos; Aguiar, Javier M; Carro, Belén; Sánchez-Esguevillas, Antonio

2012-01-01

This paper presents a proposal of an intelligent video surveillance system able to detect and identify abnormal and alarming situations by analyzing object movement. The system is designed to minimize video processing and transmission, thus allowing a large number of cameras to be deployed on the system, and therefore making it suitable for its usage as an integrated safety and security solution in Smart Cities. Alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies. This means that the system employs a high-level conceptual language easy to understand for human operators, capable of raising enriched alarms with descriptions of what is happening on the image, and to automate reactions to them such as alerting the appropriate emergency services using the Smart City safety network.

A Semantic Autonomous Video Surveillance System for Dense Camera Networks in Smart Cities

PubMed Central

Calavia, Lorena; Baladrón, Carlos; Aguiar, Javier M.; Carro, Belén; Sánchez-Esguevillas, Antonio

2012-01-01

This paper presents a proposal of an intelligent video surveillance system able to detect and identify abnormal and alarming situations by analyzing object movement. The system is designed to minimize video processing and transmission, thus allowing a large number of cameras to be deployed on the system, and therefore making it suitable for its usage as an integrated safety and security solution in Smart Cities. Alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies. This means that the system employs a high-level conceptual language easy to understand for human operators, capable of raising enriched alarms with descriptions of what is happening on the image, and to automate reactions to them such as alerting the appropriate emergency services using the Smart City safety network. PMID:23112607

The what, where and how of auditory-object perception.

PubMed

Bizley, Jennifer K; Cohen, Yale E

2013-10-01

The fundamental perceptual unit in hearing is the 'auditory object'. Similar to visual objects, auditory objects are the computational result of the auditory system's capacity to detect, extract, segregate and group spectrotemporal regularities in the acoustic environment; the multitude of acoustic stimuli around us together form the auditory scene. However, unlike the visual scene, resolving the component objects within the auditory scene crucially depends on their temporal structure. Neural correlates of auditory objects are found throughout the auditory system. However, neural responses do not become correlated with a listener's perceptual reports until the level of the cortex. The roles of different neural structures and the contribution of different cognitive states to the perception of auditory objects are not yet fully understood.

VizieR Online Data Catalog: QSOs narrow absorption line variability (Hacker+, 2013)

NASA Astrophysics Data System (ADS)

Hacker, T. L.; Brunner, R. J.; Lundgren, B. F.; York, D. G.

2013-06-01

Catalogues of 2,522 QAL systems and 33 variable NAL systems detected in SDSS DR7 quasars with repeat observations. The object identifiers, position coordinates, and plate-MJD-fibre designations are taken from the SpecObjAll table in the SDSS Catalogue Archive Server (CAS) while the quasar redshifts (zqso) are from Hewett & Wild (2010, Cat. J/MNRAS/405/2302). The absorption system redshift (zabs), system grade, and detected lines are outputs of the York et al. (2013, in. prep.) QAL detection pipeline. Some absorption lines are flagged based on alternate identifications (a), proximity of masked pixels (b), or questionable continuum fits (c). (3 data files).

Method and apparatus for detecting concealed weapons

DOEpatents

Kotter, Dale K.; Fluck, Frederick D.

2006-03-14

Apparatus for classifying a ferromagnetic object within a sensing area may include a magnetic field sensor that produces magnetic field data. A signal processing system operatively associated with the magnetic field sensor includes a neural network. The neural network compares the magnetic field data with magnetic field data produced by known ferromagnetic objects to make a probabilistic determination as to the classification of the ferromagnetic object within the sensing area. A user interface operatively associated with the signal processing system produces a user-discernable output indicative of the probabilistic determination of the classification of the ferromagnetic object within a sensing area.

Automatic mine detection based on multiple features

NASA Astrophysics Data System (ADS)

Yu, Ssu-Hsin; Gandhe, Avinash; Witten, Thomas R.; Mehra, Raman K.

2000-08-01

Recent research sponsored by the Army, Navy and DARPA has significantly advanced the sensor technologies for mine detection. Several innovative sensor systems have been developed and prototypes were built to investigate their performance in practice. Most of the research has been focused on hardware design. However, in order for the systems to be in wide use instead of in limited use by a small group of well-trained experts, an automatic process for mine detection is needed to make the final decision process on mine vs. no mine easier and more straightforward. In this paper, we describe an automatic mine detection process consisting of three stage, (1) signal enhancement, (2) pixel-level mine detection, and (3) object-level mine detection. The final output of the system is a confidence measure that quantifies the presence of a mine. The resulting system was applied to real data collected using radar and acoustic technologies.

Final report : mobile surveillance and wireless communication systems field operational test. Volume 2, FOT objectives, organization, system design, results, conclusions, and recommendations

DOT National Transportation Integrated Search

1999-03-01

The Mobile Surveillance and Wireless Communication Systems Field Operational Test (FOT) evaluated the performance of wireless traffic detection and communications systems in areas where permanent detectors, electrical power, and landline communicatio...

Video library for video imaging detection at intersection stop lines.

DOT National Transportation Integrated Search

2010-04-01

The objective of this activity was to record video that could be used for controlled : evaluation of video image vehicle detection system (VIVDS) products and software upgrades to : existing products based on a list of conditions that might be diffic...

OSSOS. IX. Two Objects in Neptune's 9:1 Resonance—Implications for Resonance Sticking in the Scattering Population

NASA Astrophysics Data System (ADS)

Volk, Kathryn; Murray-Clay, Ruth A.; Gladman, Brett J.; Lawler, Samantha M.; Yu, Tze Yeung Mathew; Alexandersen, Mike; Bannister, Michele T.; Chen, Ying-Tung; Dawson, Rebekah I.; Greenstreet, Sarah; Gwyn, Stephen D. J.; Kavelaars, J. J.; Lin, Hsing Wen; Lykawka, Patryk Sofia; Petit, Jean-Marc

2018-06-01

We discuss the detection in the Outer Solar System Origins Survey (OSSOS) of two objects in Neptune’s distant 9:1 mean motion resonance at semimajor axis a ≈ 130 au. Both objects are securely resonant on 10 Myr timescales, with one securely in the 9:1 resonance’s leading asymmetric libration island and the other in either the symmetric or trailing asymmetric island. These objects are the largest semimajor axis objects with secure resonant classifications, and their detection in a carefully characterized survey allows for the first robust resonance population estimate beyond 100 au. The detection of these objects implies a 9:1 resonance population of 1.1 × 104 objects with H r < 8.66 (D ≳ 100 km) on similar orbits (95% confidence range of ∼(0.4–3) × 104). Integrations over 4 Gyr of an ensemble of clones spanning these objects’ orbit-fit uncertainties reveal that they both have median resonance occupation timescales of ∼1 Gyr. These timescales are consistent with the hypothesis that these objects originate in the scattering population but became transiently stuck to Neptune’s 9:1 resonance within the last ∼1 Gyr of solar system evolution. Based on simulations of a model of the current scattering population, we estimate the expected resonance sticking population in the 9:1 resonance to be 1000–4500 objects with H r < 8.66 this is marginally consistent with the OSSOS 9:1 population estimate. We conclude that resonance sticking is a plausible explanation for the observed 9:1 population, but we also discuss the possibility of a primordial 9:1 population, which would have interesting implications for the Kuiper Belt’s dynamical history.

Comparison of two commercially available rapid detection methods and a conventional culture method to detect naturally occurring salmonellae on broiler carcasses

USDA-ARS?s Scientific Manuscript database

Many different screening devices and sampling methods have been used to detect the presence of naturally occurring Salmonella on commercially processed broiler carcasses. The objective of this study was to compare two commercial screening systems (BAX® and Roka®) to a standard cultural procedure use...

Performance Assessment Method for a Forged Fingerprint Detection Algorithm

NASA Astrophysics Data System (ADS)

Shin, Yong Nyuo; Jun, In-Kyung; Kim, Hyun; Shin, Woochang

The threat of invasion of privacy and of the illegal appropriation of information both increase with the expansion of the biometrics service environment to open systems. However, while certificates or smart cards can easily be cancelled and reissued if found to be missing, there is no way to recover the unique biometric information of an individual following a security breach. With the recognition that this threat factor may disrupt the large-scale civil service operations approaching implementation, such as electronic ID cards and e-Government systems, many agencies and vendors around the world continue to develop forged fingerprint detection technology, but no objective performance assessment method has, to date, been reported. Therefore, in this paper, we propose a methodology designed to evaluate the objective performance of the forged fingerprint detection technology that is currently attracting a great deal of attention.

Depth detection in interactive projection system based on one-shot black-and-white stripe pattern.

PubMed

Zhou, Qian; Qiao, Xiaorui; Ni, Kai; Li, Xinghui; Wang, Xiaohao

2017-03-06

A novel method enabling estimation of not only the screen surface as the conventional one, but the depth information from two-dimensional coordinates in an interactive projection system was proposed in this research. In this method, a one-shot black-and-white stripe pattern from a projector is projected on a screen plane, where the deformed pattern is captured by a charge-coupled device camera. An algorithm based on object/shadow simultaneous detection is proposed for fulfillment of the correspondence. The depth information of the object is then calculated using the triangulation principle. This technology provides a more direct feeling of virtual interaction in three dimensions without using auxiliary equipment or a special screen as interaction proxies. Simulation and experiments are carried out and the results verified the effectiveness of this method in depth detection.

Optical filter for highlighting spectral features part I: design and development of the filter for discrimination of human skin with and without an application of cosmetic foundation.

PubMed

Nishino, Ken; Nakamura, Mutsuko; Matsumoto, Masayuki; Tanno, Osamu; Nakauchi, Shigeki

2011-03-28

Light reflected from an object's surface contains much information about its physical and chemical properties. Changes in the physical properties of an object are barely detectable in spectra. Conventional trichromatic systems, on the other hand, cannot detect most spectral features because spectral information is compressively represented as trichromatic signals forming a three-dimensional subspace. We propose a method for designing a filter that optically modulates a camera's spectral sensitivity to find an alternative subspace highlighting an object's spectral features more effectively than the original trichromatic space. We designed and developed a filter that detects cosmetic foundations on human face. Results confirmed that the filter can visualize and nondestructively inspect the foundation distribution.

Micro-vibration detection with heterodyne holography based on time-averaged method

NASA Astrophysics Data System (ADS)

Qin, XiaoDong; Pan, Feng; Chen, ZongHui; Hou, XueQin; Xiao, Wen

2017-02-01

We propose a micro-vibration detection method by introducing heterodyne interferometry to time-averaged holography. This method compensates for the deficiency of time-average holography in quantitative measurements and widens its range of application effectively. Acousto-optic modulators are used to modulate the frequencies of the reference beam and the object beam. Accurate detection of the maximum amplitude of each point in the vibration plane is performed by altering the frequency difference of both beams. The range of amplitude detection of plane vibration is extended. In the stable vibration mode, the distribution of the maximum amplitude of each point is measured and the fitted curves are plotted. Hence the plane vibration mode of the object is demonstrated intuitively and detected quantitatively. We analyzed the method in theory and built an experimental system with a sine signal as the excitation source and a typical piezoelectric ceramic plate as the target. The experimental results indicate that, within a certain error range, the detected vibration mode agrees with the intrinsic vibration characteristics of the object, thus proving the validity of this method.

35-45 Giga Hertz Transceiver System for Phase and Magnitude Detection

NASA Technical Reports Server (NTRS)

Beni, Aman Aflaki

2007-01-01

Nondestructive evaluation (NDE) is the science and practice of examining an object in a way that the object's usefulness is not adversely affected. Different types of NDE methods exist but this thesis is based on microwave and millimeter wave NDE using imaging techniques. Microwave NDE is based on illuminating the object under test with a microwave signal and studying the various properties of the reflected signal from the object. This reflected signal contains some information about the inner structure of the object under test. This information may be contained in several parameters including the phase and magnitude of the reflected signal. The goal of this project is to design and build a Q-band coherent transceiver that is capable of measuring the reflected signal's phase and magnitude so that an image of the object under test may be reconstructed. From the several techniques that can be used to construct an image of the object under test, techniques of interest to this work include synthetic aperture focusing technique (SAFT) and microwave holography. The transceiver system should have the ability to sweep a large portion of Q-band frequency range in small frequency steps as quick as possible while the detected phase and magnitude of the reflected signal is very accurate. Several different designs were studied and the final schematic diagram of the transceiver system was determined. One of the most important modules that was designed, implemented and tested in the laboratory was an accurate phase/magnitude detector circuit. The compared results of the scans using the transceiver system and vector network analyzer (VNA) showed that this transceiver system has a great potential to replace a VNA for the purpose of microwave and millimeter wave imaging.

Detecting abandoned objects using interacting multiple models

NASA Astrophysics Data System (ADS)

Becker, Stefan; Münch, David; Kieritz, Hilke; Hübner, Wolfgang; Arens, Michael

2015-10-01

In recent years, the wide use of video surveillance systems has caused an enormous increase in the amount of data that has to be stored, monitored, and processed. As a consequence, it is crucial to support human operators with automated surveillance applications. Towards this end an intelligent video analysis module for real-time alerting in case of abandoned objects in public spaces is proposed. The overall processing pipeline consists of two major parts. First, person motion is modeled using an Interacting Multiple Model (IMM) filter. The IMM filter estimates the state of a person according to a finite-state, discrete-time Markov chain. Second, the location of persons that stay at a fixed position defines a region of interest, in which a nonparametric background model with dynamic per-pixel state variables identifies abandoned objects. In case of a detected abandoned object, an alarm event is triggered. The effectiveness of the proposed system is evaluated on the PETS 2006 dataset and the i-Lids dataset, both reflecting prototypical surveillance scenarios.

Debiasing the Distant Solar System Populations Using Pan-STARRS1

NASA Astrophysics Data System (ADS)

Lilly Schunova, Eva; Weryk, Robert J.; Chastel, Serge; Denneau, Larry; Jedicke, Robert; Wainscoat, Richard J.; Chambers, Kenneth C.

2017-10-01

We discuss our on-going effort to identify Trans-Neptunian Objects (TNOs) in the Pan-STARRS1 dataset, and to debias the size-frequency distributions (SFD) of detected TNO sub-populations in order to estimate their true population sizes. To measure our detection efficiency we used the model of Grav et al. (2011)[1], which includes Kuiper belt Objects (KBOs), Scattered Disc Objects (SDOs), and Centaurs. Our debiasing method accounts for the per-chip CCD sensitivity as well as CCD cell gaps. The search method for finding distant Solar System objects, which was developed for our initial work (Weryk et al., 2016)[2], led to discovery of 29 Centaurs, 243 KBOs and 61 SDOs from Pan-STARRS data spanning years 2010-2015. Our work is extended using more recent PS1 data.[1] Grav, T., et al. (2011), Publications of the Astronomical Society of Pacific, Volume 123, Issue 902, pp. 423.[2] Weryk, R.J., et al. (2016), eprint arXiv:1607.04895.

Smart mobile robot system for rubbish collection

NASA Astrophysics Data System (ADS)

Ali, Mohammed A. H.; Sien Siang, Tan

2018-03-01

This paper records the research and procedures of developing a smart mobility robot with detection system to collect rubbish. The objective of this paper is to design a mobile robot that can detect and recognize medium-size rubbish such as drinking cans. Besides that, the objective is also to design a mobile robot with the ability to estimate the position of rubbish from the robot. In addition, the mobile robot is also able to approach the rubbish based on position of rubbish. This paper explained about the types of image processing, detection and recognition methods and image filters. This project implements RGB subtraction method as the prior system. Other than that, algorithm for distance measurement based on image plane is implemented in this project. This project is limited to use computer webcam as the sensor. Secondly, the robot is only able to approach the nearest rubbish in the same views of camera vision and any rubbish that contain RGB colour components on its body.

Advanced driver assistance system: Road sign identification using VIAPIX system and a correlation technique

NASA Astrophysics Data System (ADS)

Ouerhani, Y.; Alfalou, A.; Desthieux, M.; Brosseau, C.

2017-02-01

We present a three-step approach based on the commercial VIAPIX® module for road traffic sign recognition and identification. Firstly, detection in a scene of all objects having characteristics of traffic signs is performed. This is followed by a first-level recognition based on correlation which consists in making a comparison between each detected object with a set of reference images of a database. Finally, a second level of identification allows us to confirm or correct the previous identification. In this study, we perform a correlation-based analysis by combining and adapting the Vander Lugt correlator with the nonlinear joint transformation correlator (JTC). Of particular significance, this approach permits to make a reliable decision on road traffic sign identification. We further discuss a robust scheme allowing us to track a detected road traffic sign in a video sequence for the purpose of increasing the decision performance of our system. This approach can have broad practical applications in the maintenance and rehabilitation of transportation infrastructure, or for drive assistance.

Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation

PubMed Central

Gonzalez, Luis F.; Montes, Glen A.; Puig, Eduard; Johnson, Sandra; Mengersen, Kerrie; Gaston, Kevin J.

2016-01-01

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification. PMID:26784196

Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation.

PubMed

Gonzalez, Luis F; Montes, Glen A; Puig, Eduard; Johnson, Sandra; Mengersen, Kerrie; Gaston, Kevin J

2016-01-14

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

A simulation study of detection of weapon of mass destruction based on radar

NASA Astrophysics Data System (ADS)

Sharifahmadian, E.; Choi, Y.; Latifi, S.

2013-05-01

Typical systems used for detection of Weapon of Mass Destruction (WMD) are based on sensing objects using gamma rays or neutrons. Nonetheless, depending on environmental conditions, current methods for detecting fissile materials have limited distance of effectiveness. Moreover, radiation related to gamma- rays can be easily shielded. Here, detecting concealed WMD from a distance is simulated and studied based on radar, especially WideBand (WB) technology. The WB-based method capitalizes on the fact that electromagnetic waves penetrate through different materials at different rates. While low-frequency waves can pass through objects more easily, high-frequency waves have a higher rate of absorption by objects, making the object recognition easier. Measuring the penetration depth allows one to identify the sensed material. During simulation, radar waves and propagation area including free space, and objects in the scene are modeled. In fact, each material is modeled as a layer with a certain thickness. At start of simulation, a modeled radar wave is radiated toward the layers. At the receiver side, based on the received signals from every layer, each layer can be identified. When an electromagnetic wave passes through an object, the wave's power will be subject to a certain level of attenuation depending of the object's characteristics. Simulation is performed using radar signals with different frequencies (ranges MHz-GHz) and powers to identify different layers.

Fuzzy Kernel k-Medoids algorithm for anomaly detection problems

NASA Astrophysics Data System (ADS)

Rustam, Z.; Talita, A. S.

2017-07-01

Intrusion Detection System (IDS) is an essential part of security systems to strengthen the security of information systems. IDS can be used to detect the abuse by intruders who try to get into the network system in order to access and utilize the available data sources in the system. There are two approaches of IDS, Misuse Detection and Anomaly Detection (behavior-based intrusion detection). Fuzzy clustering-based methods have been widely used to solve Anomaly Detection problems. Other than using fuzzy membership concept to determine the object to a cluster, other approaches as in combining fuzzy and possibilistic membership or feature-weighted based methods are also used. We propose Fuzzy Kernel k-Medoids that combining fuzzy and possibilistic membership as a powerful method to solve anomaly detection problem since on numerical experiment it is able to classify IDS benchmark data into five different classes simultaneously. We classify IDS benchmark data KDDCup'99 data set into five different classes simultaneously with the best performance was achieved by using 30 % of training data with clustering accuracy reached 90.28 percent.

Motion-seeded object-based attention for dynamic visual imagery

NASA Astrophysics Data System (ADS)

Huber, David J.; Khosla, Deepak; Kim, Kyungnam

2017-05-01

This paper† describes a novel system that finds and segments "objects of interest" from dynamic imagery (video) that (1) processes each frame using an advanced motion algorithm that pulls out regions that exhibit anomalous motion, and (2) extracts the boundary of each object of interest using a biologically-inspired segmentation algorithm based on feature contours. The system uses a series of modular, parallel algorithms, which allows many complicated operations to be carried out by the system in a very short time, and can be used as a front-end to a larger system that includes object recognition and scene understanding modules. Using this method, we show 90% accuracy with fewer than 0.1 false positives per frame of video, which represents a significant improvement over detection using a baseline attention algorithm.

Design of short-range terahertz wave passive detecting system

NASA Astrophysics Data System (ADS)

Zhang, Chao; Lou, Guowei; Zhu, Li; Qian, Songsong; Li, Ting

2016-09-01

Based on the study of radiation and transmission characteristics on THz waveband, a short-range passive detecting system is designed. The scheme originated from microwave passive detecting system. A prototype was developed following the design of key components including antennas and a harmonic mixer. The system operated at 0.36 THz. A dual-beam Cassegrain antenna was adopted for receiving signals which radiated by object and background. Local oscillator signal was generated by frequency multiplication. Harmonic mixing is adopted for reducing local oscillator signal frequency required by half. Superheterodyne technology is employed for signal acquisition. The system implemented easily. Tests and measurements were taken, which showed that the scheme was feasible and the performance of the prototype system met the design requirements.

Study of multi-channel optical system based on the compound eye

NASA Astrophysics Data System (ADS)

Zhao, Yu; Fu, Yuegang; Liu, Zhiying; Dong, Zhengchao

2014-09-01

As an important part of machine vision, compound eye optical systems have the characteristics of high resolution and large FOV. By applying the compound eye optical systems to target detection and recognition, the contradiction between large FOV and high resolution in the traditional single aperture optical systems could be solved effectively and also the parallel processing ability of the optical systems could be sufficiently shown. In this paper, the imaging features of the compound eye optical systems are analyzed. After discussing the relationship between the FOV in each subsystem and the contact ratio of the FOV in the whole system, a method to define the FOV of the subsystem is presented. And a compound eye optical system is designed, which is based on the large FOV synthesized of multi-channels. The compound eye optical system consists with a central optical system and array subsystem, in which the array subsystem is used to capture the target. The high resolution image of the target could be achieved by the central optical system. With the advantage of small volume, light weight and rapid response speed, the optical system could detect the objects which are in 3km and FOV of 60°without any scanning device. The objects in the central field 2w=5.1°could be imaged with high resolution so that the objects could be recognized.

Machine-learning-based real-bogus system for the HSC-SSP moving object detection pipeline

NASA Astrophysics Data System (ADS)

Lin, Hsing-Wen; Chen, Ying-Tung; Wang, Jen-Hung; Wang, Shiang-Yu; Yoshida, Fumi; Ip, Wing-Huen; Miyazaki, Satoshi; Terai, Tsuyoshi

2018-01-01

Machine-learning techniques are widely applied in many modern optical sky surveys, e.g., Pan-STARRS1, PTF/iPTF, and the Subaru/Hyper Suprime-Cam survey, to reduce human intervention in data verification. In this study, we have established a machine-learning-based real-bogus system to reject false detections in the Subaru/Hyper-Suprime-Cam Strategic Survey Program (HSC-SSP) source catalog. Therefore, the HSC-SSP moving object detection pipeline can operate more effectively due to the reduction of false positives. To train the real-bogus system, we use stationary sources as the real training set and "flagged" data as the bogus set. The training set contains 47 features, most of which are photometric measurements and shape moments generated from the HSC image reduction pipeline (hscPipe). Our system can reach a true positive rate (tpr) ˜96% with a false positive rate (fpr) ˜1% or tpr ˜99% at fpr ˜5%. Therefore, we conclude that stationary sources are decent real training samples, and using photometry measurements and shape moments can reject false positives effectively.

Affective brain-computer music interfacing

NASA Astrophysics Data System (ADS)

Daly, Ian; Williams, Duncan; Kirke, Alexis; Weaver, James; Malik, Asad; Hwang, Faustina; Miranda, Eduardo; Nasuto, Slawomir J.

2016-08-01

Objective. We aim to develop and evaluate an affective brain-computer music interface (aBCMI) for modulating the affective states of its users. Approach. An aBCMI is constructed to detect a user's current affective state and attempt to modulate it in order to achieve specific objectives (for example, making the user calmer or happier) by playing music which is generated according to a specific affective target by an algorithmic music composition system and a case-based reasoning system. The system is trained and tested in a longitudinal study on a population of eight healthy participants, with each participant returning for multiple sessions. Main results. The final online aBCMI is able to detect its users current affective states with classification accuracies of up to 65% (3 class, p\\lt 0.01) and modulate its user's affective states significantly above chance level (p\\lt 0.05). Significance. Our system represents one of the first demonstrations of an online aBCMI that is able to accurately detect and respond to user's affective states. Possible applications include use in music therapy and entertainment.

Study of moving object detecting and tracking algorithm for video surveillance system

NASA Astrophysics Data System (ADS)

Wang, Tao; Zhang, Rongfu

2010-10-01

This paper describes a specific process of moving target detecting and tracking in the video surveillance.Obtain high-quality background is the key to achieving differential target detecting in the video surveillance.The paper is based on a block segmentation method to build clear background,and using the method of background difference to detecing moving target,after a series of treatment we can be extracted the more comprehensive object from original image,then using the smallest bounding rectangle to locate the object.In the video surveillance system, the delay of camera and other reasons lead to tracking lag,the model of Kalman filter based on template matching was proposed,using deduced and estimated capacity of Kalman,the center of smallest bounding rectangle for predictive value,predicted the position in the next moment may appare,followed by template matching in the region as the center of this position,by calculate the cross-correlation similarity of current image and reference image,can determine the best matching center.As narrowed the scope of searching,thereby reduced the searching time,so there be achieve fast-tracking.

Development of a biomimetic roughness sensor for tactile information with an elastomer

NASA Astrophysics Data System (ADS)

Choi, Jae-Young; Kim, Sung Joon; Moon, Hyungpil; Choi, Hyouk Ryeol; Koo, Ja Choon

2016-04-01

Human uses various sensational information for identifying an object. When contacting an unidentified object with no vision, tactile sensation provides a variety of information to perceive. Tactile sensation plays an important role to recognize a shape of surfaces from touching. In robotic fields, tactile sensation is especially meaningful. Robots can perform more accurate job using comprehensive tactile information. And in case of using sensors made by soft material like silicone, sensors can be used in various situations. So we are developing a tactile sensor with soft materials. As the conventional robot operates in a controlled environment, it is a good model to make robots more available at any circumstance that sensory systems of living things. For example, there are lots of mechanoreceptors that each of them has different roles detecting simulation in side of human skin tissue. By mimicking the mechanoreceptor, a sensory system can be realized more closely to human being. It is known that human obtains roughness information through scanning the surface with fingertips. During that times, subcutaneous mechanoreceptors detect vibration. In the same way, while a robot is scanning a surface of object, a roughness sensor developed detects vibrations generated between contacting two surfaces. In this research, a roughness sensor made by an elastomer was developed and experiment for perception of objects was conducted. We describe means to compare the roughness of objects with a newly developed sensor.

Evaluation of a radar-based proximity warning system for off-highway dump trucks.

PubMed

Ruff, Todd

2006-01-01

A radar-based proximity warning system was evaluated by researchers at the Spokane Research Laboratory of the National Institute for Occupational Safety and Health to determine if the system would be effective in detecting objects in the blind spots of an off-highway dump truck. An average of five fatalities occur each year in surface mines as a result of an equipment operator not being aware of a smaller vehicle, person or change in terrain near the equipment. Sensor technology that can detect such obstacles and that also is designed for surface mining applications is rare. Researchers worked closely with the radar system manufacturer to test and modify the system on large, off-highway dump trucks at a surface mine over a period of 2 years. The final system was thoroughly evaluated by recording video images from a camera on the rear of the truck and by recording all alarms from the rear-mounted radar. Data show that the system reliably detected small vehicles, berms, people and other equipment. However, alarms from objects that posed no immediate danger were common, supporting the assertion that sensor-based systems for proximity warning should be used in combination with other devices, such as cameras, that would allow the operator to check the source of any alarm.

Rapid response radiation sensors for homeland security applications

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Sanjoy; Maurer, Richard; Guss, Paul

2014-09-01

The National Security Technologies, LLC, Remote Sensing Laboratory is developing a rapid response radiation detection system for homeland security field applications. The intelligence-driven system is deployed only when non-radiological information about the target is verifiable. The survey area is often limited, so the detection range is small; in most cases covering a distance of 10 meters or less suffices. Definitive response is required in no more than 3 seconds and should minimize false negative alarms, but can err on the side of positive false alarms. The detection system is rapidly reconfigurable in terms of size, shape, and outer appearance; it is a plug-and-play system. Multiple radiation detection components (viz., two or more sodium iodide scintillators) are used to independently "over-determine" the existence of the threat object. Rapid response electronic dose rate meters are also included in the equipment suite. Carefully studied threat signatures are the basis of the decision making. The use of Rad-Detect predictive modeling provides information on the nature of the threat object. Rad-Detect provides accurate dose rate from heavily shielded large sources; for example those lost in Mexico were Category 1 radiation sources (~3,000 Ci of 60Co), the most dangerous of five categories defined by the International Atomic Energy Agency. Taken out of their shielding containers, Category 1 sources can kill anyone who is exposed to them at close range for a few minutes to an hour. Whenever possible sub-second data acquisition will be attempted, and, when deployed, the system will be characterized for false alarm rates. Although the radiation detection materials selected are fast (viz., faster scintillators), their speed is secondary to sensitivity, which is of primary importance. Results from these efforts will be discussed and demonstrated.

The image enhancement and region of interest extraction of lobster-eye X-ray dangerous material inspection system

NASA Astrophysics Data System (ADS)

Zhan, Qi; Wang, Xin; Mu, Baozhong; Xu, Jie; Xie, Qing; Li, Yaran; Chen, Yifan; He, Yanan

2016-10-01

Dangerous materials inspection is an important technique to confirm dangerous materials crimes. It has significant impact on the prohibition of dangerous materials-related crimes and the spread of dangerous materials. Lobster-Eye Optical Imaging System is a kind of dangerous materials detection device which mainly takes advantage of backscatter X-ray. The strength of the system is its applicability to access only one side of an object, and to detect dangerous materials without disturbing the surroundings of the target material. The device uses Compton scattered x-rays to create computerized outlines of suspected objects during security detection process. Due to the grid structure of the bionic object glass, which imitate the eye of a lobster, grids contribute to the main image noise during the imaging process. At the same time, when used to inspect structured or dense materials, the image is plagued by superposition artifacts and limited by attenuation and noise. With the goal of achieving high quality images which could be used for dangerous materials detection and further analysis, we developed effective image process methods applied to the system. The first aspect of the image process is the denoising and enhancing edge contrast process, during the process, we apply deconvolution algorithm to remove the grids and other noises. After image processing, we achieve high signal-to-noise ratio image. The second part is to reconstruct image from low dose X-ray exposure condition. We developed a kind of interpolation method to achieve the goal. The last aspect is the region of interest (ROI) extraction process, which could be used to help identifying dangerous materials mixed with complex backgrounds. The methods demonstrated in the paper have the potential to improve the sensitivity and quality of x-ray backscatter system imaging.

The Whipple Mission: Exploring the Kuiper Belt and the Oort Cloud

NASA Astrophysics Data System (ADS)

Holman, Matthew J.; Alcock, Charles; Kenter, Almus T.; Kraft, Ralph P.; Nulsen, Paul; Payne, Matthew John; Vrtilek, Jan M.; Murray, Stephen S.; Murray-Clay, Ruth; Schlichting, Hilke; Brown, Michael E.; Livingston, John H.; Trangsrud, Amy R.; Werner, Michael W.

2015-01-01

Whipple will characterize the small body populations of the Kuiper Belt and the Oort Cloud with a blind occultation survey, detecting objects when they briefly (~1 second) interrupt the light from background stars, allowing the detection of much more distant and/or smaller objects than can be seen in reflected sunlight. Whipple will reach much deeper into the unexplored frontier of the outer solar system than any other mission, current or proposed. Whipple will look back to the dawn of the solar system by discovering its most remote bodies where primordial processes left their imprint.Specifically, Whipple will monitor large numbers of stars at high cadences (~12,000 stars at 20 Hz to examine Kuiper Belt events; as many as ~36,000 stars at 5 Hz to explore deep into the Oort Cloud, where events are less frequent). Analysis of the detected events will allow us to determine the size spectrum of bodies in the Kuiper Belt with radii as small as ~1 km. This will allow the testing of models of the growth and later collisional erosion of planetesimals in the earlysolar system. Whipple will explore the Oort Cloud, detecting objects as far out as ~10,000 AU. This will be the first direct exploration of the Oort Cloud since the original hypothesis of 1950.Whipple is a Discovery class mission that will be proposed to NASA in response to the upcoming Announcement of Opportunity. The mission is being developed jointly by the Smithsonian Astrophysical Observatory, Jet Propulsion Laboratory, and Ball Aerospace & Technologies, with telescope optics from L-3 Integrated Optical Systems.

The Whipple Mission: Exploring the Kuiper Belt and the Oort Cloud

NASA Astrophysics Data System (ADS)

Alcock, Charles; Brown, Michael; Gauron, Tom; Heneghan, Cate; Holman, Matthew; Kenter, Almus; Kraft, Ralph; Livingston, John; Murray, Stephen; Murray-Clay, Ruth; Nulsen, Paul; Payne, Matthew; Schlichting, Hilke; Trangsrud, Amy; Vrtilek, Jan; Werner, Michael

2014-11-01

Whipple will characterize the small body populations of the Kuiper Belt and the Oort Cloud with a blind occultation survey, detecting objects when they briefly 1 second) interrupt the light from background stars, allowing the detection of much more distant and/or smaller objects than can be seen in reflected sunlight. Whipple will reach much deeper into the unexplored frontier of the outer solar system than any other mission, current or proposed. Whipple will look back to the dawn of the solar system by discovering its most remote bodies where primordial processes left their imprint.Specifically, Whipple will monitor large numbers of stars at high cadences 12,000 stars at 20 Hz to examine Kuiper Belt events; as many as ~36,000 stars at 5 Hz to explore deep into the Oort Cloud, where events are less frequent). Analysis of the detected events will allow us to determine the size spectrum of bodies in the Kuiper Belt with radii as small as ~1 km. This will allow the testing of models of the growth and later collisional erosion of planetesimals in the early solar system. Whipple will explore the Oort Cloud, detecting objects as far out as ~10,000 AU. This will be the first direct exploration of the Oort Cloud since the original hypothesis of 1950.Whipple is a Discovery class mission that will be proposed to NASA in response to the 2014 Announcement of Opportunity. The mission is being developed jointly by the Smithsonian Astrophysical Observatory, Jet Propulsion Laboratories, and Ball Aerospace & Technologies, with telescope optics from L-3 Integrated Optical Systems.

The Whipple Mission: Exploring the Kuiper Belt and the Oort Cloud

NASA Astrophysics Data System (ADS)

Alcock, C.; Brown, M. E.; Gauron, T.; Heneghan, C.; Holman, M. J.; Kenter, A.; Kraft, R.; Lee, R.; Livingston, J.; Mcguire, J.; Murray, S. S.; Murray-Clay, R.; Nulsen, P.; Payne, M. J.; Schlichting, H.; Trangsrud, A.; Vrtilek, J.; Werner, M.

2014-12-01

Whipple will characterize the small body populations of the Kuiper Belt and the Oort Cloud with a blind occultation survey, detecting objects when they briefly (~1 second) interrupt the light from background stars, allowing the detection of much more distant and/or smaller objects than can be seen in reflected sunlight. Whipple will reach much deeper into the unexplored frontier of the outer solar system than any other mission, current or proposed. Whipple will look back to the dawn of the solar system by discovering its most remote bodies where primordial processes left their imprint. Specifically, Whipple will monitor large numbers of stars at high cadences (~12,000 stars at 20 Hz to examine Kuiper Belt events; as many as ~36,000 stars at 5 Hz to explore deep into the Oort Cloud, where events are less frequent). Analysis of the detected events will allow us to determine the size spectrum of bodies in the Kuiper Belt with radii as small as ~1 km. This will allow the testing of models of the growth and later collisional erosion of planetesimals in the early solar system. Whipple will explore the Oort Cloud, detecting objects as far out as ~10,000 AU. This will be the first direct exploration of the Oort Cloud since the original hypothesis of 1950. Whipple is a Discovery class mission that will be proposed to NASA in response to the 2014 Announcement of Opportunity. The mission is being developed jointly by the Smithsonian Astrophysical Observatory, Jet Propulsion Laboratories, and Ball Aerospace & Technologies, with telescope optics from L-3 Integrated Optical Systems.

Integrating obstacle avoidance, global path planning, visual cue detection, and landmark triangulation in a mobile robot

NASA Astrophysics Data System (ADS)

Kortenkamp, David; Huber, Marcus J.; Congdon, Clare B.; Huffman, Scott B.; Bidlack, Clint R.; Cohen, Charles J.; Koss, Frank V.; Raschke, Ulrich; Weymouth, Terry E.

1993-05-01

This paper describes the design and implementation of an integrated system for combining obstacle avoidance, path planning, landmark detection and position triangulation. Such an integrated system allows the robot to move from place to place in an environment, avoiding obstacles and planning its way out of traps, while maintaining its position and orientation using distinctive landmarks. The task the robot performs is to search a 22 m X 22 m arena for 10 distinctive objects, visiting each object in turn. This same task was recently performed by a dozen different robots at a competition in which the robot described in this paper finished first.

Fast and objective detection and analysis of structures in downhole images

NASA Astrophysics Data System (ADS)

Wedge, Daniel; Holden, Eun-Jung; Dentith, Mike; Spadaccini, Nick

2017-09-01

Downhole acoustic and optical televiewer images, and formation microimager (FMI) logs are important datasets for structural and geotechnical analyses for the mineral and petroleum industries. Within these data, dipping planar structures appear as sinusoids, often in incomplete form and in abundance. Their detection is a labour intensive and hence expensive task and as such is a significant bottleneck in data processing as companies may have hundreds of kilometres of logs to process each year. We present an image analysis system that harnesses the power of automated image analysis and provides an interactive user interface to support the analysis of televiewer images by users with different objectives. Our algorithm rapidly produces repeatable, objective results. We have embedded it in an interactive workflow to complement geologists' intuition and experience in interpreting data to improve efficiency and assist, rather than replace the geologist. The main contributions include a new image quality assessment technique for highlighting image areas most suited to automated structure detection and for detecting boundaries of geological zones, and a novel sinusoid detection algorithm for detecting and selecting sinusoids with given confidence levels. Further tools are provided to perform rapid analysis of and further detection of structures e.g. as limited to specific orientations.

Automatic concrete cracks detection and mapping of terrestrial laser scan data

NASA Astrophysics Data System (ADS)

Rabah, Mostafa; Elhattab, Ahmed; Fayad, Atef

2013-12-01

Terrestrial laser scanning has become one of the standard technologies for object acquisition in surveying engineering. The high spatial resolution of imaging and the excellent capability of measuring the 3D space by laser scanning bear a great potential if combined for both data acquisition and data compilation. Automatic crack detection from concrete surface images is very effective for nondestructive testing. The crack information can be used to decide the appropriate rehabilitation method to fix the cracked structures and prevent any catastrophic failure. In practice, cracks on concrete surfaces are traced manually for diagnosis. On the other hand, automatic crack detection is highly desirable for efficient and objective crack assessment. The current paper submits a method for automatic concrete cracks detection and mapping from the data that was obtained during laser scanning survey. The method of cracks detection and mapping is achieved by three steps, namely the step of shading correction in the original image, step of crack detection and finally step of crack mapping and processing steps. The detected crack is defined in a pixel coordinate system. To remap the crack into the referred coordinate system, a reverse engineering is used. This is achieved by a hybrid concept of terrestrial laser-scanner point clouds and the corresponding camera image, i.e. a conversion from the pixel coordinate system to the terrestrial laser-scanner or global coordinate system. The results of the experiment show that the mean differences between terrestrial laser scan and the total station are about 30.5, 16.4 and 14.3 mms in x, y and z direction, respectively.

Melon yield prediction using small unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Zhao, Tiebiao; Wang, Zhongdao; Yang, Qi; Chen, YangQuan

2017-05-01

Thanks to the development of camera technologies, small unmanned aerial systems (sUAS), it is possible to collect aerial images of field with more flexible visit, higher resolution and much lower cost. Furthermore, the performance of objection detection based on deeply trained convolutional neural networks (CNNs) has been improved significantly. In this study, we applied these technologies in the melon production, where high-resolution aerial images were used to count melons in the field and predict the yield. CNN-based object detection framework-Faster R-CNN is applied in the melon classification. Our results showed that sUAS plus CNNs were able to detect melons accurately in the late harvest season.

Design and development of electrical impedance tomography system with 32 electrodes and microcontroller

NASA Astrophysics Data System (ADS)

Ansory, Achmad; Prajitno, Prawito; Wijaya, Sastra Kusuma

2018-02-01

Electrical Impedance Tomography (EIT) is an imaging method that is able to estimate electrical impedance distribution inside an object. This EIT system is developed by using 32 electrodes and microcontroller based module. From a pair of electrodes, sinusoidal current of 3 mA is injected and the voltage differences between other pairs of electrodes are measured. Voltage measurement data are then sent to MATLAB and EIDORS software; the data are used to reconstruct two dimensions image. The system can detect and determine the position of a phantom in the tank. The object's position is accurately reconstructed and determined with the average shifting of 0.69 cm but object's area cannot be accurately reconstructed. The object's image is more accurately reconstructed when the object is located near to electrodes, has a larger size, and when the current injected to the system has a frequency of 100 kHz or 200kHz.

Multisensor data fusion for IED threat detection

NASA Astrophysics Data System (ADS)

Mees, Wim; Heremans, Roel

2012-10-01

In this paper we present the multi-sensor registration and fusion algorithms that were developed for a force protection research project in order to detect threats against military patrol vehicles. The fusion is performed at object level, using a hierarchical evidence aggregation approach. It first uses expert domain knowledge about the features used to characterize the detected threats, that is implemented in the form of a fuzzy expert system. The next level consists in fusing intra-sensor and inter-sensor information. Here an ordered weighted averaging operator is used. The object level fusion between candidate threats that are detected asynchronously on a moving vehicle by sensors with different imaging geometries, requires an accurate sensor to world coordinate transformation. This image registration will also be discussed in this paper.

Directed area search using socio-biological vision algorithms and cognitive Bayesian reasoning

NASA Astrophysics Data System (ADS)

Medasani, S.; Owechko, Y.; Allen, D.; Lu, T. C.; Khosla, D.

2010-04-01

Volitional search systems that assist the analyst by searching for specific targets or objects such as vehicles, factories, airports, etc in wide area overhead imagery need to overcome multiple problems present in current manual and automatic approaches. These problems include finding targets hidden in terabytes of information, relatively few pixels on targets, long intervals between interesting regions, time consuming analysis requiring many analysts, no a priori representative examples or templates of interest, detecting multiple classes of objects, and the need for very high detection rates and very low false alarm rates. This paper describes a conceptual analyst-centric framework that utilizes existing technology modules to search and locate occurrences of targets of interest (e.g., buildings, mobile targets of military significance, factories, nuclear plants, etc.), from video imagery of large areas. Our framework takes simple queries from the analyst and finds the queried targets with relatively minimum interaction from the analyst. It uses a hybrid approach that combines biologically inspired bottom up attention, socio-biologically inspired object recognition for volitionally recognizing targets, and hierarchical Bayesian networks for modeling and representing the domain knowledge. This approach has the benefits of high accuracy, low false alarm rate and can handle both low-level visual information and high-level domain knowledge in a single framework. Such a system would be of immense help for search and rescue efforts, intelligence gathering, change detection systems, and other surveillance systems.

Robust real-time horizon detection in full-motion video

NASA Astrophysics Data System (ADS)

Young, Grace B.; Bagnall, Bryan; Lane, Corey; Parameswaran, Shibin

2014-06-01

The ability to detect the horizon on a real-time basis in full-motion video is an important capability to aid and facilitate real-time processing of full-motion videos for the purposes such as object detection, recognition and other video/image segmentation applications. In this paper, we propose a method for real-time horizon detection that is designed to be used as a front-end processing unit for a real-time marine object detection system that carries out object detection and tracking on full-motion videos captured by ship/harbor-mounted cameras, Unmanned Aerial Vehicles (UAVs) or any other method of surveillance for Maritime Domain Awareness (MDA). Unlike existing horizon detection work, we cannot assume a priori the angle or nature (for e.g. straight line) of the horizon, due to the nature of the application domain and the data. Therefore, the proposed real-time algorithm is designed to identify the horizon at any angle and irrespective of objects appearing close to and/or occluding the horizon line (for e.g. trees, vehicles at a distance) by accounting for its non-linear nature. We use a simple two-stage hierarchical methodology, leveraging color-based features, to quickly isolate the region of the image containing the horizon and then perform a more ne-grained horizon detection operation. In this paper, we present our real-time horizon detection results using our algorithm on real-world full-motion video data from a variety of surveillance sensors like UAVs and ship mounted cameras con rming the real-time applicability of this method and its ability to detect horizon with no a priori assumptions.

The what, where and how of auditory-object perception

PubMed Central

Bizley, Jennifer K.; Cohen, Yale E.

2014-01-01

The fundamental perceptual unit in hearing is the ‘auditory object’. Similar to visual objects, auditory objects are the computational result of the auditory system's capacity to detect, extract, segregate and group spectrotemporal regularities in the acoustic environment; the multitude of acoustic stimuli around us together form the auditory scene. However, unlike the visual scene, resolving the component objects within the auditory scene crucially depends on their temporal structure. Neural correlates of auditory objects are found throughout the auditory system. However, neural responses do not become correlated with a listener's perceptual reports until the level of the cortex. The roles of different neural structures and the contribution of different cognitive states to the perception of auditory objects are not yet fully understood. PMID:24052177

Objective Properties from Subjective Quantum States: Environment as a Witness

NASA Astrophysics Data System (ADS)

Ollivier, Harold; Poulin, David; Zurek, Wojciech H.

2004-11-01

We study the emergence of objective properties in open quantum systems. In our analysis, the environment is promoted from a passive role of a reservoir selectively destroying quantum coherence to an active role of amplifier selectively proliferating information about the system. We show that only preferred pointer states of the system can leave a redundant and therefore easily detectable imprint on the environment. Observers who—as is almost always the case—discover the state of the system indirectly (by probing a fraction of its environment) will find out only about the corresponding pointer observable. Many observers can act in this fashion independently and without perturbing the system. They will agree about its state. In this operational sense, preferred pointer states exist objectively.

The simulation study on optical target laser active detection performance

NASA Astrophysics Data System (ADS)

Li, Ying-chun; Hou, Zhao-fei; Fan, Youchen

2014-12-01

According to the working principle of laser active detection system, the paper establishes the optical target laser active detection simulation system, carry out the simulation study on the detection process and detection performance of the system. For instance, the performance model such as the laser emitting, the laser propagation in the atmosphere, the reflection of optical target, the receiver detection system, the signal processing and recognition. We focus on the analysis and modeling the relationship between the laser emitting angle and defocus amount and "cat eye" effect echo laser in the reflection of optical target. Further, in the paper some performance index such as operating range, SNR and the probability of the system have been simulated. The parameters including laser emitting parameters, the reflection of the optical target and the laser propagation in the atmosphere which make a great influence on the performance of the optical target laser active detection system. Finally, using the object-oriented software design methods, the laser active detection system with the opening type, complete function and operating platform, realizes the process simulation that the detection system detect and recognize the optical target, complete the performance simulation of each subsystem, and generate the data report and the graph. It can make the laser active detection system performance models more intuitive because of the visible simulation process. The simulation data obtained from the system provide a reference to adjust the structure of the system parameters. And it provides theoretical and technical support for the top level design of the optical target laser active detection system and performance index optimization.

Laser radar system for obstacle avoidance

NASA Astrophysics Data System (ADS)

Bers, Karlheinz; Schulz, Karl R.; Armbruster, Walter

2005-09-01

The threat of hostile surveillance and weapon systems require military aircraft to fly under extreme conditions such as low altitude, high speed, poor visibility and incomplete terrain information. The probability of collision with natural and man-made obstacles during such contour missions is high if detection capability is restricted to conventional vision aids. Forward-looking scanning laser radars which are build by the EADS company and presently being flight tested and evaluated at German proving grounds, provide a possible solution, having a large field of view, high angular and range resolution, a high pulse repetition rate, and sufficient pulse energy to register returns from objects at distances of military relevance with a high hit-and-detect probability. The development of advanced 3d-scene analysis algorithms had increased the recognition probability and reduced the false alarm rate by using more readily recognizable objects such as terrain, poles, pylons, trees, etc. to generate a parametric description of the terrain surface as well as the class, position, orientation, size and shape of all objects in the scene. The sensor system and the implemented algorithms can be used for other applications such as terrain following, autonomous obstacle avoidance, and automatic target recognition. This paper describes different 3D-imaging ladar sensors with unique system architecture but different components matched for different military application. Emphasis is laid on an obstacle warning system with a high probability of detection of thin wires, the real time processing of the measured range image data, obstacle classification und visualization.

Marginal space learning for efficient detection of 2D/3D anatomical structures in medical images.

PubMed

Zheng, Yefeng; Georgescu, Bogdan; Comaniciu, Dorin

2009-01-01

Recently, marginal space learning (MSL) was proposed as a generic approach for automatic detection of 3D anatomical structures in many medical imaging modalities [1]. To accurately localize a 3D object, we need to estimate nine pose parameters (three for position, three for orientation, and three for anisotropic scaling). Instead of exhaustively searching the original nine-dimensional pose parameter space, only low-dimensional marginal spaces are searched in MSL to improve the detection speed. In this paper, we apply MSL to 2D object detection and perform a thorough comparison between MSL and the alternative full space learning (FSL) approach. Experiments on left ventricle detection in 2D MRI images show MSL outperforms FSL in both speed and accuracy. In addition, we propose two novel techniques, constrained MSL and nonrigid MSL, to further improve the efficiency and accuracy. In many real applications, a strong correlation may exist among pose parameters in the same marginal spaces. For example, a large object may have large scaling values along all directions. Constrained MSL exploits this correlation for further speed-up. The original MSL only estimates the rigid transformation of an object in the image, therefore cannot accurately localize a nonrigid object under a large deformation. The proposed nonrigid MSL directly estimates the nonrigid deformation parameters to improve the localization accuracy. The comparison experiments on liver detection in 226 abdominal CT volumes demonstrate the effectiveness of the proposed methods. Our system takes less than a second to accurately detect the liver in a volume.

Moving Object Control System

NASA Technical Reports Server (NTRS)

Arndt, G. Dickey (Inventor); Carl, James R. (Inventor)

2001-01-01

A method is provided for controlling two objects relatively moveable with respect to each other. A plurality of receivers are provided for detecting a distinctive microwave signal from each of the objects and measuring the phase thereof with respect to a reference signal. The measured phase signal is used to determine a distance between each of the objects and each of the plurality of receivers. Control signals produced in response to the relative distances are used to control the position of the two objects.

Collision detection in complex dynamic scenes using an LGMD-based visual neural network with feature enhancement.

PubMed

Yue, Shigang; Rind, F Claire

2006-05-01

The lobula giant movement detector (LGMD) is an identified neuron in the locust brain that responds most strongly to the images of an approaching object such as a predator. Its computational model can cope with unpredictable environments without using specific object recognition algorithms. In this paper, an LGMD-based neural network is proposed with a new feature enhancement mechanism to enhance the expanded edges of colliding objects via grouped excitation for collision detection with complex backgrounds. The isolated excitation caused by background detail will be filtered out by the new mechanism. Offline tests demonstrated the advantages of the presented LGMD-based neural network in complex backgrounds. Real time robotics experiments using the LGMD-based neural network as the only sensory system showed that the system worked reliably in a wide range of conditions; in particular, the robot was able to navigate in arenas with structured surrounds and complex backgrounds.

Doublet Pulse Coherent Laser Radar for Tracking of Resident Space Objects

NASA Technical Reports Server (NTRS)

Prasad, Narasimha S.; Rudd, Van; Shald, Scott; Sandford, Stephen; Dimarcantonio, Albert

2014-01-01

In this paper, the development of a long range ladar system known as ExoSPEAR at NASA Langley Research Center for tracking rapidly moving resident space objects is discussed. Based on 100 W, nanosecond class, near-IR laser, this ladar system with coherent detection technique is currently being investigated for short dwell time measurements of resident space objects (RSOs) in LEO and beyond for space surveillance applications. This unique ladar architecture is configured using a continuously agile doublet-pulse waveform scheme coupled to a closed-loop tracking and control loop approach to simultaneously achieve mm class range precision and mm/s velocity precision and hence obtain unprecedented track accuracies. Salient features of the design architecture followed by performance modeling and engagement simulations illustrating the dependence of range and velocity precision in LEO orbits on ladar parameters are presented. Estimated limits on detectable optical cross sections of RSOs in LEO orbits are discussed.

Advanced Opto-Electronics (LIDAR and Microsensor Development)

NASA Technical Reports Server (NTRS)

Vanderbilt, Vern C. (Technical Monitor); Spangler, Lee H.

2005-01-01

Our overall intent in this aspect of the project were to establish a collaborative effort between several departments at Montana State University for developing advanced optoelectronic technology for advancing the state-of-the-art in optical remote sensing of the environment. Our particular focus was on development of small systems that can eventually be used in a wide variety of applications that might include ground-, air-, and space deployments, possibly in sensor networks. Specific objectives were to: 1) Build a field-deployable direct-detection lidar system for use in measurements of clouds, aerosols, fish, and vegetation; 2) Develop a breadboard prototype water vapor differential absorption lidar (DIAL) system based on highly stable, tunable diode laser technology developed previously at MSU. We accomplished both primary objectives of this project, in developing a field-deployable direct-detection lidar and a breadboard prototype of a water vapor DIAL system. Paper summarizes each of these accomplishments.

On resilience studies of system detection and recovery techniques against stealthy insider attacks

NASA Astrophysics Data System (ADS)

Wei, Sixiao; Zhang, Hanlin; Chen, Genshe; Shen, Dan; Yu, Wei; Pham, Khanh D.; Blasch, Erik P.; Cruz, Jose B.

2016-05-01

With the explosive growth of network technologies, insider attacks have become a major concern to business operations that largely rely on computer networks. To better detect insider attacks that marginally manipulate network traffic over time, and to recover the system from attacks, in this paper we implement a temporal-based detection scheme using the sequential hypothesis testing technique. Two hypothetical states are considered: the null hypothesis that the collected information is from benign historical traffic and the alternative hypothesis that the network is under attack. The objective of such a detection scheme is to recognize the change within the shortest time by comparing the two defined hypotheses. In addition, once the attack is detected, a server migration-based system recovery scheme can be triggered to recover the system to the state prior to the attack. To understand mitigation of insider attacks, a multi-functional web display of the detection analysis was developed for real-time analytic. Experiments using real-world traffic traces evaluate the effectiveness of Detection System and Recovery (DeSyAR) scheme. The evaluation data validates the detection scheme based on sequential hypothesis testing and the server migration-based system recovery scheme can perform well in effectively detecting insider attacks and recovering the system under attack.

A combined system for 3D printing cybersecurity

NASA Astrophysics Data System (ADS)

Straub, Jeremy

2017-06-01

Previous work has discussed the impact of cybersecurity breaches on 3D printed objects. Multiple attack types that could weaken objects, make them unsuitable for certain applications and even create safety hazards have been presented. This paper considers a visible light sensing-based verification system's efficacy as a means of thwarting cybersecurity threats to 3D printing. This system detects discrepancies between expected and actual printed objects (based on an independent pristine CAD model). Whether reliance on an independent CAD model is appropriate is also considered. The future of 3D printing is projected and the importance of cybersecurity in this future is discussed.

Detecting Heap-Spraying Code Injection Attacks in Malicious Web Pages Using Runtime Execution

NASA Astrophysics Data System (ADS)

Choi, Younghan; Kim, Hyoungchun; Lee, Donghoon

The growing use of web services is increasing web browser attacks exponentially. Most attacks use a technique called heap spraying because of its high success rate. Heap spraying executes a malicious code without indicating the exact address of the code by copying it into many heap objects. For this reason, the attack has a high potential to succeed if only the vulnerability is exploited. Thus, attackers have recently begun using this technique because it is easy to use JavaScript to allocate the heap memory area. This paper proposes a novel technique that detects heap spraying attacks by executing a heap object in a real environment, irrespective of the version and patch status of the web browser. This runtime execution is used to detect various forms of heap spraying attacks, such as encoding and polymorphism. Heap objects are executed after being filtered on the basis of patterns of heap spraying attacks in order to reduce the overhead of the runtime execution. Patterns of heap spraying attacks are based on analysis of how an web browser accesses benign web sites. The heap objects are executed forcibly by changing the instruction register into the address of them after being loaded into memory. Thus, we can execute the malicious code without having to consider the version and patch status of the browser. An object is considered to contain a malicious code if the execution reaches a call instruction and then the instruction accesses the API of system libraries, such as kernel32.dll and ws_32.dll. To change registers and monitor execution flow, we used a debugger engine. A prototype, named HERAD(HEap spRAying Detector), is implemented and evaluated. In experiments, HERAD detects various forms of exploit code that an emulation cannot detect, and some heap spraying attacks that NOZZLE cannot detect. Although it has an execution overhead, HERAD produces a low number of false alarms. The processing time of several minutes is negligible because our research focuses on detecting heap spraying. This research can be applied to existing systems that collect malicious codes, such as Honeypot.

Towards a low-cost mobile subcutaneous vein detection solution using near-infrared spectroscopy.

PubMed

Juric, Simon; Flis, Vojko; Debevc, Matjaz; Holzinger, Andreas; Zalik, Borut

2014-01-01

Excessive venipunctures are both time- and resource-consuming events, which cause anxiety, pain, and distress in patients, or can lead to severe harmful injuries. We propose a low-cost mobile health solution for subcutaneous vein detection using near-infrared spectroscopy, along with an assessment of the current state of the art in this field. The first objective of this study was to get a deeper overview of the research topic, through the initial team discussions and a detailed literature review (using both academic and grey literature). The second objective, that is, identifying the commercial systems employing near-infrared spectroscopy, was conducted using the PubMed database. The goal of the third objective was to identify and evaluate (using the IEEE Xplore database) the research efforts in the field of low-cost near-infrared imaging in general, as a basis for the conceptual model of the upcoming prototype. Although the reviewed commercial devices have demonstrated usefulness and value for peripheral veins visualization, other evaluated clinical outcomes are less conclusive. Previous studies regarding low-cost near-infrared systems demonstrated the general feasibility of developing cost-effective vein detection systems; however, their limitations are restricting their applicability to clinical practice. Finally, based on the current findings, we outline the future research direction.

Aspects of image recognition in Vivid Technologies' dual-energy x-ray system for explosives detection

NASA Astrophysics Data System (ADS)

Eilbert, Richard F.; Krug, Kristoph D.

1993-04-01

The Vivid Rapid Explosives Detection Systems is a true dual energy x-ray machine employing precision x-ray data acquisition in combination with unique algorithms and massive computation capability. Data from the system's 960 detectors is digitally stored and processed by powerful supermicro-computers organized as an expandable array of parallel processors. The algorithms operate on the dual energy attenuation image data to recognize and define objects in the milieu of the baggage contents. Each object is then systematically examined for a match to a specific effective atomic number, density, and mass threshold. Material properties are determined by comparing the relative attenuations of the 75 kVp and 150 kVp beams and electronically separating the object from its local background. Other heuristic algorithms search for specific configurations and provide additional information. The machine automatically detects explosive materials and identifies bomb components in luggage with high specificity and throughput, X-ray dose is comparable to that of current airport x-ray machines. The machine is also configured to find heroin, cocaine, and US currency by selecting appropriate settings on-site. Since January 1992, production units have been operationally deployed at U.S. and European airports for improved screening of checked baggage.

Towards a Low-Cost Mobile Subcutaneous Vein Detection Solution Using Near-Infrared Spectroscopy

PubMed Central

Flis, Vojko; Debevc, Matjaz; Holzinger, Andreas; Zalik, Borut

2014-01-01

Excessive venipunctures are both time- and resource-consuming events, which cause anxiety, pain, and distress in patients, or can lead to severe harmful injuries. We propose a low-cost mobile health solution for subcutaneous vein detection using near-infrared spectroscopy, along with an assessment of the current state of the art in this field. The first objective of this study was to get a deeper overview of the research topic, through the initial team discussions and a detailed literature review (using both academic and grey literature). The second objective, that is, identifying the commercial systems employing near-infrared spectroscopy, was conducted using the PubMed database. The goal of the third objective was to identify and evaluate (using the IEEE Xplore database) the research efforts in the field of low-cost near-infrared imaging in general, as a basis for the conceptual model of the upcoming prototype. Although the reviewed commercial devices have demonstrated usefulness and value for peripheral veins visualization, other evaluated clinical outcomes are less conclusive. Previous studies regarding low-cost near-infrared systems demonstrated the general feasibility of developing cost-effective vein detection systems; however, their limitations are restricting their applicability to clinical practice. Finally, based on the current findings, we outline the future research direction. PMID:24883388

Optical tweezers based force measurement system for quantitating binding interactions: system design and application for the study of bacterial adhesion.

PubMed

Fällman, Erik; Schedin, Staffan; Jass, Jana; Andersson, Magnus; Uhlin, Bernt Eric; Axner, Ove

2004-06-15

An optical force measurement system for quantitating forces in the pN range between micrometer-sized objects has been developed. The system was based upon optical tweezers in combination with a sensitive position detection system and constructed around an inverted microscope. A trapped particle in the focus of the high numerical aperture microscope-objective behaves like an omnidirectional mechanical spring in response to an external force. The particle's displacement from the equilibrium position is therefore a direct measure of the exerted force. A weak probe laser beam, focused directly below the trapping focus, was used for position detection of the trapped particle (a polystyrene bead). The bead and the condenser focus the light to a distinct spot in the far field, monitored by a position sensitive detector. Various calibration procedures were implemented in order to provide absolute force measurements. The system has been used to measure the binding forces between Escherichia coli bacterial adhesins and galabiose-functionalized beads.

Connecting a cognitive architecture to robotic perception

NASA Astrophysics Data System (ADS)

Kurup, Unmesh; Lebiere, Christian; Stentz, Anthony; Hebert, Martial

2012-06-01

We present an integrated architecture in which perception and cognition interact and provide information to each other leading to improved performance in real-world situations. Our system integrates the Felzenswalb et. al. object-detection algorithm with the ACT-R cognitive architecture. The targeted task is to predict and classify pedestrian behavior in a checkpoint scenario, most specifically to discriminate between normal versus checkpoint-avoiding behavior. The Felzenswalb algorithm is a learning-based algorithm for detecting and localizing objects in images. ACT-R is a cognitive architecture that has been successfully used to model human cognition with a high degree of fidelity on tasks ranging from basic decision-making to the control of complex systems such as driving or air traffic control. The Felzenswalb algorithm detects pedestrians in the image and provides ACT-R a set of features based primarily on their locations. ACT-R uses its pattern-matching capabilities, specifically its partial-matching and blending mechanisms, to track objects across multiple images and classify their behavior based on the sequence of observed features. ACT-R also provides feedback to the Felzenswalb algorithm in the form of expected object locations that allow the algorithm to eliminate false-positives and improve its overall performance. This capability is an instance of the benefits pursued in developing a richer interaction between bottom-up perceptual processes and top-down goal-directed cognition. We trained the system on individual behaviors (only one person in the scene) and evaluated its performance across single and multiple behavior sets.

Content-based unconstrained color logo and trademark retrieval with color edge gradient co-occurrence histograms

NASA Astrophysics Data System (ADS)

Phan, Raymond; Androutsos, Dimitrios

2008-01-01

In this paper, we present a logo and trademark retrieval system for unconstrained color image databases that extends the Color Edge Co-occurrence Histogram (CECH) object detection scheme. We introduce more accurate information to the CECH, by virtue of incorporating color edge detection using vector order statistics. This produces a more accurate representation of edges in color images, in comparison to the simple color pixel difference classification of edges as seen in the CECH. Our proposed method is thus reliant on edge gradient information, and as such, we call this the Color Edge Gradient Co-occurrence Histogram (CEGCH). We use this as the main mechanism for our unconstrained color logo and trademark retrieval scheme. Results illustrate that the proposed retrieval system retrieves logos and trademarks with good accuracy, and outperforms the CECH object detection scheme with higher precision and recall.

GASPS--A Herschel Survey of Gas and Dust in Protoplanetary Disks: Summary and Initial Statistics

NASA Technical Reports Server (NTRS)

Dent, W.R.F.; Thi, W. F.; Kamp, I.; Williams, J. P.; Menard, F.; Andrews, S.; Ardila, D.; Aresu, G.; Augereau, J.-C.; Barrado y Navascues, D.;

Moving Object Detection Using Scanning Camera on a High-Precision Intelligent Holder.

PubMed

Chen, Shuoyang; Xu, Tingfa; Li, Daqun; Zhang, Jizhou; Jiang, Shenwang

2016-10-21

During the process of moving object detection in an intelligent visual surveillance system, a scenario with complex background is sure to appear. The traditional methods, such as "frame difference" and "optical flow", may not able to deal with the problem very well. In such scenarios, we use a modified algorithm to do the background modeling work. In this paper, we use edge detection to get an edge difference image just to enhance the ability of resistance illumination variation. Then we use a "multi-block temporal-analyzing LBP (Local Binary Pattern)" algorithm to do the segmentation. In the end, a connected component is used to locate the object. We also produce a hardware platform, the core of which consists of the DSP (Digital Signal Processor) and FPGA (Field Programmable Gate Array) platforms and the high-precision intelligent holder.

Lymph node detection in IASLC-defined zones on PET/CT images

NASA Astrophysics Data System (ADS)

Song, Yihua; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Torigian, Drew A.

2016-03-01

Lymph node detection is challenging due to the low contrast between lymph nodes as well as surrounding soft tissues and the variation in nodal size and shape. In this paper, we propose several novel ideas which are combined into a system to operate on positron emission tomography/ computed tomography (PET/CT) images to detect abnormal thoracic nodes. First, our previous Automatic Anatomy Recognition (AAR) approach is modified where lymph node zones predominantly following International Association for the Study of Lung Cancer (IASLC) specifications are modeled as objects arranged in a hierarchy along with key anatomic anchor objects. This fuzzy anatomy model built from diagnostic CT images is then deployed on PET/CT images for automatically recognizing the zones. A novel globular filter (g-filter) to detect blob-like objects over a specified range of sizes is designed to detect the most likely locations and sizes of diseased nodes. Abnormal nodes within each automatically localized zone are subsequently detected via combined use of different items of information at various scales: lymph node zone model poses found at recognition indicating the geographic layout at the global level of node clusters, g-filter response which hones in on and carefully selects node-like globular objects at the node level, and CT and PET gray value but within only the most plausible nodal regions for node presence at the voxel level. The models are built from 25 diagnostic CT scans and refined for an object hierarchy based on a separate set of 20 diagnostic CT scans. Node detection is tested on an additional set of 20 PET/CT scans. Our preliminary results indicate node detection sensitivity and specificity at around 90% and 85%, respectively.

Object detection in cinematographic video sequences for automatic indexing

NASA Astrophysics Data System (ADS)

Stauder, Jurgen; Chupeau, Bertrand; Oisel, Lionel

2003-06-01

This paper presents an object detection framework applied to cinematographic post-processing of video sequences. Post-processing is done after production and before editing. At the beginning of each shot of a video, a slate (also called clapperboard) is shown. The slate contains notably an electronic audio timecode that is necessary for audio-visual synchronization. This paper presents an object detection framework to detect slates in video sequences for automatic indexing and post-processing. It is based on five steps. The first two steps aim to reduce drastically the video data to be analyzed. They ensure high recall rate but have low precision. The first step detects images at the beginning of a shot possibly showing up a slate while the second step searches in these images for candidates regions with color distribution similar to slates. The objective is to not miss any slate while eliminating long parts of video without slate appearance. The third and fourth steps are statistical classification and pattern matching to detected and precisely locate slates in candidate regions. These steps ensure high recall rate and high precision. The objective is to detect slates with very little false alarms to minimize interactive corrections. In a last step, electronic timecodes are read from slates to automize audio-visual synchronization. The presented slate detector has a recall rate of 89% and a precision of 97,5%. By temporal integration, much more than 89% of shots in dailies are detected. By timecode coherence analysis, the precision can be raised too. Issues for future work are to accelerate the system to be faster than real-time and to extend the framework for several slate types.

Application of Laser Imaging for Bio/geophysical Studies

NASA Technical Reports Server (NTRS)

Hummel, J. R.; Goltz, S. M.; Depiero, N. L.; Degloria, D. P.; Pagliughi, F. M.

1992-01-01

SPARTA, Inc. has developed a low-cost, portable laser imager that, among other applications, can be used in bio/geophysical applications. In the application to be discussed here, the system was utilized as an imaging system for background features in a forested locale. The SPARTA mini-ladar system was used at the International Paper Northern Experimental Forest near Howland, Maine to assist in a project designed to study the thermal and radiometric phenomenology at forest edges. The imager was used to obtain data from three complex sites, a 'seed' orchard, a forest edge, and a building. The goal of the study was to demonstrate the usefulness of the laser imager as a tool to obtain geometric and internal structure data about complex 3-D objects in a natural background. The data from these images have been analyzed to obtain information about the distributions of the objects in a scene. A range detection algorithm has been used to identify individual objects in a laser image and an edge detection algorithm then applied to highlight the outlines of discrete objects. An example of an image processed in such a manner is shown. Described here are the results from the study. In addition, results are presented outlining how the laser imaging system could be used to obtain other important information about bio/geophysical systems, such as the distribution of woody material in forests.

Microscopy using source and detector arrays

NASA Astrophysics Data System (ADS)

Sheppard, Colin J. R.; Castello, Marco; Vicidomini, Giuseppe; Duocastella, Martí; Diaspro, Alberto

2016-03-01

There are basically two types of microscope, which we call conventional and scanning. The former type is a full-field imaging system. In the latter type, the object is illuminated with a probe beam, and a signal detected. We can generalize the probe to a patterned illumination. Similarly we can generalize the detection to a patterned detection. Combining these we get a range of different modalities: confocal microscopy, structured illumination (with full-field imaging), spinning disk (with multiple illumination points), and so on. The combination allows the spatial frequency bandwidth of the system to be doubled. In general we can record a four dimensional (4D) image of a 2D object (or a 6D image from a 3D object, using an acoustic tuneable lens). The optimum way to directly reconstruct the resulting image is by image scanning microscopy (ISM). But the 4D image is highly redundant, so deconvolution-based approaches are also relevant. ISM can be performed in fluorescence, bright field or interference microscopy. Several different implementations have been described, with associated advantages and disadvantages. In two-photon microscopy, the illumination and detection point spread functions are very different. This is also the case when using pupil filters or when there is a large Stokes shift.

Multiple-modality program for standoff detection of roadside hazards

NASA Astrophysics Data System (ADS)

Williams, Kathryn; Middleton, Seth; Close, Ryan; Luke, Robert H.; Suri, Rajiv

2016-05-01

The U.S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD) is executing a program to assess the performance of a variety of sensor modalities for standoff detection of roadside explosive hazards. The program objective is to identify an optimal sensor or combination of fused sensors to incorporate with autonomous detection algorithms into a system of systems for use in future route clearance operations. This paper provides an overview of the program, including a description of the sensors under consideration, sensor test events, and ongoing data analysis.

Obscenity detection using haar-like features and Gentle Adaboost classifier.

PubMed

Mustafa, Rashed; Min, Yang; Zhu, Dingju

2014-01-01

Large exposure of skin area of an image is considered obscene. This only fact may lead to many false images having skin-like objects and may not detect those images which have partially exposed skin area but have exposed erotogenic human body parts. This paper presents a novel method for detecting nipples from pornographic image contents. Nipple is considered as an erotogenic organ to identify pornographic contents from images. In this research Gentle Adaboost (GAB) haar-cascade classifier and haar-like features used for ensuring detection accuracy. Skin filter prior to detection made the system more robust. The experiment showed that, considering accuracy, haar-cascade classifier performs well, but in order to satisfy detection time, train-cascade classifier is suitable. To validate the results, we used 1198 positive samples containing nipple objects and 1995 negative images. The detection rates for haar-cascade and train-cascade classifiers are 0.9875 and 0.8429, respectively. The detection time for haar-cascade is 0.162 seconds and is 0.127 seconds for train-cascade classifier.

Terahertz imaging system for stand-off detection of threats

NASA Astrophysics Data System (ADS)

Hübers, H.-W.; Semenov, A. D.; Richter, H.; Böttger, U.

2007-04-01

Suicide bombers and hidden bombs or explosives have become serious threats especially for mass transportation. Until now there exists no established system which can be used against these threats. Therefore new technologies especially for stand-off detection of threats are required. Terahertz (THz) rays offer an alternative inspection method, which can cope with these new challenges. Major advantages of THz radiation as compared to other spectral regions are the possibility to penetrate through clothes and that THz radiation is not harmful for human health. In this report the design and results of a THz stand-off detection system will be presented. The sensor is based on active illumination of the object and sensitive heterodyne detection of reflected and backscattered radiation. The system operates at about 0.8 THz. A THz laser is used for illumination and a superconducting hot-electron bolometric mixer for detection. The local oscillator required for heterodyne detection is a multiplied microwave source. The optical system is designed to allow for stand-off detection at 20 m with a spatial resolution less than 2 cm.

Testing the system detection unit for measuring solid minerals bulk density

NASA Astrophysics Data System (ADS)

Voytyuk, I. N.; Kopteva, A. V.

2017-10-01

The paper provides a brief description of the system for measuring flux per volume of solid minerals via example of mineral coal. The paper discloses the operational principle of the detection unit. The paper provides full description of testing methodology, as well as practical implementation of the detection unit testing. This paper describes the removal of two data arrays via the channel of scattered anddirect radiation for the detection units of two generations. This paper describes Matlab software to determine the statistical characteristics of the studied objects. The mean value of pulses per cycles, and pulse counting inaccuracy relatively the mean value were determined for the calculation of the stability account of the detection units.

[Acoustic detection of absorption of millimeter-band electromagnetic waves in biological objects].

PubMed

Polnikov, I G; Putvinskiĭ, A V

1988-01-01

Principles of photoacoustic spectroscopy were applied to elaborate a new method for controlling millimeter electromagnetic waves absorption in biological objects. The method was used in investigations of frequency dependence of millimeter wave power absorption in vitro and in vivo in the commonly used experimental irradiation systems.

UXO Detection and Characterization using new Berkeley UXO Discriminator (BUD)

NASA Astrophysics Data System (ADS)

Gasperikova, E.; Morrison, H. F.; Smith, J. T.; Becker, A.

2006-05-01

An optimally designed active electromagnetic system (AEM), Berkeley UXO Discriminator, BUD, has been developed for detection and characterization of UXO in the 20 mm to 150 mm size range. The system incorporates three orthogonal transmitters, and eight pairs of differenced receivers. The transmitter-receiver assembly together with the acquisition box, as well as the battery power and GPS receiver, is mounted on a small cart to assure system mobility. BUD not only detects the object itself but also quantitatively determines its size, shape, orientation, and metal content (ferrous or non-ferrous, mixed metals). Moreover, the principal polarizabilities and size of a metallic target can be determined from a single position of the BUD platform. The search for UXO is a two-step process. The object must first be detected and its location determined then the parameters of the object must be defined. A satisfactory classification scheme is one that determines the principal dipole polarizabilities of a target. While UXO objects have a single major polarizability (principal moment) coincident with the long axis of the object and two equal transverse polarizabilities, the scrap metal has all three principal moments entirely different. This description of the inherent polarizabilities of a target is a major advance in discriminating UXO from irregular scrap metal. Our results clearly show that BUD can resolve the intrinsic polarizabilities of a target and that there are very clear distinctions between symmetric intact UXO and irregular scrap metal. Target properties are determined by an inversion algorithm, which at any given time inverts the response to yield the location (x, y, z) of the target, its attitude and its principal polarizabilities (yielding an apparent aspect ratio). Signal-to-noise estimates (or measurements) are interpreted in this inversion to yield error estimates on the location, attitude and polarizabilities. This inversion at a succession of times provides the polarizabilities as a function of time, which can in turn yield the size, true aspect ratio and estimates of the conductivity and permeability of the target. The accuracy of these property estimates depends on the time window over which the polarizability measurements, and their accuracies, are known. Initial tests at a local site over a variety of test objects and inert UXOs showed excellent detection and characterization results within the predicted size-depth range. This research was funded by the U.S. Department of Defense under ESTCP Project # UX-0437.

Detecting method of subjects' 3D positions and experimental advanced camera control system

NASA Astrophysics Data System (ADS)

Kato, Daiichiro; Abe, Kazuo; Ishikawa, Akio; Yamada, Mitsuho; Suzuki, Takahito; Kuwashima, Shigesumi

1997-04-01

Steady progress is being made in the development of an intelligent robot camera capable of automatically shooting pictures with a powerful sense of reality or tracking objects whose shooting requires advanced techniques. Currently, only experienced broadcasting cameramen can provide these pictures.TO develop an intelligent robot camera with these abilities, we need to clearly understand how a broadcasting cameraman assesses his shooting situation and how his camera is moved during shooting. We use a real- time analyzer to study a cameraman's work and his gaze movements at studios and during sports broadcasts. This time, we have developed a detecting method of subjects' 3D positions and an experimental camera control system to help us further understand the movements required for an intelligent robot camera. The features are as follows: (1) Two sensor cameras shoot a moving subject and detect colors, producing its 3D coordinates. (2) Capable of driving a camera based on camera movement data obtained by a real-time analyzer. 'Moving shoot' is the name we have given to the object position detection technology on which this system is based. We used it in a soccer game, producing computer graphics showing how players moved. These results will also be reported.

ROS-based ground stereo vision detection: implementation and experiments.

PubMed

Hu, Tianjiang; Zhao, Boxin; Tang, Dengqing; Zhang, Daibing; Kong, Weiwei; Shen, Lincheng

This article concentrates on open-source implementation on flying object detection in cluttered scenes. It is of significance for ground stereo-aided autonomous landing of unmanned aerial vehicles. The ground stereo vision guidance system is presented with details on system architecture and workflow. The Chan-Vese detection algorithm is further considered and implemented in the robot operating systems (ROS) environment. A data-driven interactive scheme is developed to collect datasets for parameter tuning and performance evaluating. The flying vehicle outdoor experiments capture the stereo sequential images dataset and record the simultaneous data from pan-and-tilt unit, onboard sensors and differential GPS. Experimental results by using the collected dataset validate the effectiveness of the published ROS-based detection algorithm.

3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands.

PubMed

Mateo, Carlos M; Gil, Pablo; Torres, Fernando

2016-05-05

Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object's surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand's fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments.

Detection, Identification, Location, and Remote Sensing Using SAW RFID Sensor Tags

NASA Technical Reports Server (NTRS)

Barton, Richard J.; Kennedy, Timothy F.; Williams, Robert M.; Fink, Patrick W.; Ngo, Phong H.

2009-01-01

The Electromagnetic Systems Branch (EV4) of the Avionic Systems Division at NASA Johnson Space Center in Houston, TX is studying the utility of surface acoustic wave (SAW) radiofrequency identification (RFID) tags for multiple wireless applications including detection, identification, tracking, and remote sensing of objects on the lunar surface, monitoring of environmental test facilities, structural shape and health monitoring, and nondestructive test and evaluation of assets. For all of these applications, it is anticipated that the system utilized to interrogate the SAW RFID tags may need to operate at fairly long range and in the presence of considerable multipath and multiple-access interference. Towards that end, EV4 is developing a prototype SAW RFID wireless interrogation system for use in such environments called the Passive Adaptive RFID Sensor Equipment (PARSED) system. The system utilizes a digitally beam-formed planar receiving antenna array to extend range and provide direction-of-arrival information coupled with an approximate maximum-likelihood signal processing algorithm to provide near-optimal estimation of both range and temperature. The system is capable of forming a large number of beams within the field of view and resolving the information from several tags within each beam. The combination of both spatial and waveform discrimination provides the capability to track and monitor telemetry from a large number of objects appearing simultaneously within the field of view of the receiving array. In this paper, we will consider the application of the PARSEQ system to the problem of simultaneous detection, identification, localization, and temperature estimation for multiple objects. We will summarize the overall design of the PARSEQ system and present a detailed description of the design and performance of the signal detection and estimation algorithms incorporated in the system. The system is currently configured only to measure temperature (jointly with range and tag ID), but future versions will be revised to measure parameters other than temperature as SAW tags capable of interfacing with external sensors become available. It is anticipated that the estimation of arbitrary parameters measured using SAW-based sensors will be based on techniques very similar to the joint range and temperature estimation techniques described in this paper.

Note: A manifold ranking based saliency detection method for camera.

PubMed

Zhang, Libo; Sun, Yihan; Luo, Tiejian; Rahman, Mohammad Muntasir

2016-09-01

Research focused on salient object region in natural scenes has attracted a lot in computer vision and has widely been used in many applications like object detection and segmentation. However, an accurate focusing on the salient region, while taking photographs of the real-world scenery, is still a challenging task. In order to deal with the problem, this paper presents a novel approach based on human visual system, which works better with the usage of both background prior and compactness prior. In the proposed method, we eliminate the unsuitable boundary with a fixed threshold to optimize the image boundary selection which can provide more precise estimations. Then, the object detection, which is optimized with compactness prior, is obtained by ranking with background queries. Salient objects are generally grouped together into connected areas that have compact spatial distributions. The experimental results on three public datasets demonstrate that the precision and robustness of the proposed algorithm have been improved obviously.

Optimizing Monitoring Designs under Alternative Objectives

DOE PAGES

Gastelum, Jason A.; USA, Richland Washington; Porter, Ellen A.; ...

2014-12-31

This paper describes an approach to identify monitoring designs that optimize detection of CO2 leakage from a carbon capture and sequestration (CCS) reservoir and compares the results generated under two alternative objective functions. The first objective function minimizes the expected time to first detection of CO2 leakage, the second more conservative objective function minimizes the maximum time to leakage detection across the set of realizations. The approach applies a simulated annealing algorithm that searches the solution space by iteratively mutating the incumbent monitoring design. The approach takes into account uncertainty by evaluating the performance of potential monitoring designs across amore » set of simulated leakage realizations. The approach relies on a flexible two-tiered signature to infer that CO2 leakage has occurred. This research is part of the National Risk Assessment Partnership, a U.S. Department of Energy (DOE) project tasked with conducting risk and uncertainty analysis in the areas of reservoir performance, natural leakage pathways, wellbore integrity, groundwater protection, monitoring, and systems level modeling.« less

Object Acquisition and Tracking for Space-Based Surveillance

DTIC Science & Technology

1991-11-27

on multiple image frames, and, accordingly, requires a smaller signal to noise ratio. It is sometimes referred to as track before detect , and can...smaller sensor optics. Both the traditional and track before detect approaches are applicable to systems using scanning sensors, as well as those which use staring sensors.

A comparison of moving object detection methods for real-time moving object detection

NASA Astrophysics Data System (ADS)

Roshan, Aditya; Zhang, Yun

2014-06-01

Moving object detection has a wide variety of applications from traffic monitoring, site monitoring, automatic theft identification, face detection to military surveillance. Many methods have been developed across the globe for moving object detection, but it is very difficult to find one which can work globally in all situations and with different types of videos. The purpose of this paper is to evaluate existing moving object detection methods which can be implemented in software on a desktop or laptop, for real time object detection. There are several moving object detection methods noted in the literature, but few of them are suitable for real time moving object detection. Most of the methods which provide for real time movement are further limited by the number of objects and the scene complexity. This paper evaluates the four most commonly used moving object detection methods as background subtraction technique, Gaussian mixture model, wavelet based and optical flow based methods. The work is based on evaluation of these four moving object detection methods using two (2) different sets of cameras and two (2) different scenes. The moving object detection methods have been implemented using MatLab and results are compared based on completeness of detected objects, noise, light change sensitivity, processing time etc. After comparison, it is observed that optical flow based method took least processing time and successfully detected boundary of moving objects which also implies that it can be implemented for real-time moving object detection.

Quantifying the effect of colorization enhancement on mammogram images

NASA Astrophysics Data System (ADS)

Wojnicki, Paul J.; Uyeda, Elizabeth; Micheli-Tzanakou, Evangelia

2002-04-01

Current methods of radiological displays provide only grayscale images of mammograms. The limitation of the image space to grayscale provides only luminance differences and textures as cues for object recognition within the image. However, color can be an important and significant cue in the detection of shapes and objects. Increasing detection ability allows the radiologist to interpret the images in more detail, improving object recognition and diagnostic accuracy. Color detection experiments using our stimulus system, have demonstrated that an observer can only detect an average of 140 levels of grayscale. An optimally colorized image can allow a user to distinguish 250 - 1000 different levels, hence increasing potential image feature detection by 2-7 times. By implementing a colorization map, which follows the luminance map of the original grayscale images, the luminance profile is preserved and color is isolated as the enhancement mechanism. The effect of this enhancement mechanism on the shape, frequency composition and statistical characteristics of the Visual Evoked Potential (VEP) are analyzed and presented. Thus, the effectiveness of the image colorization is measured quantitatively using the Visual Evoked Potential (VEP).

Using optical flow for the detection of floating mines in IR image sequences

NASA Astrophysics Data System (ADS)

Borghgraef, Alexander; Acheroy, Marc

2006-09-01

In the first Gulf War, unmoored floating mines proved to be a real hazard for shipping traffic. An automated system capable of detecting these and other free-floating small objects, using readily available sensors such as infra-red cameras, would prove to be a valuable mine-warfare asset, and could double as a collision avoidance mechanism, and a search-and-rescue aid. The noisy background provided by the sea surface, and occlusion by waves make it difficult to detect small floating objects using only algorithms based upon the intensity, size or shape of the target. This leads us to look at the sequence of images for temporal detection characteristics. The target's apparent motion is such a determinant, given the contrast between the bobbing motion of the floating object and the strong horizontal component present in the propagation of the wavefronts. We have applied the Proesmans optical flow algorithm to IR video footage of practice mines, in order to extract the motion characteristic and a threshold on the vertical motion characteristic is then imposed to detect the floating targets.

A novel biometric X-ray backscatter inspection of dangerous materials based on a lobster-eye objective

NASA Astrophysics Data System (ADS)

Xu, Jie; Wang, Xin; Mu, Baozhong; Zhan, Qi; Xie, Qing; Li, Yaran; Chen, Yifan; He, Yanan

2016-10-01

In order to counter drug-related crimes effectively, and to safeguard homeland security as well as public safety, it is important to inspect drugs, explosives and other contraband quickly and accurately from the express mail system, luggage, vehicles and other objects. In this paper, we discuss X-ray backscatter inspection system based on a novel lobster-eye X-ray objective, which is an effective inspection technology for drugs, explosives and other contraband inspection. Low atomic number materials, such as drugs and explosives, leads to strong Compton scattering after irradiated by X-ray, which is much stronger than high atomic number material, such as common metals, etc. By detecting the intensity of scattering signals, it is possible to distinguish between organics and inorganics. The lobster-eye X-ray optical system imitates the reflective eyes of lobsters, which field of view can be made as large as desired and it is practical to achieve spatial resolution of several millimeters for finite distance detection. A novel lobster-eye X-ray objective is designed based on modifying Schmidt geometry by using multi-lens structure, so as to reduce the difference of resolution between the horizontal and vertical directions. The demonstration experiments of X-ray backscattering imaging were carried out. A suitcase, a wooden box and a tire with several typical samples hidden in them were imaged by the X-ray backscattering inspection system based on a lobster-eye X-ray objective. The results show that this X-ray backscattering inspection system can get a resolution of less than five millimeters under the FOV of more than two hundred millimeters with 0.5 meter object distance, which can still be improved.

Haptic discrimination of bilateral symmetry in 2-dimensional and 3-dimensional unfamiliar displays.

PubMed

Ballesteros, S; Manga, D; Reales, J M

1997-01-01

In five experiments, we tested the accuracy and sensitivity of the haptic system in detecting bilateral symmetry of raised-line shapes (Experiments 1 and 2) and unfamiliar 3-D objects (Experiments 3-5) under different time constraints and different modes of exploration. Touch was moderately accurate for detecting this property in raised displays. Experiment 1 showed that asymmetric judgments were systematically more accurate than were symmetric judgements with scanning by one finger. Experiments 2 confirmed the results of Experiment 1 but also showed that bimanual exploration facilitated processing of symmetric shapes without improving asymmetric detections. Bimanual exploration of 3-D objects was very accurate and significantly facilitated processing of symmetric objects under different time constraints (Experiment 3). Unimanual exploration did not differ from bimanual exploration (Experiment 4), but restricting hand movements to one enclosure reduced performance significantly (Experiment 5). Spatial reference information, signal detection measures, and hand movements in processing bilateral symmetry by touch are discussed.

Moving Object Detection Using a Parallax Shift Vector Algorithm

NASA Astrophysics Data System (ADS)

Gural, Peter S.; Otto, Paul R.; Tedesco, Edward F.

2018-07-01

There are various algorithms currently in use to detect asteroids from ground-based observatories, but they are generally restricted to linear or mildly curved movement of the target object across the field of view. Space-based sensors in high inclination, low Earth orbits can induce significant parallax in a collected sequence of images, especially for objects at the typical distances of asteroids in the inner solar system. This results in a highly nonlinear motion pattern of the asteroid across the sensor, which requires a more sophisticated search pattern for detection processing. Both the classical pattern matching used in ground-based asteroid search and the more sensitive matched filtering and synthetic tracking techniques, can be adapted to account for highly complex parallax motion. A new shift vector generation methodology is discussed along with its impacts on commonly used detection algorithms, processing load, and responsiveness to asteroid track reporting. The matched filter, template generator, and pattern matcher source code for the software described herein are available via GitHub.

Sensor fusion V; Proceedings of the Meeting, Boston, MA, Nov. 15-17, 1992

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1992-01-01

Topics addressed include 3D object perception, human-machine interface in multisensor systems, sensor fusion architecture, fusion of multiple and distributed sensors, interface and decision models for sensor fusion, computational networks, simple sensing for complex action, multisensor-based control, and metrology and calibration of multisensor systems. Particular attention is given to controlling 3D objects by sketching 2D views, the graphical simulation and animation environment for flexible structure robots, designing robotic systems from sensorimotor modules, cylindrical object reconstruction from a sequence of images, an accurate estimation of surface properties by integrating information using Bayesian networks, an adaptive fusion model for a distributed detection system, multiple concurrent object descriptions in support of autonomous navigation, robot control with multiple sensors and heuristic knowledge, and optical array detectors for image sensors calibration. (No individual items are abstracted in this volume)

Digital Mapping of Buried Pipelines with a Dual Array System

DOT National Transportation Integrated Search

2003-06-06

The objective of this research is to develop a non-invasive system for detecting, mapping, and inspecting ferrous and plastic pipelines in place using technology that combines and interprets measurements from ground penetrating radar and electromagne...

A method of immediate detection of objects with a near-zero apparent motion in series of CCD-frames

NASA Astrophysics Data System (ADS)

Savanevych, V. E.; Khlamov, S. V.; Vavilova, I. B.; Briukhovetskyi, A. B.; Pohorelov, A. V.; Mkrtichian, D. E.; Kudak, V. I.; Pakuliak, L. K.; Dikov, E. N.; Melnik, R. G.; Vlasenko, V. P.; Reichart, D. E.

2018-01-01

The paper deals with a computational method for detection of the solar system minor bodies (SSOs), whose inter-frame shifts in series of CCD-frames during the observation are commensurate with the errors in measuring their positions. These objects have velocities of apparent motion between CCD-frames not exceeding three rms errors (3σ) of measurements of their positions. About 15% of objects have a near-zero apparent motion in CCD-frames, including the objects beyond the Jupiter's orbit as well as the asteroids heading straight to the Earth. The proposed method for detection of the object's near-zero apparent motion in series of CCD-frames is based on the Fisher f-criterion instead of using the traditional decision rules that are based on the maximum likelihood criterion. We analyzed the quality indicators of detection of the object's near-zero apparent motion applying statistical and in situ modeling techniques in terms of the conditional probability of the true detection of objects with a near-zero apparent motion. The efficiency of method being implemented as a plugin for the Collection Light Technology (CoLiTec) software for automated asteroids and comets detection has been demonstrated. Among the objects discovered with this plugin, there was the sungrazing comet C/2012 S1 (ISON). Within 26 min of the observation, the comet's image has been moved by three pixels in a series of four CCD-frames (the velocity of its apparent motion at the moment of discovery was equal to 0.8 pixels per CCD-frame; the image size on the frame was about five pixels). Next verification in observations of asteroids with a near-zero apparent motion conducted with small telescopes has confirmed an efficiency of the method even in bad conditions (strong backlight from the full Moon). So, we recommend applying the proposed method for series of observations with four or more frames.

Vehicle and cargo inspection system

NASA Astrophysics Data System (ADS)

Verbinski, Victor V.; Orphan, Victor J.

1997-02-01

Vehicle and Cargo Inspection System (VACIS) is comprised of a 1 Curie 137Cs gamma-ray source in a shield and collimator which produces a fan-shaped beam designed to intercept a vertical array of gama-ray detectors contained in a tower structure. The source and detector modules straddle the vehicle or container being inspected and are mounted on self-propelled trolleys which travel in synchronization along two parallel tracks covering the length of the scanned object. The signals from the gamma-ray detector array are processed and displayed so as to produce a 2D gamma-radiographic image of the object. Testing of the system on a variety of empty and lightly-loaded vehicles and containers has demonstrated the effectiveness of VACIS in detecting hidden contraband. For example, a small sample of cocaine only 1.5 inches thick was readily detected in a container.

Stochastic resonance investigation of object detection in images

NASA Astrophysics Data System (ADS)

Repperger, Daniel W.; Pinkus, Alan R.; Skipper, Julie A.; Schrider, Christina D.

2007-02-01

Object detection in images was conducted using a nonlinear means of improving signal to noise ratio termed "stochastic resonance" (SR). In a recent United States patent application, it was shown that arbitrarily large signal to noise ratio gains could be realized when a signal detection problem is cast within the context of a SR filter. Signal-to-noise ratio measures were investigated. For a binary object recognition task (friendly versus hostile), the method was implemented by perturbing the recognition algorithm and subsequently thresholding via a computer simulation. To fairly test the efficacy of the proposed algorithm, a unique database of images has been constructed by modifying two sample library objects by adjusting their brightness, contrast and relative size via commercial software to gradually compromise their saliency to identification. The key to the use of the SR method is to produce a small perturbation in the identification algorithm and then to threshold the results, thus improving the overall system's ability to discern objects. A background discussion of the SR method is presented. A standard test is proposed in which object identification algorithms could be fairly compared against each other with respect to their relative performance.

ON THE NATURE OF THE TERTIARY COMPANION TO FW TAU: ALMA CO OBSERVATIONS AND SED MODELING

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caceres, Claudio; Hardy, Adam; Schreiber, Matthias R.

2015-06-20

It is thought that planetary mass companions may form through gravitational disk instabilities or core accretion. Identifying such objects in the process of formation would provide the most direct test for the competing formation theories. One of the most promising candidates for a planetary mass object still in formation is the third object in the FW Tau system. We present here ALMA cycle 1 observations confirming the recently published 1.3 mm detection of a dust disk around this third object and present for the first time a clear detection of a single peak {sup 12}CO (2–1) line, providing direct evidencemore » for the simultaneous existence of a gas disk. We perform radiative transfer modeling of the third object in FW Tau and find that current observations are consistent with either a brown dwarf embedded in an edge-on disk or a planet embedded in a low inclination disk, which is externally irradiated by the binary companion. Further observations with ALMA, aiming for high SNR detections of non-contaminated gas lines, are required to conclusively unveil the nature of the third object in FW Tau.« less

Activities of JAXA's Innovative Technology Center on Space Debris Observation

NASA Astrophysics Data System (ADS)

Yanagisawa, T.; Kurosaki, H.; Nakajima, A.

The innovative technology research center of JAXA is developing observational technologies for GEO objects in order to cope with the space debris problem. The center had constructed the optical observational facility for space debris at Mt. Nyukasa, Nagano in 2006. As observational equipments such as CCD cameras and telescopes were set up, the normal observation started. In this paper, the detail of the facilities and its activities are introduced. The observational facility contains two telescopes and two CCD cameras. The apertures of the telescopes are 35cm and 25 cm, respectively. One CCD camera in which 2K2K chip is installed can observe a sky region of 1.3 times 1.3-degree using the 35cm telescope. The other CCD camera that contains two 4K2K chips has an ability to observe 2.6 times 2.6-degree's region with the 25cm telescope. One of our main objectives is to detect faint GEO objects that are not catalogued. Generally, the detection limit of GEO object is determined by the aperture of the telescope. However, by improving image processing techniques, the limit may become low. We are developing some image processing methods that use many CCD frames to detect faint objects. We are trying to use FPGA (Field Programmable Gate Array) system to reduce analyzing time. By applying these methods to the data taken by a large telescope, the detection limit will be significantly lowered. The orbital determination of detected GEO debris is one of the important things to do. Especially, the narrow field view of an optical telescope hinders us from re-detection of the GEO debris for the orbital determination. Long observation time is required for one GEO object for the orbital determination that is inefficient. An effective observation strategy should be considered. We are testing one observation method invented by Umehara that observes one inertia position in the space. By observing one inertia position for two nights, a GEO object that passed through the position in the first night must pass through the position in the second night. The rough orbit is determined from two nights' data. The test observation showed that this method was able to detect many GEO objects and determined their orbits by three nights' observations. We also joined the campaign observations of IADC(Inter-Agency Space Debris Coordination Committee). By analyzing the observed data with the method that we developed, 88 catalogued and 38 un-catalogued objects were detected. The magnitude of the faintest object detected in this campaign observation was 18.5. The object is un-detectable by human inspection.

Implementation of Augmented Reality Technology in Sangiran Museum with Vuforia

NASA Astrophysics Data System (ADS)

Purnomo, F. A.; Santosa, P. I.; Hartanto, R.; Pratisto, E. H.; Purbayu, A.

2018-03-01

Archaeological object is an evidence of life on ancient relics which has a lifespan of millions years ago. The discovery of this ancient object by the Museum Sangiran then is preserved and protected from potential damage. This research will develop Augmented Reality application for the museum that display a virtual information from ancient object on display. The content includes information as text, audio, and animation of 3D model as a representation of the ancient object. This study emphasizes the 3D Markerless recognition process by using Vuforia Augmented Reality (AR) system so that visitor can access the exhibition objects through different viewpoints. Based on the test result, by registering image target with 25o angle interval, 3D markerless keypoint feature can be detected with different viewpoint. The device must meet minimal specifications of Dual Core 1.2 GHz processor, GPU Power VR SG5X, 8 MP auto focus camera and 1 GB of memory to run the application. The average success of the AR application detects object in museum exhibition to 3D Markerless with a single view by 40%, Markerless multiview by 86% (for angle 0° - 180°) and 100% (for angle 0° - 360°). Application detection distance is between 23 cm and up to 540 cm with the response time to detect 3D Markerless has 12 seconds in average.

The reconnaissance and early-warning optical system design for dual field of space-based "solar blind ultraviolet"

NASA Astrophysics Data System (ADS)

Wang, Wen-cong; Jin, Dong-dong; Shao, Fei; Hu, Hui-jun; Shi, Yu-feng; Song, Juan; Zhang, Yu-tu; Yong, Liu

2016-07-01

With the development of modern technology, especially the development of information technology at high speed, the ultraviolet early warning system plays an increasingly important role. In the modern warfare, how to detect the threats earlier, prevent and reduce the attack of precision-guided missile has become a new challenge. Because the ultraviolet warning technology has high environmental adaptability, the low false alarm rate, small volume and other advantages, in the military field applications it has been developed rapidly. According to current application demands for solar blind ultraviolet detection and warning, this paper proposes a reconnaissance and early-warning optical system, which covers solar blind ultraviolet (250nm-280nm) and dual field. This structure takes advantage of a narrow field of view and long focal length optical system to achieve the target object detection, uses wide-field and short focal length optical system to achieve early warning of the target object. It makes use of an ultraviolet beam-splitter to achieve the separation of two optical systems. According to the detector and the corresponding application needs of two visual field of the optical system, the calculation and optical system design were completed. After the design, the MTF of the two optical system is more than 0.8@39lp/mm. A single pixel energy concentration is greater than 80%.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loughran, B; Singh, V; Jain, A

Purpose: Although generalized linear system analytic metrics such as GMTF and GDQE can evaluate performance of the whole imaging system including detector, scatter and focal-spot, a simplified task-specific measured metric may help to better compare detector systems. Methods: Low quantum-noise images of a neuro-vascular stent with a modified ANSI head phantom were obtained from the average of many exposures taken with the high-resolution Micro-Angiographic Fluoroscope (MAF) and with a Flat Panel Detector (FPD). The square of the Fourier Transform of each averaged image, equivalent to the measured product of the system GMTF and the object function in spatial-frequency space, wasmore » then divided by the normalized noise power spectra (NNPS) for each respective system to obtain a task-specific generalized signal-to-noise ratio. A generalized measured relative object detectability (GM-ROD) was obtained by taking the ratio of the integral of the resulting expressions for each detector system to give an overall metric that enables a realistic systems comparison for the given detection task. Results: The GM-ROD provides comparison of relative performance of detector systems from actual measurements of the object function as imaged by those detector systems. This metric includes noise correlations and spatial frequencies relevant to the specific object. Additionally, the integration bounds for the GM-ROD can be selected to emphasis the higher frequency band of each detector if high-resolution image details are to be evaluated. Examples of this new metric are discussed with a comparison of the MAF to the FPD for neuro-vascular interventional imaging. Conclusion: The GM-ROD is a new direct-measured task-specific metric that can provide clinically relevant comparison of the relative performance of imaging systems. Supported by NIH Grant: 2R01EB002873 and an equipment grant from Toshiba Medical Systems Corporation.« less

Specialization of Perceptual Processes.

DTIC Science & Technology

1994-09-01

population rose and fell, furniture was rearranged, a small mountain range was built in part of the lab (really), carpets were shampooed , and oce lighting...common task is the tracking of moving objects. Coombs [22] implemented a system 44 for xating and tracking objects using a stereo eye/ head system...be a person (person?). Finally, a motion unit is used to detect foot gestures. A pair of nod-of-the- head detectors were implemented and tested, but

HUBBLE DETECTION OF COMET NUCLEUS AT FRINGE OF SOLAR SYSTEM

NASA Technical Reports Server (NTRS)

2002-01-01

This is sample data from NASA's Hubble Space Telescope that illustrates the detection of comets in the Kuiper Belt, a region of space beyond the orbit of the planet Neptune. This pair of images, taken with the Wide Field Planetary Camera 2 (WFPC2), shows one of the candidate Kuiper Belt objects found with Hubble. Believed to be an icy comet nucleus several miles across, the object is so distant and faint that Hubble's search is the equivalent of finding the proverbial needle-in-haystack. Each photo is a 5-hour exposure of a piece of sky carefully selected such that it is nearly devoid of background stars and galaxies that could mask the elusive comet. The left image, taken on August 22, 1994, shows the candidate comet object (inside circle) embedded in the background. The right picture, take of the same region one hour forty-five minutes later shows the object has apparently moved in the predicted direction and rate of motion for a kuiper belt member. The dotted line on the images is a possible orbit that this Kuiper belt comet is following. A star (lower right corner) and a galaxy (upper right corner) provide a static background reference. In addition, other objects in the picture have not moved during this time, indicating they are outside our solar system. Through this search technique astronomers have identified 29 candidate comet nuclei belonging to an estimated population of 200 million particles orbiting the edge of our solar system. The Kupier Belt was theorized 40 years ago, and its larger members detected several years ago. However, Hubble has found the underlying population of normal comet-sized bodies. Credit: A. Cochran (University of Texas) and NASA

Performance analysis of a multispectral framing camera for detecting mines in the littoral zone and beach zone

NASA Astrophysics Data System (ADS)

Louchard, Eric; Farm, Brian; Acker, Andrew

2008-04-01

BAE Systems Sensor Systems Identification & Surveillance (IS) has developed, under contract with the Office of Naval Research, a multispectral airborne sensor system and processing algorithms capable of detecting mine-like objects in the surf zone and land mines in the beach zone. BAE Systems has used this system in a blind test at a test range established by the Naval Surface Warfare Center - Panama City Division (NSWC-PCD) at Eglin Air Force Base. The airborne and ground subsystems used in this test are described, with graphical illustrations of the detection algorithms. We report on the performance of the system configured to operate with a human operator analyzing data on a ground station. A subsurface (underwater bottom proud mine in the surf zone and moored mine in shallow water) mine detection capability is demonstrated in the surf zone. Surface float detection and proud land mine detection capability is also demonstrated. Our analysis shows that this BAE Systems-developed multispectral airborne sensor provides a robust technical foundation for a viable system for mine counter-measures, and would be a valuable asset for use prior to an amphibious assault.

Long-term object tracking combined offline with online learning

NASA Astrophysics Data System (ADS)

Hu, Mengjie; Wei, Zhenzhong; Zhang, Guangjun

2016-04-01

We propose a simple yet effective method for long-term object tracking. Different from the traditional visual tracking method, which mainly depends on frame-to-frame correspondence, we combine high-level semantic information with low-level correspondences. Our framework is formulated in a confidence selection framework, which allows our system to recover from drift and partly deal with occlusion. To summarize, our algorithm can be roughly decomposed into an initialization stage and a tracking stage. In the initialization stage, an offline detector is trained to get the object appearance information at the category level, which is used for detecting the potential target and initializing the tracking stage. The tracking stage consists of three modules: the online tracking module, detection module, and decision module. A pretrained detector is used for maintaining drift of the online tracker, while the online tracker is used for filtering out false positive detections. A confidence selection mechanism is proposed to optimize the object location based on the online tracker and detection. If the target is lost, the pretrained detector is utilized to reinitialize the whole algorithm when the target is relocated. During experiments, we evaluate our method on several challenging video sequences, and it demonstrates huge improvement compared with detection and online tracking only.

Multigrid contact detection method

NASA Astrophysics Data System (ADS)

He, Kejing; Dong, Shoubin; Zhou, Zhaoyao

2007-03-01

Contact detection is a general problem of many physical simulations. This work presents a O(N) multigrid method for general contact detection problems (MGCD). The multigrid idea is integrated with contact detection problems. Both the time complexity and memory consumption of the MGCD are O(N) . Unlike other methods, whose efficiencies are influenced strongly by the object size distribution, the performance of MGCD is insensitive to the object size distribution. We compare the MGCD with the no binary search (NBS) method and the multilevel boxing method in three dimensions for both time complexity and memory consumption. For objects with similar size, the MGCD is as good as the NBS method, both of which outperform the multilevel boxing method regarding memory consumption. For objects with diverse size, the MGCD outperform both the NBS method and the multilevel boxing method. We use the MGCD to solve the contact detection problem for a granular simulation system based on the discrete element method. From this granular simulation, we get the density property of monosize packing and binary packing with size ratio equal to 10. The packing density for monosize particles is 0.636. For binary packing with size ratio equal to 10, when the number of small particles is 300 times as the number of big particles, the maximal packing density 0.824 is achieved.

Method and apparatus for detecting internal structures of bulk objects using acoustic imaging

DOEpatents

Deason, Vance A.; Telschow, Kenneth L.

2002-01-01

Apparatus for producing an acoustic image of an object according to the present invention may comprise an excitation source for vibrating the object to produce at least one acoustic wave therein. The acoustic wave results in the formation of at least one surface displacement on the surface of the object. A light source produces an optical object wavefront and an optical reference wavefront and directs the optical object wavefront toward the surface of the object to produce a modulated optical object wavefront. A modulator operatively associated with the optical reference wavefront modulates the optical reference wavefront in synchronization with the acoustic wave to produce a modulated optical reference wavefront. A sensing medium positioned to receive the modulated optical object wavefront and the modulated optical reference wavefront combines the modulated optical object and reference wavefronts to produce an image related to the surface displacement on the surface of the object. A detector detects the image related to the surface displacement produced by the sensing medium. A processing system operatively associated with the detector constructs an acoustic image of interior features of the object based on the phase and amplitude of the surface displacement on the surface of the object.

Intra- and Inter-database Study for Arabic, English, and German Databases: Do Conventional Speech Features Detect Voice Pathology?

PubMed

Ali, Zulfiqar; Alsulaiman, Mansour; Muhammad, Ghulam; Elamvazuthi, Irraivan; Al-Nasheri, Ahmed; Mesallam, Tamer A; Farahat, Mohamed; Malki, Khalid H

2017-05-01

A large population around the world has voice complications. Various approaches for subjective and objective evaluations have been suggested in the literature. The subjective approach strongly depends on the experience and area of expertise of a clinician, and human error cannot be neglected. On the other hand, the objective or automatic approach is noninvasive. Automatic developed systems can provide complementary information that may be helpful for a clinician in the early screening of a voice disorder. At the same time, automatic systems can be deployed in remote areas where a general practitioner can use them and may refer the patient to a specialist to avoid complications that may be life threatening. Many automatic systems for disorder detection have been developed by applying different types of conventional speech features such as the linear prediction coefficients, linear prediction cepstral coefficients, and Mel-frequency cepstral coefficients (MFCCs). This study aims to ascertain whether conventional speech features detect voice pathology reliably, and whether they can be correlated with voice quality. To investigate this, an automatic detection system based on MFCC was developed, and three different voice disorder databases were used in this study. The experimental results suggest that the accuracy of the MFCC-based system varies from database to database. The detection rate for the intra-database ranges from 72% to 95%, and that for the inter-database is from 47% to 82%. The results conclude that conventional speech features are not correlated with voice, and hence are not reliable in pathology detection. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Particle detection, number estimation, and feature measurement in gene transfer studies: optical fractionator stereology integrated with digital image processing and analysis.

PubMed

King, Michael A; Scotty, Nicole; Klein, Ronald L; Meyer, Edwin M

2002-10-01

Assessing the efficacy of in vivo gene transfer often requires a quantitative determination of the number, size, shape, or histological visualization characteristics of biological objects. The optical fractionator has become a choice stereological method for estimating the number of objects, such as neurons, in a structure, such as a brain subregion. Digital image processing and analytic methods can increase detection sensitivity and quantify structural and/or spectral features located in histological specimens. We describe a hardware and software system that we have developed for conducting the optical fractionator process. A microscope equipped with a video camera and motorized stage and focus controls is interfaced with a desktop computer. The computer contains a combination live video/computer graphics adapter with a video frame grabber and controls the stage, focus, and video via a commercial imaging software package. Specialized macro programs have been constructed with this software to execute command sequences requisite to the optical fractionator method: defining regions of interest, positioning specimens in a systematic uniform random manner, and stepping through known volumes of tissue for interactive object identification (optical dissectors). The system affords the flexibility to work with count regions that exceed the microscope image field size at low magnifications and to adjust the parameters of the fractionator sampling to best match the demands of particular specimens and object types. Digital image processing can be used to facilitate object detection and identification, and objects that meet criteria for counting can be analyzed for a variety of morphometric and optical properties. Copyright 2002 Elsevier Science (USA)

Dynamic Steering for Improved Sensor Autonomy and Catalogue Maintenance

NASA Astrophysics Data System (ADS)

Hobson, T.; Gordon, N.; Clarkson, I.; Rutten, M.; Bessell, T.

A number of international agencies endeavour to maintain catalogues of the man-made resident space objects (RSOs) currently orbiting the Earth. Such catalogues are primarily created to anticipate and avoid destructive collisions involving important space assets such as manned missions and active satellites. An agencys ability to achieve this objective is dependent on the accuracy, reliability and timeliness of the information used to update its catalogue. A primary means for gathering this information is by regularly making direct observations of the tens-of-thousands of currently detectable RSOs via networks of space surveillance sensors. But operational constraints sometimes prevent accurate and timely reacquisition of all known RSOs, which can cause them to become lost to the tracking system. Furthermore, when comprehensive acquisition of new objects does not occur, these objects, in addition to the lost RSOs, result in uncorrelated detections when next observed. Due to the rising number of space-missions and the introduction of newer, more capable space-sensors, the number of uncorrelated targets is at an all-time high. The process of differentiating uncorrelated detections caused by once-acquired now-lost RSOs from newly detected RSOs is a difficult and often labour intensive task. Current methods for overcoming this challenge focus on advancements in orbit propagation and object characterisation to improve prediction accuracy and target identification. In this paper, we describe a complementary approach that incorporates increased awareness of error and failed observations into the RSO tracking solution. Our methodology employs a technique called dynamic steering to improve the autonomy and capability of a space surveillance networks steerable sensors. By co-situating each sensor with a low-cost high-performance computer, the steerable sensor can quickly and intelligently decide how to steer itself. The sensor-system uses a dedicated parallel-processing architecture to enable it to compute a high-fidelity estimate of the targets prior state error distribution in real-time. Negative information, such as when an RSO is targeted for observation but it is not observed, is incorporated to improve the likelihood of reacquiring the target when attempting to observe the target in future. The sensor is consequently capable of improving its utility by planning each observation using a sensor steering solution that is informed by all prior attempts at observing the target. We describe the practical implementation of a single experimental sensor and offer the results of recent field trials. These trials involved reacquisition and constrained Initial Orbit Determination of RSOs, a number of months after prior observation and initial detection. Using the proposed approach, the system is capable of using targeting information that would be unusable by existing space surveillance networks. The system consequently offers a means of enhancing space surveillance for SSA via increased system capacity, a higher degree of autonomy and the ability to reacquire objects whose dynamics are insufficiently modelled to cue a conventional space surveillance system for observation and tracking.

Orthorectified High Resolution Multispectral Imagery for Application to Change Detection and Analysis

NASA Technical Reports Server (NTRS)

Benkelman, Cody A.

1997-01-01

The project team has outlined several technical objectives which will allow the companies to improve on their current capabilities. These include modifications to the imaging system, enabling it to operate more cost effectively and with greater ease of use, automation of the post-processing software to mosaic and orthorectify the image scenes collected, and the addition of radiometric calibration to greatly aid in the ability to perform accurate change detection. Business objectives include fine tuning of the market plan plus specification of future product requirements, expansion of sales activities (including identification of necessary additional resources required to meet stated revenue objectives), development of a product distribution plan, and implementation of a world wide sales effort.

Methods for identification and verification using vacuum XRF system

NASA Technical Reports Server (NTRS)

Kaiser, Bruce (Inventor); Schramm, Fred (Inventor)

2005-01-01

Apparatus and methods in which one or more elemental taggants that are intrinsically located in an object are detected by x-ray fluorescence analysis under vacuum conditions to identify or verify the object's elemental content for elements with lower atomic numbers. By using x-ray fluorescence analysis, the apparatus and methods of the invention are simple and easy to use, as well as provide detection by a non line-of-sight method to establish the origin of objects, as well as their point of manufacture, authenticity, verification, security, and the presence of impurities. The invention is extremely advantageous because it provides the capability to measure lower atomic number elements in the field with a portable instrument.

Physical security and cyber security issues and human error prevention for 3D printed objects: detecting the use of an incorrect printing material

NASA Astrophysics Data System (ADS)

Straub, Jeremy

2017-06-01

A wide variety of characteristics of 3D printed objects have been linked to impaired structural integrity and use-efficacy. The printing material can also have a significant impact on the quality, utility and safety characteristics of a 3D printed object. Material issues can be created by vendor issues, physical security issues and human error. This paper presents and evaluates a system that can be used to detect incorrect material use in a 3D printer, using visible light imaging. Specifically, it assesses the ability to ascertain the difference between materials of different color and different types of material with similar coloration.

Waveforms for Active Sensing: Optical Waveform Design and Analysis for Ballistic Imaging Through Turbid Media

DTIC Science & Technology

2008-04-04

Poisson process, the probabilities of false alarm PFA and detection PD are computed as PFA P k1 N yk 0 k 1 eNXeNXek k! 1...character- istics (ROC) (PD versus PFA ) curves for detecting opaque objects in heavy fog, considering a detector with Xe 20 and a laser power as in...objects in this scattering me- dium up to a distance of 30 MFPs. Figure 4(b) shows the system performance curves by fixing the false alarm rate PFA at

A-Track: A New Approach for Detection of Moving Objects in FITS Images

NASA Astrophysics Data System (ADS)

Kılıç, Yücel; Karapınar, Nurdan; Atay, Tolga; Kaplan, Murat

2016-07-01

Small planet and asteroid observations are important for understanding the origin and evolution of the Solar System. In this work, we have developed a fast and robust pipeline, called A-Track, for detecting asteroids and comets in sequential telescope images. The moving objects are detected using a modified line detection algorithm, called ILDA. We have coded the pipeline in Python 3, where we have made use of various scientific modules in Python to process the FITS images. We tested the code on photometrical data taken by an SI-1100 CCD with a 1-meter telescope at TUBITAK National Observatory, Antalya. The pipeline can be used to analyze large data archives or daily sequential data. The code is hosted on GitHub under the GNU GPL v3 license.

Design and application of a structured phantom for detection performance comparison between breast tomosynthesis and digital mammography

NASA Astrophysics Data System (ADS)

Cockmartin, L.; Marshall, N. W.; Zhang, G.; Lemmens, K.; Shaheen, E.; Van Ongeval, C.; Fredenberg, E.; Dance, D. R.; Salvagnini, E.; Michielsen, K.; Bosmans, H.

2017-02-01

This paper introduces and applies a structured phantom with inserted target objects for the comparison of detection performance of digital breast tomosynthesis (DBT) against 2D full field digital mammography (FFDM). The phantom consists of a 48 mm thick breast-shaped polymethyl methacrylate (PMMA) container filled with water and PMMA spheres of different diameters. Three-dimensionally (3D) printed spiculated masses (diameter range: 3.8-9.7 mm) and non-spiculated masses (1.6-6.2 mm) along with microcalcifications (90-250 µm) were inserted as targets. Reproducibility of the phantom application was studied on a single system using 30 acquisitions. Next, the phantom was evaluated on five different combined FFDM & DBT systems and target detection was compared for FFDM and DBT modes. Ten phantom images in both FFDM and DBT modes were acquired on these 5 systems using automatic exposure control. Five readers evaluated target detectability. Images were read with the four-alternative forced-choice (4-AFC) paradigm, with always one segment including a target and 3 normal background segments. The percentage of correct responses (PC) was assessed based on 10 trials of each reader for each object type, size and imaging modality. Additionally, detection threshold diameters at 62.5 PC were assessed via non-linear regression fitting of the psychometric curve. The reproducibility study showed no significant differences in PC values. Evaluation of target detection in FFDM showed that microcalcification detection thresholds ranged between 110 and 118 µm and were similar compared to the detection in DBT (range of 106-158 µm). In DBT, detection of both mass types increased significantly (p  =  0.0001 and p  =  0.0002 for non-spiculated and spiculated masses respectively) compared to FFDM, achieving almost 100% detection for all spiculated mass diameters. In conclusion, a structured phantom with inserted targets was able to show evidence for detectability differences between FFDM and DBT modes for five commercial systems. This phantom has potential for application in task-based assessment at acceptance and commissioning testing of DBT systems.

Exploring the feasibility of traditional image querying tasks for industrial radiographs

NASA Astrophysics Data System (ADS)

Bray, Iliana E.; Tsai, Stephany J.; Jimenez, Edward S.

2015-08-01

Although there have been great strides in object recognition with optical images (photographs), there has been comparatively little research into object recognition for X-ray radiographs. Our exploratory work contributes to this area by creating an object recognition system designed to recognize components from a related database of radiographs. Object recognition for radiographs must be approached differently than for optical images, because radiographs have much less color-based information to distinguish objects, and they exhibit transmission overlap that alters perceived object shapes. The dataset used in this work contained more than 55,000 intermixed radiographs and photographs, all in a compressed JPEG form and with multiple ways of describing pixel information. For this work, a robust and efficient system is needed to combat problems presented by properties of the X-ray imaging modality, the large size of the given database, and the quality of the images contained in said database. We have explored various pre-processing techniques to clean the cluttered and low-quality images in the database, and we have developed our object recognition system by combining multiple object detection and feature extraction methods. We present the preliminary results of the still-evolving hybrid object recognition system.

Ground radar detection of meteoroids in space

NASA Technical Reports Server (NTRS)

Kessler, D. J.; Landry, P. M.; Gabbard, J. R.; Moran, J. L. T.

1980-01-01

A special test to lower the detection threshold for satellite fragments potentially dangerous to spacecraft was carried out by NORAD for NASA, using modified radar software. The Perimeter Acquisition Radar Attack Characterization System, a large, planar face, phased radar, operates at a nominal 430 MHz and produces 120 pulses per second, 45 of which were dedicated to search. In a time period of 8.4 hours of observations over three days, over 6000 objects were detected and tracked of which 37 were determined to have velocities greater than escape velocity. Six of these were larger objects with radar cross sections greater than 0.1 sq m and were probably orbiting satellites. A table gives the flux of both observed groups.

Computer aided detection of surgical retained foreign object for prevention

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hadjiiski, Lubomir, E-mail: lhadjisk@umich.edu; Marentis, Theodore C.; Rondon, Lucas

2015-03-15

Purpose: Surgical retained foreign objects (RFOs) have significant morbidity and mortality. They are associated with approximately $1.5 × 10{sup 9} annually in preventable medical costs. The detection accuracy of radiographs for RFOs is a mediocre 59%. The authors address the RFO problem with two complementary technologies: a three-dimensional (3D) gossypiboma micro tag, the μTag that improves the visibility of RFOs on radiographs, and a computer aided detection (CAD) system that detects the μTag. It is desirable for the CAD system to operate in a high specificity mode in the operating room (OR) and function as a first reader for themore » surgeon. This allows for fast point of care results and seamless workflow integration. The CAD system can also operate in a high sensitivity mode as a second reader for the radiologist to ensure the highest possible detection accuracy. Methods: The 3D geometry of the μTag produces a similar two dimensional (2D) depiction on radiographs regardless of its orientation in the human body and ensures accurate detection by a radiologist and the CAD. The authors created a data set of 1800 cadaver images with the 3D μTag and other common man-made surgical objects positioned randomly. A total of 1061 cadaver images contained a single μTag and the remaining 739 were without μTag. A radiologist marked the location of the μTag using an in-house developed graphical user interface. The data set was partitioned into three independent subsets: a training set, a validation set, and a test set, consisting of 540, 560, and 700 images, respectively. A CAD system with modules that included preprocessing μTag enhancement, labeling, segmentation, feature analysis, classification, and detection was developed. The CAD system was developed using the training and the validation sets. Results: On the training set, the CAD achieved 81.5% sensitivity with 0.014 false positives (FPs) per image in a high specificity mode for the surgeons in the OR and 96.1% sensitivity with 0.81 FPs per image in a high sensitivity mode for the radiologists. On the independent test set, the CAD achieved 79.5% sensitivity with 0.003 FPs per image in a high specificity mode for the surgeons and 90.2% sensitivity with 0.23 FPs per image in a high sensitivity mode for the radiologists. Conclusions: To the best of the authors’ knowledge, this is the first time a 3D μTag is used to produce a recognizable, substantially similar 2D projection on radiographs regardless of orientation in space. It is the first time a CAD system is used to search for man-made objects over anatomic background. The CAD system for the μTags achieved reasonable performance in both the high specificity and the high sensitivity modes.« less

Radar sensitivity to human heartbeats and respiration

NASA Astrophysics Data System (ADS)

Aardal, Øyvind; Brovoll, Sverre; Paichard, Yoann; Berger, Tor; Lande, Tor Sverre; Hamran, Svein-Erik

2015-05-01

Human heartbeats and respiration can be detected from a distance using radar. This can be used for medical applications and human being detection. It is useful to have a system independent measure of how detectable the vital signs are. In radar applications, the Radar Cross Section (RCS) is normally used to characterize the detectability of an object. Since the human vital signs are seen by the radar as movements of the torso, the modulations in the person RCS can be used as a system independent measure of the vital signs detectability. In this paper, measurements of persons seated in an anechoic chamber are presented. The measurements were calibrated using empty room and a metallic calibration sphere. A narrowband radar operating at frequencies from 500 MHz to 18 GHz in discrete steps was used. A turntable provided measurements at precise aspect angles all around the person under test. In an I & Q receiver, the heartbeat and respiration modulation is a combination of amplitude and phase mod- modulations. The measurements were filtered, leaving the modulations from the vital signs in the radar recordings. The procedure for RCS computation was applied to these filtered data, capturing the complex signatures. It was found that both the heartbeat and respiration detectability increase with increasing frequency. The heartbeat signatures are almost equal from the front and the back, while being almost undetectable from the sides of the person. The respiration signatures are slightly higher from the front than from the back, and smaller from the sides. The signature measurements presented in this paper provide an objective system independent measure of the detectability of human vital signs as a function of frequency and aspect angle. These measures are useful for example in system design and in assessing real measurement scenarios.

The Whipple Mission: Exploring the Kuiper Belt and the Oort Cloud

NASA Astrophysics Data System (ADS)

Alcock, Charles; Brown, Michael; Gauron, Tom; Heneghan, Cate; Holman, Matthew; Kenter, Almus; Kraft, Ralph; Livingstone, John; Murray-Clay, Ruth; Nulsen, Paul; Payne, Matthew; Schlichting, Hilke; Trangsrud, Amy; Vrtilek, Jan; Werner, Michael

2015-11-01

Whipple will characterize the small body populations of the Kuiper Belt and the Oort Cloud with a blind occultation survey, detecting objects when they briefly (~1 second) interrupt the light from background stars, allowing the detection of much more distant and/or smaller objects than can be seen in reflected sunlight. Whipple will reach much deeper into the unexplored frontier of the outer solar system than any other mission, current or proposed. Whipple will look back to the dawn of the solar system by discovering its most remote bodies where primordial processes left their imprint.Specifically, Whipple will monitor large numbers of stars at high cadences (~12,000 stars at 20 Hz to examine Kuiper Belt events; as many as ~36,000 stars at 5 Hz to explore deep into the Oort Cloud, where events are less frequent). Analysis of the detected events will allow us to determine the size spectrum of bodies in the Kuiper Belt with radii as small as ~1 km. This will allow the testing of models of the growth and later collisional erosion of planetesimals in the early solar system. Whipple will explore the Oort Cloud, potentially detecting objects as far out as ~10,000 AU. This will be the first direct exploration of the Oort Cloud since the original hypothesis of 1950.Whipple is a Discovery class mission that was proposed to NASA in response to the 2014 Announcement of Opportunity. The mission is being developed jointly by the Smithsonian Astrophysical Observatory, Jet Propulsion Laboratories, and Ball Aerospace & Technologies, with telescope optics from L-3 Integrated Optical Systems and imaging sensors from Teledyne Imaging Sensors.

Searching for Solar System Wide Binaries with Pan-STARRS-1

NASA Astrophysics Data System (ADS)

Holman, Matthew J.; Protopapas, P.; Tholen, D. J.

2007-10-01

Roughly 60% of the observing time of the Pan-STARRS-1 (PS1) telescope will be dedicated to a "3pi steradian" survey with an observing cadence that is designed for the detection of near-Earth asteroids and slow-moving solar system bodies. Over this course of its 3.5 year cience mission, this unprecedented survey will discover nearly every asteroid, Trojan, Centaur, long-period comet, short-period comet, and trans-neptunian object (TNO) brighter than magnitude R=23. This census will be used to address a large number of questions regarding the physical and dynamical properties of the various small body populations of the solar system. Roughly 1-2% of TNOs are wide binaries with companions at separations greater than 1 arcsec and brightness differences less than 2 magnitudes (Kern & Elliot 2006; Noll et al 2007). These can be readily detected by PS1; we will carry out such a search with PS1 data. To do so, we will modify the Pan-STARRS Moving Object Processing System (MOPS) such that it will associate the components of resolved or marginally resolved binaries, link such pairs of detections obtained at different epochs, and the estimate the relative orbit of the binary. We will also determine the efficiency with which such binaries are detected as a function of the binary's relative orbit and the relative magnitudes of the components. Based on an estimated 7000 TNOs that PS1 will discover, we anticipate finding 70-140 wide binaries. The PS1 data, 60 epochs over three years, is naturally suited to determining the orbits of these objects. Our search will accurately determine the binary fraction for a variety of subclasses of TNOs.

Developing an Environmental Scanning System.

ERIC Educational Resources Information Center

Morrison, James L.

A step-by-step approach is provided for developing an environmental scanning system for colleges and universities to assist them in planning for the future. The objectives of such a system are to detect social, scientific, economic, technical, and political interactions important to the organization; define potential threats and opportunities from…

Boosting-Based Optimization as a Generic Framework for Novelty and Fraud Detection in Complex Strategies

NASA Astrophysics Data System (ADS)

Gavrishchaka, Valeriy V.; Kovbasinskaya, Maria; Monina, Maria

2008-11-01

Novelty detection is a very desirable additional feature of any practical classification or forecasting system. Novelty and rare patterns detection is the main objective in such applications as fault/abnormality discovery in complex technical and biological systems, fraud detection and risk management in financial and insurance industry. Although many interdisciplinary approaches for rare event modeling and novelty detection have been proposed, significant data incompleteness due to the nature of the problem makes it difficult to find a universal solution. Even more challenging and much less formalized problem is novelty detection in complex strategies and models where practical performance criteria are usually multi-objective and the best state-of-the-art solution is often not known due to the complexity of the task and/or proprietary nature of the application area. For example, it is much more difficult to detect a series of small insider trading or other illegal transactions mixed with valid operations and distributed over long time period according to a well-designed strategy than a single, large fraudulent transaction. Recently proposed boosting-based optimization was shown to be an effective generic tool for the discovery of stable multi-component strategies/models from the existing parsimonious base strategies/models in financial and other applications. Here we outline how the same framework can be used for novelty and fraud detection in complex strategies and models.

Three-dimensional laser radar modeling

NASA Astrophysics Data System (ADS)

Steinvall, Ove K.; Carlsson, Tomas

2001-09-01

Laser radars have the unique capability to give intensity and full 3-D images of an object. Doppler lidars can give velocity and vibration characteristics of an objects. These systems have many civilian and military applications such as terrain modelling, depth sounding, object detection and classification as well as object positioning. In order to derive the signal waveform from the object one has to account for the laser pulse time characteristics, media effects such as the atmospheric attenuation and turbulence effects or scattering properties, the target shape and reflection (BRDF), speckle noise together with the receiver and background noise. Finally the type of waveform processing (peak detection, leading edge etc.) is needed to model the sensor output to be compared with observations. We have developed a computer model which models performance of a 3-D laser radar. We will give examples of signal waveforms generated from model different targets calculated by integrating the laser beam profile in space and time over the target including reflection characteristics during different speckle and turbulence conditions. The result will be of help when designing and using new laser radar systems. The importance of different type of signal processing of the waveform in order to fulfil performance goals will be shown.

Moving Object Detection in Heterogeneous Conditions in Embedded Systems.

PubMed

Garbo, Alessandro; Quer, Stefano

2017-07-01

This paper presents a system for moving object exposure, focusing on pedestrian detection, in external, unfriendly, and heterogeneous environments. The system manipulates and accurately merges information coming from subsequent video frames, making small computational efforts in each single frame. Its main characterizing feature is to combine several well-known movement detection and tracking techniques, and to orchestrate them in a smart way to obtain good results in diversified scenarios. It uses dynamically adjusted thresholds to characterize different regions of interest, and it also adopts techniques to efficiently track movements, and detect and correct false positives. Accuracy and reliability mainly depend on the overall receipt, i.e., on how the software system is designed and implemented, on how the different algorithmic phases communicate information and collaborate with each other, and on how concurrency is organized. The application is specifically designed to work with inexpensive hardware devices, such as off-the-shelf video cameras and small embedded computational units, eventually forming an intelligent urban grid. As a matter of fact, the major contribution of the paper is the presentation of a tool for real-time applications in embedded devices with finite computational (time and memory) resources. We run experimental results on several video sequences (both home-made and publicly available), showing the robustness and accuracy of the overall detection strategy. Comparisons with state-of-the-art strategies show that our application has similar tracking accuracy but much higher frame-per-second rates.

Moving Object Detection in Heterogeneous Conditions in Embedded Systems

PubMed Central

Garbo, Alessandro

2017-01-01

This paper presents a system for moving object exposure, focusing on pedestrian detection, in external, unfriendly, and heterogeneous environments. The system manipulates and accurately merges information coming from subsequent video frames, making small computational efforts in each single frame. Its main characterizing feature is to combine several well-known movement detection and tracking techniques, and to orchestrate them in a smart way to obtain good results in diversified scenarios. It uses dynamically adjusted thresholds to characterize different regions of interest, and it also adopts techniques to efficiently track movements, and detect and correct false positives. Accuracy and reliability mainly depend on the overall receipt, i.e., on how the software system is designed and implemented, on how the different algorithmic phases communicate information and collaborate with each other, and on how concurrency is organized. The application is specifically designed to work with inexpensive hardware devices, such as off-the-shelf video cameras and small embedded computational units, eventually forming an intelligent urban grid. As a matter of fact, the major contribution of the paper is the presentation of a tool for real-time applications in embedded devices with finite computational (time and memory) resources. We run experimental results on several video sequences (both home-made and publicly available), showing the robustness and accuracy of the overall detection strategy. Comparisons with state-of-the-art strategies show that our application has similar tracking accuracy but much higher frame-per-second rates. PMID:28671582

Testing solar system formation models using Pan-STARRS1 detections of nearly inactive Manx comets

NASA Astrophysics Data System (ADS)

Boe, Benjamin; Jedicke, Robert; Meech, Karen Jean; Morbidelli, Alessandro; Wiegert, Paul

2016-10-01

Newly discovered Manx comets show low levels of sublimation at perihelion indicating significantly lower volatile abundance compared to typical long period comets. The S-class spectrum of Manx comet C/2014 S3 (PANSTARRS) indicates that they may have formed in the inner solar system and were later perturbed to the highly eccentric orbits observed today (Meech et al. 2016). We used the Pan-STARRS1 observation history and its Moving Object Processing System (MOPS) (Denneau et al. 2013) to model Manx detections since Pan-STARRS has been the primary discovery source of Manx comets. A synthetic Manx population was generated according to the Wiegert and Tremaine (1999) model and processed through MOPS to determine the expected Pan-STARRS1 detections and the corresponding detection efficiencies for Manx comets as a function of each orbital parameter and object size. The population of normal long period comets (LPCs) was modeled in the same fashion. Unbiased populations for LPCs and Manx comets were computed by correcting the real comet populations with the detection efficiencies. Finally, the ratio of the bias corrected number of Manx comets to LPCs is compared to the predictions of various solar system formation models.References:Meech, K. J. et al. (2016), Science Advances 2, 4, id. E1600038.Denneau, L. et al. (2013), Publications of the Astronomical Society of the Pacific, 125, 926, 357-395Wiegert, P. and Tremaine, S. (1999), Icarus, 137, 1, 84-121.

A mathematical model of extremely low frequency ocean induced electromagnetic noise

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dautta, Manik, E-mail: manik.dautta@anyeshan.com; Faruque, Rumana Binte, E-mail: rumana.faruque@anyeshan.com; Islam, Rakibul, E-mail: rakibul.islam@anyeshan.com

2016-07-12

Magnetic Anomaly Detection (MAD) system uses the principle that ferromagnetic objects disturb the magnetic lines of force of the earth. These lines of force are able to pass through both water and air in similar manners. A MAD system, usually mounted on an aerial vehicle, is thus often employed to confirm the detection and accomplish localization of large ferromagnetic objects submerged in a sea-water environment. However, the total magnetic signal encountered by a MAD system includes contributions from a myriad of low to Extremely Low Frequency (ELF) sources. The goal of the MAD system is to detect small anomaly signalsmore » in the midst of these low-frequency interfering signals. Both the Range of Detection (R{sub d}) and the Probability of Detection (P{sub d}) are limited by the ratio of anomaly signal strength to the interfering magnetic noise. In this paper, we report a generic mathematical model to estimate the signal-to-noise ratio or SNR. Since time-variant electro-magnetic signals are affected by conduction losses due to sea-water conductivity and the presence of air-water interface, we employ the general formulation of dipole induced electromagnetic field propagation in stratified media [1]. As a first step we employ a volumetric distribution of isolated elementary magnetic dipoles, each having its own dipole strength and orientation, to estimate the magnetic noise observed by a MAD system. Numerical results are presented for a few realizations out of an ensemble of possible realizations of elementary dipole source distributions.« less

Comparison of experimental three-band IR detection of buried objects and multiphysics simulations

NASA Astrophysics Data System (ADS)

Rabelo, Renato C.; Tilley, Heather P.; Catterlin, Jeffrey K.; Karunasiri, Gamani; Alves, Fabio D. P.

2018-04-01

A buried-object detection system composed of a LWIR, a MWIR and a SWIR camera, along with a set of ground and ambient temperature sensors was constructed and tested. The objects were buried in a 1.2x1x0.3 m3 sandbox and surface temperature (using LWIR and MWIR cameras) and reflection (using SWIR camera) were recoded throughout the day. Two objects (aluminum and Teflon) with volume of about 2.5x10-4 m3 , were placed at varying depths during the measurements. Ground temperature sensors buried at three different depths measured the vertical temperature profile within the sandbox, while the weather station recorded the ambient temperature and solar radiation intensity. Images from the three cameras were simultaneously acquired in five-minute intervals throughout many days. An algorithm to postprocess and combine the images was developed in order to maximize the probability of detection by identifying thermal anomalies (temperature contrast) resulting from the presence of the buried object in an otherwise homogeneous medium. A simplified detection metric based on contrast differences was established to allow the evaluation of the image processing method. Finite element simulations were performed, reproducing the experiment conditions and, when possible, incorporated with data coming from actual measurements. Comparisons between experiment and simulation results were performed and the simulation parameters were adjusted until images generated from both methods are matched, aiming at obtaining insights of the buried material properties. Preliminary results show a great potential for detection of shallowburied objects such as land mines and IEDs and possible identification using finite element generated maps fitting measured surface maps.

3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands

PubMed Central

Mateo, Carlos M.; Gil, Pablo; Torres, Fernando

2016-01-01

Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object’s surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand’s fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments. PMID:27164102

Features of Different Inorganic Scintillators Used in Neutron-Radiation Systems for Illegal Substance Detection

NASA Astrophysics Data System (ADS)

Batyaev, V. F.; Belichenko, S. G.; Bestaev, R. R.

2016-04-01

The work is devoted to a quantitative comparison of different inorganic scintillators to be used in neutron-radiation inspection systems. Such systems can be based on the tagged neutron (TN) method and have a significant potential in different applications such as detection of explosives, drugs, mines, identification of chemical warfare agents, assay of nuclear materials and human body composition [1]-[3]. The elemental composition of an inspected object is determined via spectrometry of gammas from the object bombarded by neutrons which are tagged by an alpha-detector built inside a neutron generator. This creates a task to find a quantitative indicator of the object identification quality (via elemental composition) as a function of basic parameters of the γ-detectors, such as their efficiency, energy and time resolutions, which in turn are generally defined by a scintillator of the detector. We have tried to solve the task for a set of four scintillators which are often used in the study of TN method, namely BGO, LaBr3, LYSO, NaI(Tl), whose basic parameters are well known [4]-[7].

Moving Object Detection Using Scanning Camera on a High-Precision Intelligent Holder

PubMed Central

Chen, Shuoyang; Xu, Tingfa; Li, Daqun; Zhang, Jizhou; Jiang, Shenwang

2016-01-01

During the process of moving object detection in an intelligent visual surveillance system, a scenario with complex background is sure to appear. The traditional methods, such as “frame difference” and “optical flow”, may not able to deal with the problem very well. In such scenarios, we use a modified algorithm to do the background modeling work. In this paper, we use edge detection to get an edge difference image just to enhance the ability of resistance illumination variation. Then we use a “multi-block temporal-analyzing LBP (Local Binary Pattern)” algorithm to do the segmentation. In the end, a connected component is used to locate the object. We also produce a hardware platform, the core of which consists of the DSP (Digital Signal Processor) and FPGA (Field Programmable Gate Array) platforms and the high-precision intelligent holder. PMID:27775671

A Passive Learning Sensor Architecture for Multimodal Image Labeling: An Application for Social Robots.

PubMed

Gutiérrez, Marco A; Manso, Luis J; Pandya, Harit; Núñez, Pedro

2017-02-11

Object detection and classification have countless applications in human-robot interacting systems. It is a necessary skill for autonomous robots that perform tasks in household scenarios. Despite the great advances in deep learning and computer vision, social robots performing non-trivial tasks usually spend most of their time finding and modeling objects. Working in real scenarios means dealing with constant environment changes and relatively low-quality sensor data due to the distance at which objects are often found. Ambient intelligence systems equipped with different sensors can also benefit from the ability to find objects, enabling them to inform humans about their location. For these applications to succeed, systems need to detect the objects that may potentially contain other objects, working with relatively low-resolution sensor data. A passive learning architecture for sensors has been designed in order to take advantage of multimodal information, obtained using an RGB-D camera and trained semantic language models. The main contribution of the architecture lies in the improvement of the performance of the sensor under conditions of low resolution and high light variations using a combination of image labeling and word semantics. The tests performed on each of the stages of the architecture compare this solution with current research labeling techniques for the application of an autonomous social robot working in an apartment. The results obtained demonstrate that the proposed sensor architecture outperforms state-of-the-art approaches.

Proto-object categorisation and local gist vision using low-level spatial features.

PubMed

Martins, Jaime A; Rodrigues, J M F; du Buf, J M H

2015-09-01

Object categorisation is a research area with significant challenges, especially in conditions with bad lighting, occlusions, different poses and similar objects. This makes systems that rely on precise information unable to perform efficiently, like a robotic arm that needs to know which objects it can reach. We propose a biologically inspired object detection and categorisation framework that relies on robust low-level object shape. Using only edge conspicuity and disparity features for scene figure-ground segregation and object categorisation, a trained neural network classifier can quickly categorise broad object families and consequently bootstrap a low-level scene gist system. We argue that similar processing is possibly located in the parietal pathway leading to the LIP cortex and, via areas V5/MT and MST, providing useful information to the superior colliculus for eye and head control. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Simultaneous Detection and Tracking of Pedestrian from Panoramic Laser Scanning Data

NASA Astrophysics Data System (ADS)

Xiao, Wen; Vallet, Bruno; Schindler, Konrad; Paparoditis, Nicolas

2016-06-01

Pedestrian traffic flow estimation is essential for public place design and construction planning. Traditional data collection by human investigation is tedious, inefficient and expensive. Panoramic laser scanners, e.g. Velodyne HDL-64E, which scan surroundings repetitively at a high frequency, have been increasingly used for 3D object tracking. In this paper, a simultaneous detection and tracking (SDAT) method is proposed for precise and automatic pedestrian trajectory recovery. First, the dynamic environment is detected using two different methods, Nearest-point and Max-distance. Then, all the points on moving objects are transferred into a space-time (x, y, t) coordinate system. The pedestrian detection and tracking amounts to assign the points belonging to pedestrians into continuous trajectories in space-time. We formulate the point assignment task as an energy function which incorporates the point evidence, trajectory number, pedestrian shape and motion. A low energy trajectory will well explain the point observations, and have plausible trajectory trend and length. The method inherently filters out points from other moving objects and false detections. The energy function is solved by a two-step optimization process: tracklet detection in a short temporal window; and global tracklet association through the whole time span. Results demonstrate that the proposed method can automatically recover the pedestrians trajectories with accurate positions and low false detections and mismatches.

Long-term strategy for the statistical design of a forest health monitoring system

Treesearch

Hans T. Schreuder; Raymond L. Czaplewski

1993-01-01

A conceptual framework is given for a broad-scale survey of forest health that accomplishes three objectives: generate descriptive statistics; detect changes in such statistics; and simplify analytical inferences that identify, and possibly establish cause-effect relationships. Our paper discusses the development of sampling schemes to satisfy these three objectives,...

Spacewatch discovery of near-Earth asteroids

NASA Technical Reports Server (NTRS)

Gehrels, Tom

1992-01-01

Our overall scientific goal is to survey the solar system to completion - that is, to find the various populations and to study their statistics, interrelations, and origins. The practical benefit to SERC is that we are finding Earth-approaching asteroids that are accessible for mining. Our system can detect Earth-approachers in the 1-km size range even when they are far away, and can detect smaller objects when they are moving rapidly past Earth. Until Spacewatch, the size range of 6-300 meters in diameter for the near-Earth asteroids was unexplored. This important region represents the transition between the meteorites and the larger observed near-Earth asteroids. One of our Spacewatch discoveries, 1991 VG, may be representative of a new orbital class of object. If it is really a natural object, and not man-made, its orbital parameters are closer to those of the Earth than we have seen before; its delta V is the lowest of all objects known thus far. We may expect new discoveries as we continue our surveying, with fine-tuning of the techniques.

System of technical vision for autonomous unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Bondarchuk, A. S.

2018-05-01

This paper is devoted to the implementation of image recognition algorithm using the LabVIEW software. The created virtual instrument is designed to detect the objects on the frames from the camera mounted on the UAV. The trained classifier is invariant to changes in rotation, as well as to small changes in the camera's viewing angle. Finding objects in the image using particle analysis, allows you to classify regions of different sizes. This method allows the system of technical vision to more accurately determine the location of the objects of interest and their movement relative to the camera.