Sample records for object detection system

  1. Ferromagnetic Objects Magnetovision Detection System.

    PubMed

    Nowicki, Michał; Szewczyk, Roman

    2013-12-02

    This paper presents the application of a weak magnetic fields magnetovision scanning system for detection of dangerous ferromagnetic objects. A measurement system was developed and built to study the magnetic field vector distributions. The measurements of the Earth's field distortions caused by various ferromagnetic objects were carried out. The ability for passive detection of hidden or buried dangerous objects and the determination of their location was demonstrated.

  2. Vision-based object detection and recognition system for intelligent vehicles

    NASA Astrophysics Data System (ADS)

    Ran, Bin; Liu, Henry X.; Martono, Wilfung

    1999-01-01

    Recently, a proactive crash mitigation system is proposed to enhance the crash avoidance and survivability of the Intelligent Vehicles. Accurate object detection and recognition system is a prerequisite for a proactive crash mitigation system, as system component deployment algorithms rely on accurate hazard detection, recognition, and tracking information. In this paper, we present a vision-based approach to detect and recognize vehicles and traffic signs, obtain their information, and track multiple objects by using a sequence of color images taken from a moving vehicle. The entire system consist of two sub-systems, the vehicle detection and recognition sub-system and traffic sign detection and recognition sub-system. Both of the sub- systems consist of four models: object detection model, object recognition model, object information model, and object tracking model. In order to detect potential objects on the road, several features of the objects are investigated, which include symmetrical shape and aspect ratio of a vehicle and color and shape information of the signs. A two-layer neural network is trained to recognize different types of vehicles and a parameterized traffic sign model is established in the process of recognizing a sign. Tracking is accomplished by combining the analysis of single image frame with the analysis of consecutive image frames. The analysis of the single image frame is performed every ten full-size images. The information model will obtain the information related to the object, such as time to collision for the object vehicle and relative distance from the traffic sings. Experimental results demonstrated a robust and accurate system in real time object detection and recognition over thousands of image frames.

  3. 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.

  4. System and method for detecting a faulty object in a system

    DOEpatents

    Gunnels, John A.; Gustavson, Fred Gehrung; Engle, Robert Daniel

    2010-12-14

    A method (and system) for detecting at least one faulty object in a system including a plurality of objects in communication with each other in an n-dimensional architecture, includes probing a first plane of objects in the n-dimensional architecture and probing at least one other plane of objects in the n-dimensional architecture which would result in identifying a faulty object in the system.

  5. System and method for detecting a faulty object in a system

    DOEpatents

    Gunnels, John A [Brewster, NY; Gustavson, Fred Gehrung [Briarcliff Manor, NY; Engle, Robert Daniel [St. Louis, MO

    2009-03-17

    A method (and system) for detecting at least one faulty object in a system including a plurality of objects in communication with each other in an n-dimensional architecture, includes probing a first plane of objects in the n-dimensional architecture and probing at least one other plane of objects in the n-dimensional architecture which would result in identifying a faulty object in the system.

  6. 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

  7. Hardware Evaluation Of Heavy Truck Side And Rear Object Detection Systems

    DOT National Transportation Integrated Search

    1995-01-01

    This paper focuses on two types of electronics-based object detection systems for heavy truck applications: those sensing the presence of objects to the rear of the vehicle (referred to as Rear Object Detection Systems, or RODS) and those sensing the...

  8. 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.

  9. 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

  10. 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.

  11. Automated object detection and tracking with a flash LiDAR system

    NASA Astrophysics Data System (ADS)

    Hammer, Marcus; Hebel, Marcus; Arens, Michael

    2016-10-01

    The detection of objects, or persons, is a common task in the fields of environment surveillance, object observation or danger defense. There are several approaches for automated detection with conventional imaging sensors as well as with LiDAR sensors, but for the latter the real-time detection is hampered by the scanning character and therefore by the data distortion of most LiDAR systems. The paper presents a solution for real-time data acquisition of a flash LiDAR sensor with synchronous raw data analysis, point cloud calculation, object detection, calculation of the next best view and steering of the pan-tilt head of the sensor. As a result the attention is always focused on the object, independent of the behavior of the object. Even for highly volatile and rapid changes in the direction of motion the object is kept in the field of view. The experimental setup used in this paper is realized with an elementary person detection algorithm in medium distances (20 m to 60 m) to show the efficiency of the system for objects with a high angular speed. It is easy to replace the detection part by any other object detection algorithm and thus it is easy to track nearly any object, for example a car or a boat or an UAV in various distances.

  12. Detection and Tracking of Moving Objects with Real-Time Onboard Vision System

    NASA Astrophysics Data System (ADS)

    Erokhin, D. Y.; Feldman, A. B.; Korepanov, S. E.

    2017-05-01

    Detection of moving objects in video sequence received from moving video sensor is a one of the most important problem in computer vision. The main purpose of this work is developing set of algorithms, which can detect and track moving objects in real time computer vision system. This set includes three main parts: the algorithm for estimation and compensation of geometric transformations of images, an algorithm for detection of moving objects, an algorithm to tracking of the detected objects and prediction their position. The results can be claimed to create onboard vision systems of aircraft, including those relating to small and unmanned aircraft.

  13. Real-time system for imaging and object detection with a multistatic GPR array

    DOEpatents

    Paglieroni, David W; Beer, N Reginald; Bond, Steven W; Top, Philip L; Chambers, David H; Mast, Jeffrey E; Donetti, John G; Mason, Blake C; Jones, Steven M

    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.

  14. 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.

  15. Imaging, object detection, and change detection with a polarized multistatic GPR array

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

    Beer, N. Reginald; Paglieroni, David W.

    A polarized detection system performs imaging, object detection, and change detection factoring in the orientation of an object relative to the orientation of transceivers. The polarized detection system may operate on one of several modes of operation based on whether the imaging, object detection, or change detection is performed separately for each transceiver orientation. In combined change mode, the polarized detection system performs imaging, object detection, and change detection separately for each transceiver orientation, and then combines changes across polarizations. In combined object mode, the polarized detection system performs imaging and object detection separately for each transceiver orientation, and thenmore » combines objects across polarizations and performs change detection on the result. In combined image mode, the polarized detection system performs imaging separately for each transceiver orientation, and then combines images across polarizations and performs object detection followed by change detection on the result.« less

  16. Point pattern match-based change detection in a constellation of previously detected objects

    DOEpatents

    Paglieroni, David W.

    2016-06-07

    A method and system is provided that applies attribute- and topology-based change detection to objects that were detected on previous scans of a medium. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, detection strength, size, elongation, orientation, etc. The locations define a three-dimensional network topology forming a constellation of previously detected objects. The change detection system stores attributes of the previously detected objects in a constellation database. The change detection system detects changes by comparing the attributes and topological consistency of newly detected objects encountered during a new scan of the medium to previously detected objects in the constellation database. The change detection system may receive the attributes of the newly detected objects as the objects are detected by an object detection system in real time.

  17. 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.

  18. Buried object detection in GPR images

    DOEpatents

    Paglieroni, David W; Chambers, David H; Bond, Steven W; Beer, W. Reginald

    2014-04-29

    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.

  19. Road detection and buried object detection in elevated EO/IR imagery

    NASA Astrophysics Data System (ADS)

    Kennedy, Levi; Kolba, Mark P.; Walters, Joshua R.

    2012-06-01

    To assist the warfighter in visually identifying potentially dangerous roadside objects, the U.S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD) has developed an elevated video sensor system testbed for data collection. This system provides color and mid-wave infrared (MWIR) imagery. Signal Innovations Group (SIG) has developed an automated processing capability that detects the road within the sensor field of view and identifies potentially threatening buried objects within the detected road. The road detection algorithm leverages system metadata to project the collected imagery onto a flat ground plane, allowing for more accurate detection of the road as well as the direct specification of realistic physical constraints in the shape of the detected road. Once the road has been detected in an image frame, a buried object detection algorithm is applied to search for threatening objects within the detected road space. The buried object detection algorithm leverages textural and pixel intensity-based features to detect potential anomalies and then classifies them as threatening or non-threatening objects. Both the road detection and the buried object detection algorithms have been developed to facilitate their implementation in real-time in the NVESD system.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. Attribute and topology based change detection in a constellation of previously detected objects

    DOEpatents

    Paglieroni, David W.; Beer, Reginald N.

    2016-01-19

    A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.

  5. 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.

  6. 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

  7. 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.

  8. Determining root correspondence between previously and newly detected objects

    DOEpatents

    Paglieroni, David W.; Beer, N Reginald

    2014-06-17

    A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.

  9. Research on moving object detection based on frog's eyes

    NASA Astrophysics Data System (ADS)

    Fu, Hongwei; Li, Dongguang; Zhang, Xinyuan

    2008-12-01

    On the basis of object's information processing mechanism with frog's eyes, this paper discussed a bionic detection technology which suitable for object's information processing based on frog's vision. First, the bionics detection theory by imitating frog vision is established, it is an parallel processing mechanism which including pick-up and pretreatment of object's information, parallel separating of digital image, parallel processing, and information synthesis. The computer vision detection system is described to detect moving objects which has special color, special shape, the experiment indicates that it can scheme out the detecting result in the certain interfered background can be detected. A moving objects detection electro-model by imitating biologic vision based on frog's eyes is established, the video simulative signal is digital firstly in this system, then the digital signal is parallel separated by FPGA. IN the parallel processing, the video information can be caught, processed and displayed in the same time, the information fusion is taken by DSP HPI ports, in order to transmit the data which processed by DSP. This system can watch the bigger visual field and get higher image resolution than ordinary monitor systems. In summary, simulative experiments for edge detection of moving object with canny algorithm based on this system indicate that this system can detect the edge of moving objects in real time, the feasibility of bionic model was fully demonstrated in the engineering system, and it laid a solid foundation for the future study of detection technology by imitating biologic vision.

  10. 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.

  11. 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

  12. 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.

  13. Impulse radar imaging system for concealed object detection

    NASA Astrophysics Data System (ADS)

    Podd, F. J. W.; David, M.; Iqbal, G.; Hussain, F.; Morris, D.; Osakue, E.; Yeow, Y.; Zahir, S.; Armitage, D. W.; Peyton, A. J.

    2013-10-01

    -to-noise parameter to determine how the frequencies contained in the echo dataset are normalised. The chosen image reconstruction algorithm is based on the back-projection method. The algorithm was implemented in MATLAB and uses a pre-calculated sensitivity matrix to increase the computation speed. The results include both 2D and 3D image datasets. The 3D datasets were obtained by scanning the dual sixteen element linear antenna array over the test object. The system has been tested on both humans and mannequin test objects. The front surface of an object placed on the human/mannequin torso is clearly visible, but its presence is also seen from a tell-tale imaging characteristic. This characteristic is caused by a reduction in the wave velocity as the electromagnetic radiation passes through the object, and manifests as an indentation in the reconstructed image that is readily identifiable. The prototype system has been shown to easily detect a 12 mm x 30 mm x70 mm plastic object concealed under clothing.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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

  3. Object detection with a multistatic array using singular value decomposition

    DOEpatents

    Hallquist, Aaron T.; Chambers, David H.

    2014-07-01

    A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across a surface and that travels down the surface. The detection system converts the return signals from a time domain to a frequency domain, resulting in frequency return signals. The detection system then performs a singular value decomposition for each frequency to identify singular values for each frequency. The detection system then detects the presence of a subsurface object based on a comparison of the identified singular values to expected singular values when no subsurface object is present.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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 ...).

  11. 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.

  12. 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

  13. 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.

  14. Seeing Objects as Faces Enhances Object Detection.

    PubMed

    Takahashi, Kohske; Watanabe, Katsumi

    2015-10-01

    The face is a special visual stimulus. Both bottom-up processes for low-level facial features and top-down modulation by face expectations contribute to the advantages of face perception. However, it is hard to dissociate the top-down factors from the bottom-up processes, since facial stimuli mandatorily lead to face awareness. In the present study, using the face pareidolia phenomenon, we demonstrated that face awareness, namely seeing an object as a face, enhances object detection performance. In face pareidolia, some people see a visual stimulus, for example, three dots arranged in V shape, as a face, while others do not. This phenomenon allows us to investigate the effect of face awareness leaving the stimulus per se unchanged. Participants were asked to detect a face target or a triangle target. While target per se was identical between the two tasks, the detection sensitivity was higher when the participants recognized the target as a face. This was the case irrespective of the stimulus eccentricity or the vertical orientation of the stimulus. These results demonstrate that seeing an object as a face facilitates object detection via top-down modulation. The advantages of face perception are, therefore, at least partly, due to face awareness.

  15. Seeing Objects as Faces Enhances Object Detection

    PubMed Central

    Watanabe, Katsumi

    2015-01-01

    The face is a special visual stimulus. Both bottom-up processes for low-level facial features and top-down modulation by face expectations contribute to the advantages of face perception. However, it is hard to dissociate the top-down factors from the bottom-up processes, since facial stimuli mandatorily lead to face awareness. In the present study, using the face pareidolia phenomenon, we demonstrated that face awareness, namely seeing an object as a face, enhances object detection performance. In face pareidolia, some people see a visual stimulus, for example, three dots arranged in V shape, as a face, while others do not. This phenomenon allows us to investigate the effect of face awareness leaving the stimulus per se unchanged. Participants were asked to detect a face target or a triangle target. While target per se was identical between the two tasks, the detection sensitivity was higher when the participants recognized the target as a face. This was the case irrespective of the stimulus eccentricity or the vertical orientation of the stimulus. These results demonstrate that seeing an object as a face facilitates object detection via top-down modulation. The advantages of face perception are, therefore, at least partly, due to face awareness. PMID:27648219

  16. 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.

  17. Learned filters for object detection in multi-object visual tracking

    NASA Astrophysics Data System (ADS)

    Stamatescu, Victor; Wong, Sebastien; McDonnell, Mark D.; Kearney, David

    2016-05-01

    We investigate the application of learned convolutional filters in multi-object visual tracking. The filters were learned in both a supervised and unsupervised manner from image data using artificial neural networks. This work follows recent results in the field of machine learning that demonstrate the use learned filters for enhanced object detection and classification. Here we employ a track-before-detect approach to multi-object tracking, where tracking guides the detection process. The object detection provides a probabilistic input image calculated by selecting from features obtained using banks of generative or discriminative learned filters. We present a systematic evaluation of these convolutional filters using a real-world data set that examines their performance as generic object detectors.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. Decoupling Object Detection and Categorization

    ERIC Educational Resources Information Center

    Mack, Michael L.; Palmeri, Thomas J.

    2010-01-01

    We investigated whether there exists a behavioral dependency between object detection and categorization. Previous work (Grill-Spector & Kanwisher, 2005) suggests that object detection and basic-level categorization may be the very same perceptual mechanism: As objects are parsed from the background they are categorized at the basic level. In…

  3. 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.

  4. 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.

  5. 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

  6. 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].

  7. 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.

  8. The subjective experience of object recognition: comparing metacognition for object detection and object categorization.

    PubMed

    Meuwese, Julia D I; van Loon, Anouk M; Lamme, Victor A F; Fahrenfort, Johannes J

    2014-05-01

    Perceptual decisions seem to be made automatically and almost instantly. Constructing a unitary subjective conscious experience takes more time. For example, when trying to avoid a collision with a car on a foggy road you brake or steer away in a reflex, before realizing you were in a near accident. This subjective aspect of object recognition has been given little attention. We used metacognition (assessed with confidence ratings) to measure subjective experience during object detection and object categorization for degraded and masked objects, while objective performance was matched. Metacognition was equal for degraded and masked objects, but categorization led to higher metacognition than did detection. This effect turned out to be driven by a difference in metacognition for correct rejection trials, which seemed to be caused by an asymmetry of the distractor stimulus: It does not contain object-related information in the detection task, whereas it does contain such information in the categorization task. Strikingly, this asymmetry selectively impacted metacognitive ability when objective performance was matched. This finding reveals a fundamental difference in how humans reflect versus act on information: When matching the amount of information required to perform two tasks at some objective level of accuracy (acting), metacognitive ability (reflecting) is still better in tasks that rely on positive evidence (categorization) than in tasks that rely more strongly on an absence of evidence (detection).

  9. Monocular Vision-Based Underwater Object Detection

    PubMed Central

    Zhang, Zhen; Dai, Fengzhao; Bu, Yang; Wang, Huibin

    2017-01-01

    In this paper, we propose an underwater object detection method using monocular vision sensors. In addition to commonly used visual features such as color and intensity, we investigate the potential of underwater object detection using light transmission information. The global contrast of various features is used to initially identify the region of interest (ROI), which is then filtered by the image segmentation method, producing the final underwater object detection results. We test the performance of our method with diverse underwater datasets. Samples of the datasets are acquired by a monocular camera with different qualities (such as resolution and focal length) and setups (viewing distance, viewing angle, and optical environment). It is demonstrated that our ROI detection method is necessary and can largely remove the background noise and significantly increase the accuracy of our underwater object detection method. PMID:28771194

  10. 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

  11. Object detection and tracking system

    DOEpatents

    Ma, Tian J.

    2017-05-30

    Methods and apparatuses for analyzing a sequence of images for an object are disclosed herein. In a general embodiment, the method identifies a region of interest in the sequence of images. The object is likely to move within the region of interest. The method divides the region of interest in the sequence of images into sections and calculates signal-to-noise ratios for a section in the sections. A signal-to-noise ratio for the section is calculated using the section in the image, a prior section in a prior image to the image, and a subsequent section in a subsequent image to the image. The signal-to-noise ratios are for potential velocities of the object in the section. The method also selects a velocity from the potential velocities for the object in the section using a potential velocity in the potential velocities having a highest signal-to-noise ratio in the signal-to-noise ratios.

  12. 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.

  13. 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.

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. Detecting impossible changes in infancy: a three-system account

    PubMed Central

    Wang, Su-hua; Baillargeon, Renée

    2012-01-01

    Can infants detect that an object has magically disappeared, broken apart or changed color while briefly hidden? Recent research suggests that infants detect some but not other ‘impossible’ changes; and that various contextual manipulations can induce infants to detect changes they would not otherwise detect. We present an account that includes three systems: a physical-reasoning, an object-tracking, and an object-representation system. What impossible changes infants detect depends on what object information is included in the physical-reasoning system; this information becomes subject to a principle of persistence, which states that objects can undergo no spontaneous or uncaused change. What contextual manipulations induce infants to detect impossible changes depends on complex interplays between the physical-reasoning system and the object-tracking and object-representation systems. PMID:18078778

  2. 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.

  3. 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

  4. Salient object detection method based on multiple semantic features

    NASA Astrophysics Data System (ADS)

    Wang, Chunyang; Yu, Chunyan; Song, Meiping; Wang, Yulei

    2018-04-01

    The existing salient object detection model can only detect the approximate location of salient object, or highlight the background, to resolve the above problem, a salient object detection method was proposed based on image semantic features. First of all, three novel salient features were presented in this paper, including object edge density feature (EF), object semantic feature based on the convex hull (CF) and object lightness contrast feature (LF). Secondly, the multiple salient features were trained with random detection windows. Thirdly, Naive Bayesian model was used for combine these features for salient detection. The results on public datasets showed that our method performed well, the location of salient object can be fixed and the salient object can be accurately detected and marked by the specific window.

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. A-Track: Detecting Moving Objects in FITS images

    NASA Astrophysics Data System (ADS)

    Atay, T.; Kaplan, M.; Kilic, Y.; Karapinar, N.

    2017-04-01

    A-Track is a fast, open-source, cross-platform pipeline for detecting moving objects (asteroids and comets) in sequential telescope images in FITS format. The moving objects are detected using a modified line detection algorithm.

  10. Small target detection using objectness and saliency

    NASA Astrophysics Data System (ADS)

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

    2017-10-01

    We are motived by the need for generic object detection algorithm which achieves high recall for small targets in complex scenes with acceptable computational efficiency. We propose a novel object detection algorithm, which has high localization quality with acceptable computational cost. Firstly, we obtain the objectness map as in BING[1] and use NMS to get the top N points. Then, k-means algorithm is used to cluster them into K classes according to their location. We set the center points of the K classes as seed points. For each seed point, an object potential region is extracted. Finally, a fast salient object detection algorithm[2] is applied to the object potential regions to highlight objectlike pixels, and a series of efficient post-processing operations are proposed to locate the targets. Our method runs at 5 FPS on 1000*1000 images, and significantly outperforms previous methods on small targets in cluttered background.

  11. A Multi-object Exoplanet Detecting Technique

    NASA Astrophysics Data System (ADS)

    Zhang, K.

    2011-05-01

    Exoplanet exploration is not only a meaningful astronomical action, but also has a close relation with the extra-terrestrial life. High resolution echelle spectrograph is the key instrument for measuring stellar radial velocity (RV). But with higher precision, better environmental stability and higher cost are required. An improved technique of RV means invented by David J. Erskine in 1997, External Dispersed Interferometry (EDI), can increase the RV measuring precision by combining the moderate resolution spectrograph with a fixed-delay Michelson interferometer. LAMOST with large aperture and large field of view is equipped with 16 multi-object low resolution fiber spectrographs. And these spectrographs are capable to work in medium resolution mode (R=5{K}˜10{K}). LAMOST will be one of the most powerful exoplanet detecting systems over the world by introducing EDI technique. The EDI technique is a new technique for developing astronomical instrumentation in China. The operating theory of EDI was generally verified by a feasibility experiment done in 2009. And then a multi-object exoplanet survey system based on LAMOST spectrograph was proposed. According to this project, three important tasks have been done as follows: Firstly, a simulation of EDI operating theory contains the stellar spectrum model, interferometer transmission model, spectrograph mediation model and RV solution model. In order to meet the practical situation, two detecting modes, temporal and spatial phase-stepping methods, are separately simulated. The interference spectrum is analyzed with Fourier transform algorithm and a higher resolution conventional spectrum is resolved. Secondly, an EDI prototype is composed of a multi-object interferometer prototype and the LAMOST spectrograph. Some ideas are used in the design to reduce the effect of central obscuration, for example, modular structure and external/internal adjusting frames. Another feasibility experiment was done at Xinglong Station in

  12. Multi-object Detection and Discrimination Algorithms

    DTIC Science & Technology

    2015-03-26

    with  an   algorithm  similar  to  a  depth-­‐first   search .   This  stage  of  the   algorithm  is  O(CN).  From...Multi-object Detection and Discrimination Algorithms This document contains an overview of research and work performed and published at the University...of Florida from October 1, 2009 to October 31, 2013 pertaining to proposal 57306CS: Multi-object Detection and Discrimination Algorithms

  13. 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.

  14. Buried Object Detection

    DTIC Science & Technology

    1988-01-22

    Final Report 19 January 1987 Army Research OfficeM Contract No. DAAL03..87-K-0052 National Center for Physical Acoustics D T ! C " Naioal P. 0. Box 847...black . umberJ FIELO I GROUP I SU9GROU-p Acoustic , Seismic, Acoustic seismic coupling, porefluid, pulse echo, propagation, soils, sound speed...seismic transfer function. /’An acoustic scheme for buried object detection is thought to involve a sound source above the ground and a microphone as a

  15. Space Object Maneuver Detection Algorithms Using TLE Data

    NASA Astrophysics Data System (ADS)

    Pittelkau, M.

    2016-09-01

    An important aspect of Space Situational Awareness (SSA) is detection of deliberate and accidental orbit changes of space objects. Although space surveillance systems detect orbit maneuvers within their tracking algorithms, maneuver data are not readily disseminated for general use. However, two-line element (TLE) data is available and can be used to detect maneuvers of space objects. This work is an attempt to improve upon existing TLE-based maneuver detection algorithms. Three adaptive maneuver detection algorithms are developed and evaluated: The first is a fading-memory Kalman filter, which is equivalent to the sliding-window least-squares polynomial fit, but computationally more efficient and adaptive to the noise in the TLE data. The second algorithm is based on a sample cumulative distribution function (CDF) computed from a histogram of the magnitude-squared |V|2 of change-in-velocity vectors (V), which is computed from the TLE data. A maneuver detection threshold is computed from the median estimated from the CDF, or from the CDF and a specified probability of false alarm. The third algorithm is a median filter. The median filter is the simplest of a class of nonlinear filters called order statistics filters, which is within the theory of robust statistics. The output of the median filter is practically insensitive to outliers, or large maneuvers. The median of the |V|2 data is proportional to the variance of the V, so the variance is estimated from the output of the median filter. A maneuver is detected when the input data exceeds a constant times the estimated variance.

  16. Salient Object Detection via Structured Matrix Decomposition.

    PubMed

    Peng, Houwen; Li, Bing; Ling, Haibin; Hu, Weiming; Xiong, Weihua; Maybank, Stephen J

    2016-05-04

    Low-rank recovery models have shown potential for salient object detection, where a matrix is decomposed into a low-rank matrix representing image background and a sparse matrix identifying salient objects. Two deficiencies, however, still exist. First, previous work typically assumes the elements in the sparse matrix are mutually independent, ignoring the spatial and pattern relations of image regions. Second, when the low-rank and sparse matrices are relatively coherent, e.g., when there are similarities between the salient objects and background or when the background is complicated, it is difficult for previous models to disentangle them. To address these problems, we propose a novel structured matrix decomposition model with two structural regularizations: (1) a tree-structured sparsity-inducing regularization that captures the image structure and enforces patches from the same object to have similar saliency values, and (2) a Laplacian regularization that enlarges the gaps between salient objects and the background in feature space. Furthermore, high-level priors are integrated to guide the matrix decomposition and boost the detection. We evaluate our model for salient object detection on five challenging datasets including single object, multiple objects and complex scene images, and show competitive results as compared with 24 state-of-the-art methods in terms of seven performance metrics.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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

  2. Object detection from images obtained through underwater turbulence medium

    NASA Astrophysics Data System (ADS)

    Furhad, Md. Hasan; Tahtali, Murat; Lambert, Andrew

    2017-09-01

    Imaging through underwater experiences severe distortions due to random fluctuations of temperature and salinity in water, which produces underwater turbulence through diffraction limited blur. Lights reflecting from objects perturb and attenuate contrast, making the recognition of objects of interest difficult. Thus, the information available for detecting underwater objects of interest becomes a challenging task as they have inherent confusion among the background, foreground and other image properties. In this paper, a saliency-based approach is proposed to detect the objects acquired through an underwater turbulent medium. This approach has drawn attention among a wide range of computer vision applications, such as image retrieval, artificial intelligence, neuro-imaging and object detection. The image is first processed through a deblurring filter. Next, a saliency technique is used on the image for object detection. In this step, a saliency map that highlights the target regions is generated and then a graph-based model is proposed to extract these target regions for object detection.

  3. Sensor Tasking for Detection and Custody of HAMR Objects

    NASA Astrophysics Data System (ADS)

    Frueh, C.; Paul, S. M.; Fiedler, H.

    High area-to-mass ratio objects (HAMR) are objects that are highly perturbed especially by non-conservative forces such as drag and solar radiation pressure. As a consequence, they are population different orbital regions than low area-to-mass ratio objects. This makes the objects hard to detect. After initial detection those objects are often lost, because standard follow-up times of thirty periods are not sufficient for redetection. This paper applies a sensor tasking and follow-up strategy to the problem of detecting and keeping custody of HAMR objects.

  4. 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.

  5. 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.

  6. Research on Daily Objects Detection Based on Deep Neural Network

    NASA Astrophysics Data System (ADS)

    Ding, Sheng; Zhao, Kun

    2018-03-01

    With the rapid development of deep learning, great breakthroughs have been made in the field of object detection. In this article, the deep learning algorithm is applied to the detection of daily objects, and some progress has been made in this direction. Compared with traditional object detection methods, the daily objects detection method based on deep learning is faster and more accurate. The main research work of this article: 1. collect a small data set of daily objects; 2. in the TensorFlow framework to build different models of object detection, and use this data set training model; 3. the training process and effect of the model are improved by fine-tuning the model parameters.

  7. A survey on object detection in optical remote sensing images

    NASA Astrophysics Data System (ADS)

    Cheng, Gong; Han, Junwei

    2016-07-01

    Object detection in optical remote sensing images, being a fundamental but challenging problem in the field of aerial and satellite image analysis, plays an important role for a wide range of applications and is receiving significant attention in recent years. While enormous methods exist, a deep review of the literature concerning generic object detection is still lacking. This paper aims to provide a review of the recent progress in this field. Different from several previously published surveys that focus on a specific object class such as building and road, we concentrate on more generic object categories including, but are not limited to, road, building, tree, vehicle, ship, airport, urban-area. Covering about 270 publications we survey (1) template matching-based object detection methods, (2) knowledge-based object detection methods, (3) object-based image analysis (OBIA)-based object detection methods, (4) machine learning-based object detection methods, and (5) five publicly available datasets and three standard evaluation metrics. We also discuss the challenges of current studies and propose two promising research directions, namely deep learning-based feature representation and weakly supervised learning-based geospatial object detection. It is our hope that this survey will be beneficial for the researchers to have better understanding of this research field.

  8. 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

  9. 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.

  10. Amaro-autonomous real-time detection of moving maritime objects: introducing a flight experiment for an on-board ship detection system

    NASA Astrophysics Data System (ADS)

    Schwenk, Kurt; Willburger, Katharina; Pless, Sebastian

    2017-10-01

    Motivated by politics and economy, the monitoring of the world wide ship traffic is a field of high topicality. To detect illegal activities like piracy, illegal fishery, ocean dumping and refugee transportation is of great value. The analysis of satellite images on the ground delivers a great contribution to situation awareness. However, for many applications the up-to-dateness of the data is crucial. With ground based processing, the time between image acquisition and delivery of the data to the end user is in the range of several hours. The highest influence to the duration of ground based processing is the delay caused by the transmission of the large amount of image data from the satellite to the processing centre on the ground. One expensive solution to this issue is the usage of data relay satellites systems like EDRS. Another approach is to analyse the image data directly on-board of the satellite. Since the product data (e.g. ship position, heading, velocity, characteristics) is very small compared to the input image data, real-time connections provided by satellite telecommunication services like Iridium or Orbcomm can be used to send small packets of information directly to the end user without significant delay. The AMARO (Autonomous real-time detection of moving maritime objects) project at DLR is a feasibility study of an on-board ship detection system involving a real-time low bandwidth communication. The operation of a prototype on-board ship detection system will be demonstrated on an airborne platform. In this article, the scope, aim and design of a flight experiment for an on-board ship detection system scheduled for mid of 2018 is presented. First, the scope and the constraints of the experiment are explained in detail. The main goal is to demonstrate the operability of an automatic ship detection system on board of an airplane. For data acquisition the optical high resolution DLR MACS-MARE camera (VIS/NIR) is used. The system will be able to

  11. Tracks detection from high-orbit space objects

    NASA Astrophysics Data System (ADS)

    Shumilov, Yu. P.; Vygon, V. G.; Grishin, E. A.; Konoplev, A. O.; Semichev, O. P.; Shargorodskii, V. D.

    2017-05-01

    The paper presents studies results of a complex algorithm for the detection of highly orbital space objects. Before the implementation of the algorithm, a series of frames with weak tracks of space objects, which can be discrete, is recorded. The algorithm includes pre-processing, classical for astronomy, consistent filtering of each frame and its threshold processing, shear transformation, median filtering of the transformed series of frames, repeated threshold processing and detection decision making. Modeling of space objects weak tracks on of the night starry sky real frames obtained in the regime of a stationary telescope was carried out. It is shown that the permeability of an optoelectronic device has increased by almost 2m.

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. Research notes : detecting objects at railroad crossings.

    DOT National Transportation Integrated Search

    2004-04-01

    The highest risks are at intersections with roadways. An object may fall off of a truck or farm vehicle, or someone may drop something. The goal of this research was to evaluate promising technologies for the detection of such objects at railroad-roa...

  18. 75 FR 81708 - Notice of Decision To Issue Buy American Waivers for Foreign Object Debris (FOD) Detection Equipment

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-12-28

    ... Circular 150/5220-24, Airport Foreign Object Debris (FOD) detection equipment, detailing system... produce sufficient and reasonable amounts of stationary FOD detection systems; the FAA issued a notice in... manufacturing stationary FOD detection systems in the United States: Trex Aviation Systems and QinetiQ. Although...

  19. Object Detection in Natural Backgrounds Predicted by Discrimination Performance and Models

    NASA Technical Reports Server (NTRS)

    Ahumada, A. J., Jr.; Watson, A. B.; Rohaly, A. M.; Null, Cynthia H. (Technical Monitor)

    1995-01-01

    In object detection, an observer looks for an object class member in a set of backgrounds. In discrimination, an observer tries to distinguish two images. Discrimination models predict the probability that an observer detects a difference between two images. We compare object detection and image discrimination with the same stimuli by: (1) making stimulus pairs of the same background with and without the target object and (2) either giving many consecutive trials with the same background (discrimination) or intermixing the stimuli (object detection). Six images of a vehicle in a natural setting were altered to remove the vehicle and mixed with the original image in various proportions. Detection observers rated the images for vehicle presence. Discrimination observers rated the images for any difference from the background image. Estimated detectabilities of the vehicles were found by maximizing the likelihood of a Thurstone category scaling model. The pattern of estimated detectabilities is similar for discrimination and object detection, and is accurately predicted by a Cortex Transform discrimination model. Predictions of a Contrast- Sensitivity- Function filter model and a Root-Mean-Square difference metric based on the digital image values are less accurate. The discrimination detectabilities averaged about twice those of object detection.

  20. A biological hierarchical model based underwater moving object detection.

    PubMed

    Shen, Jie; Fan, Tanghuai; Tang, Min; Zhang, Qian; Sun, Zhen; Huang, Fengchen

    2014-01-01

    Underwater moving object detection is the key for many underwater computer vision tasks, such as object recognizing, locating, and tracking. Considering the super ability in visual sensing of the underwater habitats, the visual mechanism of aquatic animals is generally regarded as the cue for establishing bionic models which are more adaptive to the underwater environments. However, the low accuracy rate and the absence of the prior knowledge learning limit their adaptation in underwater applications. Aiming to solve the problems originated from the inhomogeneous lumination and the unstable background, the mechanism of the visual information sensing and processing pattern from the eye of frogs are imitated to produce a hierarchical background model for detecting underwater objects. Firstly, the image is segmented into several subblocks. The intensity information is extracted for establishing background model which could roughly identify the object and the background regions. The texture feature of each pixel in the rough object region is further analyzed to generate the object contour precisely. Experimental results demonstrate that the proposed method gives a better performance. Compared to the traditional Gaussian background model, the completeness of the object detection is 97.92% with only 0.94% of the background region that is included in the detection results.

  1. A Biological Hierarchical Model Based Underwater Moving Object Detection

    PubMed Central

    Shen, Jie; Fan, Tanghuai; Tang, Min; Zhang, Qian; Sun, Zhen; Huang, Fengchen

    2014-01-01

    Underwater moving object detection is the key for many underwater computer vision tasks, such as object recognizing, locating, and tracking. Considering the super ability in visual sensing of the underwater habitats, the visual mechanism of aquatic animals is generally regarded as the cue for establishing bionic models which are more adaptive to the underwater environments. However, the low accuracy rate and the absence of the prior knowledge learning limit their adaptation in underwater applications. Aiming to solve the problems originated from the inhomogeneous lumination and the unstable background, the mechanism of the visual information sensing and processing pattern from the eye of frogs are imitated to produce a hierarchical background model for detecting underwater objects. Firstly, the image is segmented into several subblocks. The intensity information is extracted for establishing background model which could roughly identify the object and the background regions. The texture feature of each pixel in the rough object region is further analyzed to generate the object contour precisely. Experimental results demonstrate that the proposed method gives a better performance. Compared to the traditional Gaussian background model, the completeness of the object detection is 97.92% with only 0.94% of the background region that is included in the detection results. PMID:25140194

  2. S-CNN: Subcategory-aware convolutional networks for object detection.

    PubMed

    Chen, Tao; Lu, Shijian; Fan, Jiayuan

    2017-09-26

    The marriage between the deep convolutional neural network (CNN) and region proposals has made breakthroughs for object detection in recent years. While the discriminative object features are learned via a deep CNN for classification, the large intra-class variation and deformation still limit the performance of the CNN based object detection. We propose a subcategory-aware CNN (S-CNN) to solve the object intra-class variation problem. In the proposed technique, the training samples are first grouped into multiple subcategories automatically through a novel instance sharing maximum margin clustering process. A multi-component Aggregated Channel Feature (ACF) detector is then trained to produce more latent training samples, where each ACF component corresponds to one clustered subcategory. The produced latent samples together with their subcategory labels are further fed into a CNN classifier to filter out false proposals for object detection. An iterative learning algorithm is designed for the joint optimization of image subcategorization, multi-component ACF detector, and subcategory-aware CNN classifier. Experiments on INRIA Person dataset, Pascal VOC 2007 dataset and MS COCO dataset show that the proposed technique clearly outperforms the state-of-the-art methods for generic object detection.

  3. 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...

  4. Color object detection using spatial-color joint probability functions.

    PubMed

    Luo, Jiebo; Crandall, David

    2006-06-01

    Object detection in unconstrained images is an important image understanding problem with many potential applications. There has been little success in creating a single algorithm that can detect arbitrary objects in unconstrained images; instead, algorithms typically must be customized for each specific object. Consequently, it typically requires a large number of exemplars (for rigid objects) or a large amount of human intuition (for nonrigid objects) to develop a robust algorithm. We present a robust algorithm designed to detect a class of compound color objects given a single model image. A compound color object is defined as having a set of multiple, particular colors arranged spatially in a particular way, including flags, logos, cartoon characters, people in uniforms, etc. Our approach is based on a particular type of spatial-color joint probability function called the color edge co-occurrence histogram. In addition, our algorithm employs perceptual color naming to handle color variation, and prescreening to limit the search scope (i.e., size and location) for the object. Experimental results demonstrated that the proposed algorithm is insensitive to object rotation, scaling, partial occlusion, and folding, outperforming a closely related algorithm based on color co-occurrence histograms by a decisive margin.

  5. Deep Spatial-Temporal Joint Feature Representation for Video Object Detection.

    PubMed

    Zhao, Baojun; Zhao, Boya; Tang, Linbo; Han, Yuqi; Wang, Wenzheng

    2018-03-04

    With the development of deep neural networks, many object detection frameworks have shown great success in the fields of smart surveillance, self-driving cars, and facial recognition. However, the data sources are usually videos, and the object detection frameworks are mostly established on still images and only use the spatial information, which means that the feature consistency cannot be ensured because the training procedure loses temporal information. To address these problems, we propose a single, fully-convolutional neural network-based object detection framework that involves temporal information by using Siamese networks. In the training procedure, first, the prediction network combines the multiscale feature map to handle objects of various sizes. Second, we introduce a correlation loss by using the Siamese network, which provides neighboring frame features. This correlation loss represents object co-occurrences across time to aid the consistent feature generation. Since the correlation loss should use the information of the track ID and detection label, our video object detection network has been evaluated on the large-scale ImageNet VID dataset where it achieves a 69.5% mean average precision (mAP).

  6. 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.

  7. The detection methods of dynamic objects

    NASA Astrophysics Data System (ADS)

    Knyazev, N. L.; Denisova, L. A.

    2018-01-01

    The article deals with the application of cluster analysis methods for solving the task of aircraft detection on the basis of distribution of navigation parameters selection into groups (clusters). The modified method of cluster analysis for search and detection of objects and then iterative combining in clusters with the subsequent count of their quantity for increase in accuracy of the aircraft detection have been suggested. The course of the method operation and the features of implementation have been considered. In the conclusion the noted efficiency of the offered method for exact cluster analysis for finding targets has been shown.

  8. 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

  9. 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…

  10. 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

  11. Acoustic facilitation of object movement detection during self-motion

    PubMed Central

    Calabro, F. J.; Soto-Faraco, S.; Vaina, L. M.

    2011-01-01

    In humans, as well as most animal species, perception of object motion is critical to successful interaction with the surrounding environment. Yet, as the observer also moves, the retinal projections of the various motion components add to each other and extracting accurate object motion becomes computationally challenging. Recent psychophysical studies have demonstrated that observers use a flow-parsing mechanism to estimate and subtract self-motion from the optic flow field. We investigated whether concurrent acoustic cues for motion can facilitate visual flow parsing, thereby enhancing the detection of moving objects during simulated self-motion. Participants identified an object (the target) that moved either forward or backward within a visual scene containing nine identical textured objects simulating forward observer translation. We found that spatially co-localized, directionally congruent, moving auditory stimuli enhanced object motion detection. Interestingly, subjects who performed poorly on the visual-only task benefited more from the addition of moving auditory stimuli. When auditory stimuli were not co-localized to the visual target, improvements in detection rates were weak. Taken together, these results suggest that parsing object motion from self-motion-induced optic flow can operate on multisensory object representations. PMID:21307050

  12. 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.

  13. Hard x-ray focusing optics for concealed object detection

    NASA Astrophysics Data System (ADS)

    Jannson, Tomasz; Gertsenshteyn, Michael

    2006-05-01

    In this paper, we discuss hard x-ray optics, in general, and lobster-eye focusing optics, in particular, for concealed object detection, at longer distances. The longer distance (~50m) scenario is important for Improvised Explosives Detection (IED), "seeing through walls," "seeing objects under ground," and related applications.

  14. 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

  15. Toward an Objective Enhanced-V Detection Algorithm

    NASA Technical Reports Server (NTRS)

    Brunner, Jason; Feltz, Wayne; Moses, John; Rabin, Robert; Ackerman, Steven

    2007-01-01

    The area of coldest cloud tops above thunderstorms sometimes has a distinct V or U shape. This pattern, often referred to as an "enhanced-V' signature, has been observed to occur during and preceding severe weather in previous studies. This study describes an algorithmic approach to objectively detect enhanced-V features with observations from the Geostationary Operational Environmental Satellite and Low Earth Orbit data. The methodology consists of cross correlation statistics of pixels and thresholds of enhanced-V quantitative parameters. The effectiveness of the enhanced-V detection method will be examined using Geostationary Operational Environmental Satellite, MODerate-resolution Imaging Spectroradiometer, and Advanced Very High Resolution Radiometer image data from case studies in the 2003-2006 seasons. The main goal of this study is to develop an objective enhanced-V detection algorithm for future implementation into operations with future sensors, such as GOES-R.

  16. 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.

  17. 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.

  18. 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

  19. Multi-Frame Convolutional Neural Networks for Object Detection in Temporal Data

    DTIC Science & Technology

    2017-03-01

    maximum 200 words) Given the problem of detecting objects in video , existing neural-network solutions rely on a post-processing step to combine...information across frames and strengthen conclusions. This technique has been successful for videos with simple, dominant objects but it cannot detect objects...Computer Science iii THIS PAGE INTENTIONALLY LEFT BLANK iv ABSTRACT Given the problem of detecting objects in video , existing neural-network solutions rely

  20. Object detection via eye tracking and fringe restraint

    NASA Astrophysics Data System (ADS)

    Pan, Fei; Zhang, Hanming; Zeng, Ying; Tong, Li; Yan, Bin

    2017-07-01

    Object detection is a computer vision problem which caught a large amount of attention. But the candidate boundingboxes extracted from only image features may end up with false-detection due to the semantic gap between the top-down and the bottom up information. In this paper, we propose a novel method for generating object bounding-boxes proposals using the combination of eye fixation point, saliency detection and edges. The new method obtains a fixation orientated Gaussian map, optimizes the map through single-layer cellular automata, and derives bounding-boxes from the optimized map on three levels. Then we score the boxes by combining all the information above, and choose the box with the highest score to be the final box. We perform an evaluation of our method by comparing with previous state-ofthe art approaches on the challenging POET datasets, the images of which are chosen from PASCAL VOC 2012. Our method outperforms them on small scale objects while comparable to them in general.

  1. 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

  2. Image Discrimination Models Predict Object Detection in Natural Backgrounds

    NASA Technical Reports Server (NTRS)

    Ahumada, Albert J., Jr.; Rohaly, A. M.; Watson, Andrew B.; Null, Cynthia H. (Technical Monitor)

    1994-01-01

    Object detection involves looking for one of a large set of object sub-images in a large set of background images. Image discrimination models only predict the probability that an observer will detect a difference between two images. In a recent study based on only six different images, we found that discrimination models can predict the relative detectability of objects in those images, suggesting that these simpler models may be useful in some object detection applications. Here we replicate this result using a new, larger set of images. Fifteen images of a vehicle in an other-wise natural setting were altered to remove the vehicle and mixed with the original image in a proportion chosen to make the target neither perfectly recognizable nor unrecognizable. The target was also rotated about a vertical axis through its center and mixed with the background. Sixteen observers rated these 30 target images and the 15 background-only images for the presence of a vehicle. The likelihoods of the observer responses were computed from a Thurstone scaling model with the assumption that the detectabilities are proportional to the predictions of an image discrimination model. Three image discrimination models were used: a cortex transform model, a single channel model with a contrast sensitivity function filter, and the Root-Mean-Square (RMS) difference of the digital target and background-only images. As in the previous study, the cortex transform model performed best; the RMS difference predictor was second best; and last, but still a reasonable predictor, was the single channel model. Image discrimination models can predict the relative detectabilities of objects in natural backgrounds.

  3. A Space Object Detection Algorithm using Fourier Domain Likelihood Ratio Test

    NASA Astrophysics Data System (ADS)

    Becker, D.; Cain, S.

    Space object detection is of great importance in the highly dependent yet competitive and congested space domain. Detection algorithms employed play a crucial role in fulfilling the detection component in the situational awareness mission to detect, track, characterize and catalog unknown space objects. Many current space detection algorithms use a matched filter or a spatial correlator to make a detection decision at a single pixel point of a spatial image based on the assumption that the data follows a Gaussian distribution. This paper explores the potential for detection performance advantages when operating in the Fourier domain of long exposure images of small and/or dim space objects from ground based telescopes. A binary hypothesis test is developed based on the joint probability distribution function of the image under the hypothesis that an object is present and under the hypothesis that the image only contains background noise. The detection algorithm tests each pixel point of the Fourier transformed images to make the determination if an object is present based on the criteria threshold found in the likelihood ratio test. Using simulated data, the performance of the Fourier domain detection algorithm is compared to the current algorithm used in space situational awareness applications to evaluate its value.

  4. Multi-Objective Community Detection Based on Memetic Algorithm

    PubMed Central

    2015-01-01

    Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels. PMID:25932646

  5. Multi-objective community detection based on memetic algorithm.

    PubMed

    Wu, Peng; Pan, Li

    2015-01-01

    Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels.

  6. Method for detecting a mass density image of an object

    DOEpatents

    Wernick, Miles N [Chicago, IL; Yang, Yongyi [Westmont, IL

    2008-12-23

    A method for detecting a mass density image of an object. An x-ray beam is transmitted through the object and a transmitted beam is emitted from the object. The transmitted beam is directed at an angle of incidence upon a crystal analyzer. A diffracted beam is emitted from the crystal analyzer onto a detector and digitized. A first image of the object is detected from the diffracted beam emitted from the crystal analyzer when positioned at a first angular position. A second image of the object is detected from the diffracted beam emitted from the crystal analyzer when positioned at a second angular position. A refraction image is obtained and a regularized mathematical inversion algorithm is applied to the refraction image to obtain a mass density image.

  7. 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.

  8. 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.

  9. The detection of 'virtual' objects using echoes by humans: Spectral cues.

    PubMed

    Rowan, Daniel; Papadopoulos, Timos; Archer, Lauren; Goodhew, Amanda; Cozens, Hayley; Lopez, Ricardo Guzman; Edwards, David; Holmes, Hannah; Allen, Robert

    2017-07-01

    Some blind people use echoes to detect discrete, silent objects to support their spatial orientation/navigation, independence, safety and wellbeing. The acoustical features that people use for this are not well understood. Listening to changes in spectral shape due to the presence of an object could be important for object detection and avoidance, especially at short range, although it is currently not known whether it is possible with echolocation-related sounds. Bands of noise were convolved with recordings of binaural impulse responses of objects in an anechoic chamber to create 'virtual objects', which were analysed and played to sighted and blind listeners inexperienced in echolocation. The sounds were also manipulated to remove cues unrelated to spectral shape. Most listeners could accurately detect hard flat objects using changes in spectral shape. The useful spectral changes for object detection occurred above approximately 3 kHz, as with object localisation. However, energy in the sounds below 3 kHz was required to exploit changes in spectral shape for object detection, whereas energy below 3 kHz impaired object localisation. Further recordings showed that the spectral changes were diminished by room reverberation. While good high-frequency hearing is generally important for echolocation, the optimal echo-generating stimulus will probably depend on the task. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  10. 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

  11. Object Detection Techniques Applied on Mobile Robot Semantic Navigation

    PubMed Central

    Astua, Carlos; Barber, Ramon; Crespo, Jonathan; Jardon, Alberto

    2014-01-01

    The future of robotics predicts that robots will integrate themselves more every day with human beings and their environments. To achieve this integration, robots need to acquire information about the environment and its objects. There is a big need for algorithms to provide robots with these sort of skills, from the location where objects are needed to accomplish a task up to where these objects are considered as information about the environment. This paper presents a way to provide mobile robots with the ability-skill to detect objets for semantic navigation. This paper aims to use current trends in robotics and at the same time, that can be exported to other platforms. Two methods to detect objects are proposed, contour detection and a descriptor based technique, and both of them are combined to overcome their respective limitations. Finally, the code is tested on a real robot, to prove its accuracy and efficiency. PMID:24732101

  12. Detecting objects in radiographs for homeland security

    NASA Astrophysics Data System (ADS)

    Prasad, Lakshman; Snyder, Hans

    2005-05-01

    We present a general scheme for segmenting a radiographic image into polygons that correspond to visual features. This decomposition provides a vectorized representation that is a high-level description of the image. The polygons correspond to objects or object parts present in the image. This characterization of radiographs allows the direct application of several shape recognition algorithms to identify objects. In this paper we describe the use of constrained Delaunay triangulations as a uniform foundational tool to achieve multiple visual tasks, namely image segmentation, shape decomposition, and parts-based shape matching. Shape decomposition yields parts that serve as tokens representing local shape characteristics. Parts-based shape matching enables the recognition of objects in the presence of occlusions, which commonly occur in radiographs. The polygonal representation of image features affords the efficient design and application of sophisticated geometric filtering methods to detect large-scale structural properties of objects in images. Finally, the representation of radiographs via polygons results in significant reduction of image file sizes and permits the scalable graphical representation of images, along with annotations of detected objects, in the SVG (scalable vector graphics) format that is proposed by the world wide web consortium (W3C). This is a textual representation that can be compressed and encrypted for efficient and secure transmission of information over wireless channels and on the Internet. In particular, our methods described here provide an algorithmic framework for developing image analysis tools for screening cargo at ports of entry for homeland security.

  13. DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection.

    PubMed

    Ouyang, Wanli; Zeng, Xingyu; Wang, Xiaogang; Qiu, Shi; Luo, Ping; Tian, Yonglong; Li, Hongsheng; Yang, Shuo; Wang, Zhe; Li, Hongyang; Loy, Chen Change; Wang, Kun; Yan, Junjie; Tang, Xiaoou

    2016-07-07

    In this paper, we propose deformable deep convolutional neural networks for generic object detection. This new deep learning object detection framework has innovations in multiple aspects. In the proposed new deep architecture, a new deformation constrained pooling (def-pooling) layer models the deformation of object parts with geometric constraint and penalty. A new pre-training strategy is proposed to learn feature representations more suitable for the object detection task and with good generalization capability. By changing the net structures, training strategies, adding and removing some key components in the detection pipeline, a set of models with large diversity are obtained, which significantly improves the effectiveness of model averaging. The proposed approach improves the mean averaged precision obtained by RCNN [16], which was the state-of-the-art, from 31% to 50.3% on the ILSVRC2014 detection test set. It also outperforms the winner of ILSVRC2014, GoogLeNet, by 6.1%. Detailed component-wise analysis is also provided through extensive experimental evaluation, which provides a global view for people to understand the deep learning object detection pipeline.

  14. 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.

  15. Object locating system

    DOEpatents

    Novak, J.L.; Petterson, B.

    1998-06-09

    A sensing system locates an object by sensing the object`s effect on electric fields. The object`s effect on the mutual capacitance of electrode pairs varies according to the distance between the object and the electrodes. A single electrode pair can sense the distance from the object to the electrodes. Multiple electrode pairs can more precisely locate the object in one or more dimensions. 12 figs.

  16. Feature-fused SSD: fast detection for small objects

    NASA Astrophysics Data System (ADS)

    Cao, Guimei; Xie, Xuemei; Yang, Wenzhe; Liao, Quan; Shi, Guangming; Wu, Jinjian

    2018-04-01

    Small objects detection is a challenging task in computer vision due to its limited resolution and information. In order to solve this problem, the majority of existing methods sacrifice speed for improvement in accuracy. In this paper, we aim to detect small objects at a fast speed, using the best object detector Single Shot Multibox Detector (SSD) with respect to accuracy-vs-speed trade-off as base architecture. We propose a multi-level feature fusion method for introducing contextual information in SSD, in order to improve the accuracy for small objects. In detailed fusion operation, we design two feature fusion modules, concatenation module and element-sum module, different in the way of adding contextual information. Experimental results show that these two fusion modules obtain higher mAP on PASCAL VOC2007 than baseline SSD by 1.6 and 1.7 points respectively, especially with 2-3 points improvement on some small objects categories. The testing speed of them is 43 and 40 FPS respectively, superior to the state of the art Deconvolutional single shot detector (DSSD) by 29.4 and 26.4 FPS.

  17. A New Moving Object Detection Method Based on Frame-difference and Background Subtraction

    NASA Astrophysics Data System (ADS)

    Guo, Jiajia; Wang, Junping; Bai, Ruixue; Zhang, Yao; Li, Yong

    2017-09-01

    Although many methods of moving object detection have been proposed, moving object extraction is still the core in video surveillance. However, with the complex scene in real world, false detection, missed detection and deficiencies resulting from cavities inside the body still exist. In order to solve the problem of incomplete detection for moving objects, a new moving object detection method combined an improved frame-difference and Gaussian mixture background subtraction is proposed in this paper. To make the moving object detection more complete and accurate, the image repair and morphological processing techniques which are spatial compensations are applied in the proposed method. Experimental results show that our method can effectively eliminate ghosts and noise and fill the cavities of the moving object. Compared to other four moving object detection methods which are GMM, VIBE, frame-difference and a literature's method, the proposed method improve the efficiency and accuracy of the detection.

  18. Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

    DOEpatents

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

    2015-07-28

    An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using a combinatorial algorithm.

  19. Finding Kuiper Belt Objects Below the Detection Limit

    NASA Astrophysics Data System (ADS)

    Whidden, Peter; Kalmbach, Bryce; Bektesevic, Dino; Connolly, Andrew; Jones, Lynne; Smotherman, Hayden; Becker, Andrew

    2018-01-01

    We demonstrate a novel approach for uncovering the signatures of moving objects (e.g. Kuiper Belt Objects) below the detection thresholds of single astronomical images. To do so, we will employ a matched filter moving at specific rates of proposed orbits through a time-domain dataset. This is analogous to the better-known "shift-and-stack" method; however it uses neither direct shifting nor stacking of the image pixels. Instead of resampling the raw pixels to create an image stack, we will instead integrate the object detection probabilities across multiple single-epoch images to accrue support for a proposed orbit. The filtering kernel provides a measure of the probability that an object is present along a given orbit, and enables the user to make principled decisions about when the search has been successful, and when it may be terminated. The results we present here utilize GPUs to speed up the search by two orders of magnitudes over CPU implementations.

  20. 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.

  1. 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%.

  2. Object locating system

    DOEpatents

    Novak, James L.; Petterson, Ben

    1998-06-09

    A sensing system locates an object by sensing the object's effect on electric fields. The object's effect on the mutual capacitance of electrode pairs varies according to the distance between the object and the electrodes. A single electrode pair can sense the distance from the object to the electrodes. Multiple electrode pairs can more precisely locate the object in one or more dimensions.

  3. Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

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

    Paiton, Dylan M.; Kenyon, Garrett T.; Brumby, Steven P.

    An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using amore » combinatorial algorithm.« less

  4. Object detection and imaging with acoustic time reversal mirrors

    NASA Astrophysics Data System (ADS)

    Fink, Mathias

    1993-11-01

    Focusing an acoustic wave on an object of unknown shape through an inhomogeneous medium of any geometrical shape is a challenge in underground detection. Optimal detection and imaging of objects needs the development of such focusing techniques. The use of a time reversal mirror (TRM) represents an original solution to this problem. It realizes in real time a focusing process matched to the object shape, to the geometries of the acoustic interfaces and to the geometries of the mirror. It is a self adaptative technique which compensates for any geometrical distortions of the mirror structure as well as for diffraction and refraction effects through the interfaces. Two real time 64 and 128 channel prototypes have been built in our laboratory and TRM experiments demonstrating the TRM performance through inhomogeneous solid and liquid media are presented. Applications to medical therapy (kidney stone detection and destruction) and to nondestructive testing of metallurgical samples of different geometries are described. Extension of this study to underground detection and imaging will be discussed.

  5. 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.

  6. Probabilistic resident space object detection using archival THEMIS fluxgate magnetometer data

    NASA Astrophysics Data System (ADS)

    Brew, Julian; Holzinger, Marcus J.

    2018-05-01

    Recent progress in the detection of small space objects, at geosynchronous altitudes, through ground-based optical and radar measurements is demonstrated as a viable method. However, in general, these methods are limited to detection of objects greater than 10 cm. This paper examines the use of magnetometers to detect plausible flyby encounters with charged space objects using a matched filter signal existence binary hypothesis test approach. Relevant data-set processing and reduction of archival fluxgate magnetometer data from the NASA THEMIS mission is discussed in detail. Using the proposed methodology and a false alarm rate of 10%, 285 plausible detections with probability of detection greater than 80% are claimed and several are reviewed in detail.

  7. Wireless sensor networks for heritage object deformation detection and tracking algorithm.

    PubMed

    Xie, Zhijun; Huang, Guangyan; Zarei, Roozbeh; He, Jing; Zhang, Yanchun; Ye, Hongwu

    2014-10-31

    Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT). In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection.

  8. Wireless Sensor Networks for Heritage Object Deformation Detection and Tracking Algorithm

    PubMed Central

    Xie, Zhijun; Huang, Guangyan; Zarei, Roozbeh; He, Jing; Zhang, Yanchun; Ye, Hongwu

    2014-01-01

    Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT). In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection. PMID:25365458

  9. Salient object detection based on multi-scale contrast.

    PubMed

    Wang, Hai; Dai, Lei; Cai, Yingfeng; Sun, Xiaoqiang; Chen, Long

    2018-05-01

    Due to the development of deep learning networks, a salient object detection based on deep learning networks, which are used to extract the features, has made a great breakthrough compared to the traditional methods. At present, the salient object detection mainly relies on very deep convolutional network, which is used to extract the features. In deep learning networks, an dramatic increase of network depth may cause more training errors instead. In this paper, we use the residual network to increase network depth and to mitigate the errors caused by depth increase simultaneously. Inspired by image simplification, we use color and texture features to obtain simplified image with multiple scales by means of region assimilation on the basis of super-pixels in order to reduce the complexity of images and to improve the accuracy of salient target detection. We refine the feature on pixel level by the multi-scale feature correction method to avoid the feature error when the image is simplified at the above-mentioned region level. The final full connection layer not only integrates features of multi-scale and multi-level but also works as classifier of salient targets. The experimental results show that proposed model achieves better results than other salient object detection models based on original deep learning networks. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. Moving object detection and tracking in videos through turbulent medium

    NASA Astrophysics Data System (ADS)

    Halder, Kalyan Kumar; Tahtali, Murat; Anavatti, Sreenatha G.

    2016-06-01

    This paper addresses the problem of identifying and tracking moving objects in a video sequence having a time-varying background. This is a fundamental task in many computer vision applications, though a very challenging one because of turbulence that causes blurring and spatiotemporal movements of the background images. Our proposed approach involves two major steps. First, a moving object detection algorithm that deals with the detection of real motions by separating the turbulence-induced motions using a two-level thresholding technique is used. In the second step, a feature-based generalized regression neural network is applied to track the detected objects throughout the frames in the video sequence. The proposed approach uses the centroid and area features of the moving objects and creates the reference regions instantly by selecting the objects within a circle. Simulation experiments are carried out on several turbulence-degraded video sequences and comparisons with an earlier method confirms that the proposed approach provides a more effective tracking of the targets.

  11. A Study of Dim Object Detection for the Space Surveillance Telescope

    DTIC Science & Technology

    2013-03-21

    ENG-13-M-32 Abstract Current methods of dim object detection for space surveillance make use of a Gaussian log-likelihood-ratio-test-based...quantitatively comparing the efficacy of two methods for dim object detection , termed in this paper the point detector and the correlator, both of which rely... applications . It is used in national defense for detecting satellites. It is used to detecting space debris, which threatens both civilian and

  12. Object detection in natural scenes: Independent effects of spatial and category-based attention.

    PubMed

    Stein, Timo; Peelen, Marius V

    2017-04-01

    Humans are remarkably efficient in detecting highly familiar object categories in natural scenes, with evidence suggesting that such object detection can be performed in the (near) absence of attention. Here we systematically explored the influences of both spatial attention and category-based attention on the accuracy of object detection in natural scenes. Manipulating both types of attention additionally allowed for addressing how these factors interact: whether the requirement for spatial attention depends on the extent to which observers are prepared to detect a specific object category-that is, on category-based attention. The results showed that the detection of targets from one category (animals or vehicles) was better than the detection of targets from two categories (animals and vehicles), demonstrating the beneficial effect of category-based attention. This effect did not depend on the semantic congruency of the target object and the background scene, indicating that observers attended to visual features diagnostic of the foreground target objects from the cued category. Importantly, in three experiments the detection of objects in scenes presented in the periphery was significantly impaired when observers simultaneously performed an attentionally demanding task at fixation, showing that spatial attention affects natural scene perception. In all experiments, the effects of category-based attention and spatial attention on object detection performance were additive rather than interactive. Finally, neither spatial nor category-based attention influenced metacognitive ability for object detection performance. These findings demonstrate that efficient object detection in natural scenes is independently facilitated by spatial and category-based attention.

  13. Moving object detection using dynamic motion modelling from UAV aerial images.

    PubMed

    Saif, A F M Saifuddin; Prabuwono, Anton Satria; Mahayuddin, Zainal Rasyid

    2014-01-01

    Motion analysis based moving object detection from UAV aerial image is still an unsolved issue due to inconsideration of proper motion estimation. Existing moving object detection approaches from UAV aerial images did not deal with motion based pixel intensity measurement to detect moving object robustly. Besides current research on moving object detection from UAV aerial images mostly depends on either frame difference or segmentation approach separately. There are two main purposes for this research: firstly to develop a new motion model called DMM (dynamic motion model) and secondly to apply the proposed segmentation approach SUED (segmentation using edge based dilation) using frame difference embedded together with DMM model. The proposed DMM model provides effective search windows based on the highest pixel intensity to segment only specific area for moving object rather than searching the whole area of the frame using SUED. At each stage of the proposed scheme, experimental fusion of the DMM and SUED produces extracted moving objects faithfully. Experimental result reveals that the proposed DMM and SUED have successfully demonstrated the validity of the proposed methodology.

  14. Interaction between hippocampal serotonin and cannabinoid systems in reactivity to spatial and object novelty detection.

    PubMed

    Nasehi, Mohammad; Rostam-Nezhad, Elnaz; Ebrahimi-Ghiri, Mohaddeseh; Zarrindast, Mohammad-Reza

    2017-01-15

    Functional interaction between cannabinoid and serotonin neuronal systems have been reported in different tasks related to memory assessment. The present study investigated the effect of serotonin 5-HT4 agents into the dorsal hippocampus (the CA1 region) on spatial and object novelty detection deficits induced by activation of cannabinoid CB1 receptors (CB1Rs) using arachidonylcyclopropylamide (ACPA) in a non-associative behavioral task designed to forecast the ability of rodents to encode spatial and non-spatial relationships between distinct stimuli. Post-training, intra-CA1 microinjection of 5-HT4 receptor agonist RS67333 or 5-HT4 receptor antagonist RS23597 both at the dose of 0.016μg/mouse impaired spatial memory, while cannabinoid CB1R antagonist AM251 (0.1μg/mouse) facilitated object novelty memory. Also, post-training, intraperitoneal administration of CB1R agonist ACPA (0.005-0.05mg/kg) impaired both memories. However, a subthreshold dose of RS67333 restored ACPA response on both memories. Moreover, a subthreshold dose of RS23597 potentiated ACPA (0.01mg/kg) and reversed ACPA (0.05mg/kg) responses on spatial memory, while it potentiated ACPA response at the dose of 0.005 or 0.05mg/kg on object novelty memory. Furthermore, effective dose of AM251 restored ACPA response at the higher dose. AM251 blocked response induced by combination of RS67333 or RS23597 and the higher dose of ACPA on both memories. Our results highlight that hippocampal 5-HT4 receptors differently affect cannabinoid signaling in spatial and object novelty memories. The inactivation of CB1 receptors blocks the effect of 5-HT4 agents into the CA1 region on memory deficits induced by activation of CB1Rs via ACPA. Copyright © 2016. Published by Elsevier B.V.

  15. Faint Object Detection in Multi-Epoch Observations via Catalog Data Fusion

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

    Budavári, Tamás; Szalay, Alexander S.; Loredo, Thomas J.

    Astronomy in the time-domain era faces several new challenges. One of them is the efficient use of observations obtained at multiple epochs. The work presented here addresses faint object detection and describes an incremental strategy for separating real objects from artifacts in ongoing surveys. The idea is to produce low-threshold single-epoch catalogs and to accumulate information across epochs. This is in contrast to more conventional strategies based on co-added or stacked images. We adopt a Bayesian approach, addressing object detection by calculating the marginal likelihoods for hypotheses asserting that there is no object or one object in a small imagemore » patch containing at most one cataloged source at each epoch. The object-present hypothesis interprets the sources in a patch at different epochs as arising from a genuine object; the no-object hypothesis interprets candidate sources as spurious, arising from noise peaks. We study the detection probability for constant-flux objects in a Gaussian noise setting, comparing results based on single and stacked exposures to results based on a series of single-epoch catalog summaries. Our procedure amounts to generalized cross-matching: it is the product of a factor accounting for the matching of the estimated fluxes of the candidate sources and a factor accounting for the matching of their estimated directions. We find that probabilistic fusion of multi-epoch catalogs can detect sources with similar sensitivity and selectivity compared to stacking. The probabilistic cross-matching framework underlying our approach plays an important role in maintaining detection sensitivity and points toward generalizations that could accommodate variability and complex object structure.« less

  16. Faint Object Detection in Multi-Epoch Observations via Catalog Data Fusion

    NASA Astrophysics Data System (ADS)

    Budavári, Tamás; Szalay, Alexander S.; Loredo, Thomas J.

    2017-03-01

    Astronomy in the time-domain era faces several new challenges. One of them is the efficient use of observations obtained at multiple epochs. The work presented here addresses faint object detection and describes an incremental strategy for separating real objects from artifacts in ongoing surveys. The idea is to produce low-threshold single-epoch catalogs and to accumulate information across epochs. This is in contrast to more conventional strategies based on co-added or stacked images. We adopt a Bayesian approach, addressing object detection by calculating the marginal likelihoods for hypotheses asserting that there is no object or one object in a small image patch containing at most one cataloged source at each epoch. The object-present hypothesis interprets the sources in a patch at different epochs as arising from a genuine object; the no-object hypothesis interprets candidate sources as spurious, arising from noise peaks. We study the detection probability for constant-flux objects in a Gaussian noise setting, comparing results based on single and stacked exposures to results based on a series of single-epoch catalog summaries. Our procedure amounts to generalized cross-matching: it is the product of a factor accounting for the matching of the estimated fluxes of the candidate sources and a factor accounting for the matching of their estimated directions. We find that probabilistic fusion of multi-epoch catalogs can detect sources with similar sensitivity and selectivity compared to stacking. The probabilistic cross-matching framework underlying our approach plays an important role in maintaining detection sensitivity and points toward generalizations that could accommodate variability and complex object structure.

  17. 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 ...

  18. 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

  19. 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.

  20. Astrometry of Solar System Objects with Gaia

    NASA Astrophysics Data System (ADS)

    Hestroffer, Daniel J.; Arenou, Frederic; Desmars, Josselin; Robert, Vincent; Thuillot, William; Arlot, Jean-Eudes; Carry, Benoit; David, Pedro; Eggl, Siegfried; Fabricius, Claus; Kudryashova, Maria; Lainey, Valery; Spoto, Federica; Tanga, Paolo; Gaia DPAC

    2016-10-01

    The Gaia ESA space mission will provide astrometric observations of a large number of celestial bodies, with unprecedented accuracy, and in an homogenous reference frame (to become the optical ICRF). The Gaia satellite is monitoring regularly the whole celestial sphere, with one complete scan in about 6month, down to approximately magnitude V≤20.7. It will provide after its nominal lifetime, (5 years, 2014-2019) about 70 astrometric points for several hundred thousands of solar system objects, asteroids from the Near-Earth region to Centaurs and bright TNOs, as well as planetary satellites and comets. The highly precise astrometric and photometric data is bound to lead to huge advances in the science of small Small Solar System Bodies (e.g. Tanga et al. 2016 P\\&SS, Hestroffer et al. 2014 COSPAR #40 ; Mignard et al. 2007 EMP).The first Gaia data release (GDR#1) is foreseen for Q3-2016 and will provide highly precise positions of selected stars down to mag V≈20. While solar system objets data is foreseen for the next data release (in 2017), science of Solar System will also highly benefit from the Gaia stellar catalogue. We will present the status of the satellite and Gaia mission, and details on the stellar data that will be published in this GDR#1. We discuss the catalogue content, number of stars, parameters and precisions, and the process of cross-matching and validation. We also touch upon the construction of combined Tycho-Gaia TGAS catalogue.A Gaia data daily processing is devoted to the identification of Solar System Objects. During this process the detection of new (or critical) objects arises and leads to the triggering of scientific alerts to be found on the web gaiafunsso.imcce.fr. We have also set up an international follow-up network called Gaia-FUN-SSO to validate the detection in space. For this goal, in case of detection the observational data must be sent to the MPC by the observers. Besides, Gaia should benefit for the classical astrometric

  1. On the Detectability of Interstellar Objects Like 1I/'Oumuamua

    NASA Astrophysics Data System (ADS)

    Ragozzine, Darin

    2018-04-01

    Almost since Oort's 1950 hypothesis of a tenuously bound cloud of comets, planetary formation theorists have realized that the process of planet formation must have ejected very large numbers of planetesimals into interstellar space. Unforunately, these objects are distributed over galactic volumes, while they are only likely to be detectable if they pass within a few AU of Earth, resulting in an incredibly sparse detectable population. Furthermore, hypotheses for the formation and distribution of these bodies allows for uncertainties of orders of magnitude in the expected detection rate: our analysis suggested LSST would discover 0.01-100 objects during its lifetime (Cook et al. 2016). The discovery of 1I/'Oumuamua by a survey less powerful that LSST indicates either a low probability event and/or that properties of this population are on the more favorable end of the spectrum. We revisit the detailed detection analysis of Cook et al. 2016 in light of the detection of 1I/'Oumuamua. We use these results to better understand 1I/'Oumuamua and to update our assessment of future detections of interstellar objects. We highlight some key questions that can be answered only by additional discoveries.

  2. Detect2Rank: Combining Object Detectors Using Learning to Rank.

    PubMed

    Karaoglu, Sezer; Yang Liu; Gevers, Theo

    2016-01-01

    Object detection is an important research area in the field of computer vision. Many detection algorithms have been proposed. However, each object detector relies on specific assumptions of the object appearance and imaging conditions. As a consequence, no algorithm can be considered universal. With the large variety of object detectors, the subsequent question is how to select and combine them. In this paper, we propose a framework to learn how to combine object detectors. The proposed method uses (single) detectors like Deformable Part Models, Color Names and Ensemble of Exemplar-SVMs, and exploits their correlation by high-level contextual features to yield a combined detection list. Experiments on the PASCAL VOC07 and VOC10 data sets show that the proposed method significantly outperforms single object detectors, DPM (8.4%), CN (6.8%) and EES (17.0%) on VOC07 and DPM (6.5%), CN (5.5%) and EES (16.2%) on VOC10. We show with an experiment that there are no constraints on the type of the detector. The proposed method outperforms (2.4%) the state-of-the-art object detector (RCNN) on VOC07 when Regions with Convolutional Neural Network is combined with other detectors used in this paper.

  3. 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

  4. 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.

  5. Object memory and change detection: dissociation as a function of visual and conceptual similarity.

    PubMed

    Yeh, Yei-Yu; Yang, Cheng-Ta

    2008-01-01

    People often fail to detect a change between two visual scenes, a phenomenon referred to as change blindness. This study investigates how a post-change object's similarity to the pre-change object influences memory of the pre-change object and affects change detection. The results of Experiment 1 showed that similarity lowered detection sensitivity but did not affect the speed of identifying the pre-change object, suggesting that similarity between the pre- and post-change objects does not degrade the pre-change representation. Identification speed for the pre-change object was faster than naming the new object regardless of detection accuracy. Similarity also decreased detection sensitivity in Experiment 2 but improved the recognition of the pre-change object under both correct detection and detection failure. The similarity effect on recognition was greatly reduced when 20% of each pre-change stimulus was masked by random dots in Experiment 3. Together the results suggest that the level of pre-change representation under detection failure is equivalent to the level under correct detection and that the pre-change representation is almost complete. Similarity lowers detection sensitivity but improves explicit access in recognition. Dissociation arises between recognition and change detection as the two judgments rely on the match-to-mismatch signal and mismatch-to-match signal, respectively.

  6. Expanded opportunities of THz passive camera for the detection of concealed objects

    NASA Astrophysics Data System (ADS)

    Trofimov, Vyacheslav A.; Trofimov, Vladislav V.; Kuchik, Igor E.

    2013-10-01

    Among the security problems, the detection of object implanted into either the human body or animal body is the urgent problem. At the present time the main tool for the detection of such object is X-raying only. However, X-ray is the ionized radiation and therefore can not be used often. Other way for the problem solving is passive THz imaging using. In our opinion, using of the passive THz camera may help to detect the object implanted into the human body under certain conditions. The physical reason of such possibility arises from temperature trace on the human skin as a result of the difference in temperature between object and parts of human body. Modern passive THz cameras have not enough resolution in temperature to see this difference. That is why, we use computer processing to enhance the passive THz camera resolution for this application. After computer processing of images captured by passive THz camera TS4, developed by ThruVision Systems Ltd., we may see the pronounced temperature trace on the human body skin from the water, which is drunk by person, or other food eaten by person. Nevertheless, there are many difficulties on the way of full soution of this problem. We illustrate also an improvement of quality of the image captured by comercially available passive THz cameras using computer processing. In some cases, one can fully supress a noise on the image without loss of its quality. Using computer processing of the THz image of objects concealed on the human body, one may improve it many times. Consequently, the instrumental resolution of such device may be increased without any additional engineering efforts.

  7. Water Detection Based on Object Reflections

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.; Matthies, Larry H.

    2012-01-01

    Water bodies are challenging terrain hazards for terrestrial unmanned ground vehicles (UGVs) for several reasons. Traversing through deep water bodies could cause costly damage to the electronics of UGVs. Additionally, a UGV that is either broken down due to water damage or becomes stuck in a water body during an autonomous operation will require rescue, potentially drawing critical resources away from the primary operation and increasing the operation cost. Thus, robust water detection is a critical perception requirement for UGV autonomous navigation. One of the properties useful for detecting still water bodies is that their surface acts as a horizontal mirror at high incidence angles. Still water bodies in wide-open areas can be detected by geometrically locating the exact pixels in the sky that are reflecting on candidate water pixels on the ground, predicting if ground pixels are water based on color similarity to the sky and local terrain features. But in cluttered areas where reflections of objects in the background dominate the appearance of the surface of still water bodies, detection based on sky reflections is of marginal value. Specifically, this software attempts to solve the problem of detecting still water bodies on cross-country terrain in cluttered areas at low cost.

  8. 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.

  9. Multi-object detection and tracking technology based on hexagonal opto-electronic detector

    NASA Astrophysics Data System (ADS)

    Song, Yong; Hao, Qun; Li, Xiang

    2008-02-01

    A novel multi-object detection and tracking technology based on hexagonal opto-electronic detector is proposed, in which (1) a new hexagonal detector, which is composed of 6 linear CCDs, has been firstly developed to achieve the field of view of 360 degree, (2) to achieve the detection and tracking of multi-object with high speed, the object recognition criterions of Object Signal Width Criterion (OSWC) and Horizontal Scale Ratio Criterion (HSRC) are proposed. In this paper, Simulated Experiments have been carried out to verify the validity of the proposed technology, which show that the detection and tracking of multi-object can be achieved with high speed by using the proposed hexagonal detector and the criterions of OSWC and HSRC, indicating that the technology offers significant advantages in Photo-electric Detection, Computer Vision, Virtual Reality, Augment Reality, etc.

  10. Real-time object detection and semantic segmentation for autonomous driving

    NASA Astrophysics Data System (ADS)

    Li, Baojun; Liu, Shun; Xu, Weichao; Qiu, Wei

    2018-02-01

    In this paper, we proposed a Highly Coupled Network (HCNet) for joint objection detection and semantic segmentation. It follows that our method is faster and performs better than the previous approaches whose decoder networks of different tasks are independent. Besides, we present multi-scale loss architecture to learn better representation for different scale objects, but without extra time in the inference phase. Experiment results show that our method achieves state-of-the-art results on the KITTI datasets. Moreover, it can run at 35 FPS on a GPU and thus is a practical solution to object detection and semantic segmentation for autonomous driving.

  11. 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

  12. 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.

  13. Fast object detection algorithm based on HOG and CNN

    NASA Astrophysics Data System (ADS)

    Lu, Tongwei; Wang, Dandan; Zhang, Yanduo

    2018-04-01

    In the field of computer vision, object classification and object detection are widely used in many fields. The traditional object detection have two main problems:one is that sliding window of the regional selection strategy is high time complexity and have window redundancy. And the other one is that Robustness of the feature is not well. In order to solve those problems, Regional Proposal Network (RPN) is used to select candidate regions instead of selective search algorithm. Compared with traditional algorithms and selective search algorithms, RPN has higher efficiency and accuracy. We combine HOG feature and convolution neural network (CNN) to extract features. And we use SVM to classify. For TorontoNet, our algorithm's mAP is 1.6 percentage points higher. For OxfordNet, our algorithm's mAP is 1.3 percentage higher.

  14. Shadow detection of moving objects based on multisource information in Internet of things

    NASA Astrophysics Data System (ADS)

    Ma, Zhen; Zhang, De-gan; Chen, Jie; Hou, Yue-xian

    2017-05-01

    Moving object detection is an important part in intelligent video surveillance under the banner of Internet of things. The detection of moving target's shadow is also an important step in moving object detection. On the accuracy of shadow detection will affect the detection results of the object directly. Based on the variety of shadow detection method, we find that only using one feature can't make the result of detection accurately. Then we present a new method for shadow detection which contains colour information, the invariance of optical and texture feature. Through the comprehensive analysis of the detecting results of three kinds of information, the shadow was effectively determined. It gets ideal effect in the experiment when combining advantages of various methods.

  15. The relationship between change detection and recognition of centrally attended objects in motion pictures.

    PubMed

    Angelone, Bonnie L; Levin, Daniel T; Simons, Daniel J

    2003-01-01

    Observers typically detect changes to central objects more readily than changes to marginal objects, but they sometimes miss changes to central, attended objects as well. However, even if observers do not report such changes, they may be able to recognize the changed object. In three experiments we explored change detection and recognition memory for several types of changes to central objects in motion pictures. Observers who failed to detect a change still performed at above chance levels on a recognition task in almost all conditions. In addition, observers who detected the change were no more accurate in their recognition than those who did not detect the change. Despite large differences in the detectability of changes across conditions, those observers who missed the change did not vary in their ability to recognize the changing object.

  16. Effect of chewing speed on the detection of a foreign object in food.

    PubMed

    Paphangkorakit, J; Ladsena, V; Rukyuttithamkul, T; Khamtad, T

    2016-03-01

    Accidentally biting hard on a piece of hard foreign object in food is among the causes of tooth fracturing and could be associated with oral sensibility. This study has investigated the effect of chewing speed on the ability to detect a foreign object in food in human. Fourteen healthy subjects were asked to randomly chew one of 10 cooked rice balls, five of which containing a foreign object made from a tiny uncooked rice grain, until they detected the rice grain. Each subject chewed the test foods both at 50 (slow) and 100 (fast) chews min(-1). The accuracy of detection and the number of chews before detection (CBD) were recorded and compared between the two chewing speeds using paired t-tests. The results showed that almost all subjects detected the foreign object by biting. The accuracy of detection was more than 90% and not significantly different between slow and fast chewing but the mean CBD in slow chewing (11·7 ± 1·3 chews) was significantly different from that in fast chewing (20·7 ± 1·9 chews; P < 0·001). The study showed that slow chewers required less number of chews before a foreign object in food could be detected and was, presumably, more effective in detecting the object compared to fast chewers. If each chew bears equal probability of teeth encountering the foreign object, slow chewing might also reduce the chance of accidentally biting hard on the foreign object and fracturing the tooth. © 2015 John Wiley & Sons Ltd.

  17. 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.

  18. The detection of earth orbiting objects by IRAS

    NASA Technical Reports Server (NTRS)

    Dow, Kimberly L.; Sykes, Mark V.; Low, Frank J.; Vilas, Faith

    1990-01-01

    A systematic examination of 1836 images of the sky constructed from scans made by the Infrared Astronomical Satellite has resulted in the detection of 466 objects which are shown to be in earth orbit. Analysis of the spatial and size distribution and thermal properties of these objets, which may include payloads, rocket bodies and debris particles, is being conducted as one step in a feasibility study for space-based debris detection technologies.

  19. Toward an Objective Enhanced-V Detection Algorithm

    NASA Technical Reports Server (NTRS)

    Moses, John F.; Brunner,Jason C.; Feltz, Wayne F.; Ackerman, Steven A.; Moses, John F.; Rabin, Robert M.

    2007-01-01

    The area of coldest cloud tops above thunderstorms sometimes has a distinct V or U shape. This pattern, often referred to as an "enhanced-V signature, has been observed to occur during and preceding severe weather. This study describes an algorithmic approach to objectively detect overshooting tops, temperature couplets, and enhanced-V features with observations from the Geostationary Operational Environmental Satellite and Low Earth Orbit data. The methodology consists of temperature, temperature difference, and distance thresholds for the overshooting top and temperature couplet detection parts of the algorithm and consists of cross correlation statistics of pixels for the enhanced-V detection part of the algorithm. The effectiveness of the overshooting top and temperature couplet detection components of the algorithm is examined using GOES and MODIS image data for case studies in the 2003-2006 seasons. The main goal is for the algorithm to be useful for operations with future sensors, such as GOES-R.

  20. 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.

  1. 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.

  2. 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

  3. A man-made object detection for underwater TV

    NASA Astrophysics Data System (ADS)

    Cheng, Binbin; Wang, Wenwu; Chen, Yao

    2018-03-01

    It is a great challenging task to complete an automatic search of objects underwater. Usually the forward looking sonar is used to find the target, and then the initial identification of the target is completed by the side-scan sonar, and finally the confirmation of the target is accomplished by underwater TV. This paper presents an efficient method for automatic extraction of man-made sensitive targets in underwater TV. Firstly, the image of underwater TV is simplified with taking full advantage of the prior knowledge of the target and the background; then template matching technology is used for target detection; finally the target is confirmed by extracting parallel lines on the target contour. The algorithm is formulated for real-time execution on limited-memory commercial-of-the-shelf platforms and is capable of detection objects in underwater TV.

  4. The fate of object memory traces under change detection and change blindness.

    PubMed

    Busch, Niko A

    2013-07-03

    Observers often fail to detect substantial changes in a visual scene. This so-called change blindness is often taken as evidence that visual representations are sparse and volatile. This notion rests on the assumption that the failure to detect a change implies that representations of the changing objects are lost all together. However, recent evidence suggests that under change blindness, object memory representations may be formed and stored, but not retrieved. This study investigated the fate of object memory representations when changes go unnoticed. Participants were presented with scenes consisting of real world objects, one of which changed on each trial, while recording event-related potentials (ERPs). Participants were first asked to localize where the change had occurred. In an additional recognition task, participants then discriminated old objects, either from the pre-change or the post-change scene, from entirely new objects. Neural traces of object memories were studied by comparing ERPs for old and novel objects. Participants performed poorly in the detection task and often failed to recognize objects from the scene, especially pre-change objects. However, a robust old/novel effect was observed in the ERP, even when participants were change blind and did not recognize the old object. This implicit memory trace was found both for pre-change and post-change objects. These findings suggest that object memories are stored even under change blindness. Thus, visual representations may not be as sparse and volatile as previously thought. Rather, change blindness may point to a failure to retrieve and use these representations for change detection. Copyright © 2013 Elsevier B.V. All rights reserved.

  5. Deep Learning for Real-Time Capable Object Detection and Localization on Mobile Platforms

    NASA Astrophysics Data System (ADS)

    Particke, F.; Kolbenschlag, R.; Hiller, M.; Patiño-Studencki, L.; Thielecke, J.

    2017-10-01

    Industry 4.0 is one of the most formative terms in current times. Subject of research are particularly smart and autonomous mobile platforms, which enormously lighten the workload and optimize production processes. In order to interact with humans, the platforms need an in-depth knowledge of the environment. Hence, it is required to detect a variety of static and non-static objects. Goal of this paper is to propose an accurate and real-time capable object detection and localization approach for the use on mobile platforms. A method is introduced to use the powerful detection capabilities of a neural network for the localization of objects. Therefore, detection information of a neural network is combined with depth information from a RGB-D camera, which is mounted on a mobile platform. As detection network, YOLO Version 2 (YOLOv2) is used on a mobile robot. In order to find the detected object in the depth image, the bounding boxes, predicted by YOLOv2, are mapped to the corresponding regions in the depth image. This provides a powerful and extremely fast approach for establishing a real-time-capable Object Locator. In the evaluation part, the localization approach turns out to be very accurate. Nevertheless, it is dependent on the detected object itself and some additional parameters, which are analysed in this paper.

  6. 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.

  7. 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.

  8. Object-based landslide detection in different geographic regions

    NASA Astrophysics Data System (ADS)

    Friedl, Barbara; Hölbling, Daniel; Eisank, Clemens; Blaschke, Thomas

    2015-04-01

    Landslides occur in almost all mountainous regions of the world and rank among the most severe natural hazards. In the last decade - according to the world disaster report 2014 published by the International Federation of Red Cross and Red Crescent Societies (IRFC) - more than 9.000 people were killed by mass movements, more than 3.2 million people were affected and the total amount of disaster estimated damage accounts to more than 1.700 million US dollars. The application of remote sensing data for mapping landslides can contribute to post-disaster reconstruction or hazard mitigation, either by providing rapid information about the spatial distribution and location of landslides in the aftermath of triggering events or by creating and updating landslide inventories. This is especially valid for remote and inaccessible areas, where information on landslides is often lacking. However, reliable methods are needed for extracting timely and relevant information about landslides from remote sensing data. In recent years, novel methods such as object-based image analysis (OBIA) have been successfully employed for semi-automated landslide mapping. Several studies revealed that OBIA frequently outperforms pixel-based approaches, as a range of image object properties (spectral, spatial, morphometric, contextual) can be exploited during the analysis. However, object-based methods are often tailored to specific study areas, and thus, the transferability to regions with different geological settings, is often limited. The present case study evaluates the transferability and applicability of an OBIA approach for landslide detection in two distinct regions, i.e. the island of Taiwan and Austria. In Taiwan, sub-areas in the Baichi catchment in the North and in the Huaguoshan catchment in the southern-central part of the island are selected; in Austria, landslide-affected sites in the Upper Salzach catchment in the federal state of Salzburg are investigated. For both regions

  9. Understanding of Object Detection Based on CNN Family and YOLO

    NASA Astrophysics Data System (ADS)

    Du, Juan

    2018-04-01

    As a key use of image processing, object detection has boomed along with the unprecedented advancement of Convolutional Neural Network (CNN) and its variants since 2012. When CNN series develops to Faster Region with CNN (R-CNN), the Mean Average Precision (mAP) has reached 76.4, whereas, the Frame Per Second (FPS) of Faster R-CNN remains 5 to 18 which is far slower than the real-time effect. Thus, the most urgent requirement of object detection improvement is to accelerate the speed. Based on the general introduction to the background and the core solution CNN, this paper exhibits one of the best CNN representatives You Only Look Once (YOLO), which breaks through the CNN family’s tradition and innovates a complete new way of solving the object detection with most simple and high efficient way. Its fastest speed has achieved the exciting unparalleled result with FPS 155, and its mAP can also reach up to 78.6, both of which have surpassed the performance of Faster R-CNN greatly. Additionally, compared with the latest most advanced solution, YOLOv2 achieves an excellent tradeoff between speed and accuracy as well as an object detector with strong generalization ability to represent the whole image.

  10. Infrared system for monitoring movement of objects

    DOEpatents

    Valentine, K.H.; Falter, D.D.; Falter, K.G.

    1991-04-30

    A system is described for monitoring moving objects, such as the flight of honeybees and other insects, using a pulsed laser light source. This system has a self-powered micro-miniaturized transmitting unit powered, in the preferred embodiment, with an array of solar cells. This transmitting unit is attached to the object to be monitored. These solar cells provide current to a storage energy capacitor to produce, for example, five volts for the operation of the transmitter. In the simplest embodiment, the voltage on the capacitor operates a pulse generator to provide a pulsed energizing signal to one or more very small laser diodes. The pulsed light is then received at a receiving base station using substantially standard means which converts the light to an electrical signal for processing in a microprocessor to create the information as to the movement of the object. In the case of a unit for monitoring honeybees and other insects, the transmitting unit weighs less than 50 mg, and has a size no larger than 1[times]3[times]5 millimeters. Also, the preferred embodiment provides for the coding of the light to uniquely identify the particular transmitting unit that is being monitored. A wake-up' circuit is provided in the preferred embodiment whereby there is no transmission until the voltage on the capacitor has exceeded a pre-set threshold. Various other uses of the motion-detection system are described. 4 figures.

  11. Infrared system for monitoring movement of objects

    DOEpatents

    Valentine, Kenneth H.; Falter, Diedre D.; Falter, Kelly G.

    1991-01-01

    A system for monitoring moving objects, such as the flight of honeybees and other insects, using a pulsed laser light source. This system has a self-powered micro-miniaturized transmitting unit powered, in the preferred embodiment, with an array solar cells. This transmitting unit is attached to the object to be monitored. These solar cells provide current to a storage energy capacitor to produce, for example, five volts for the operation of the transmitter. In the simplest embodiment, the voltage on the capacitor operates a pulse generator to provide a pulsed energizing signal to one or more very small laser diodes. The pulsed light is then received at a receiving base station using substantially standard means which converts the light to an electrical signal for processing in a microprocessor to create the information as to the movement of the object. In the case of a unit for monitoring honeybees and other insects, the transmitting unit weighs less than 50 mg, and has a size no larger than 1.times.3.times.5 millimeters. Also, the preferred embodiment provides for the coding of the light to uniquely identify the particular transmitting unit that is being monitored. A "wake-up" circuit is provided in the preferred embodiment whereby there is no transmission until the voltage on the capacitor has exceeded a pre-set threshold. Various other uses of the motion-detection system are described.

  12. 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.

  13. [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.

  14. Cognitive object recognition system (CORS)

    NASA Astrophysics Data System (ADS)

    Raju, Chaitanya; Varadarajan, Karthik Mahesh; Krishnamurthi, Niyant; Xu, Shuli; Biederman, Irving; Kelley, Troy

    2010-04-01

    We have developed a framework, Cognitive Object Recognition System (CORS), inspired by current neurocomputational models and psychophysical research in which multiple recognition algorithms (shape based geometric primitives, 'geons,' and non-geometric feature-based algorithms) are integrated to provide a comprehensive solution to object recognition and landmarking. Objects are defined as a combination of geons, corresponding to their simple parts, and the relations among the parts. However, those objects that are not easily decomposable into geons, such as bushes and trees, are recognized by CORS using "feature-based" algorithms. The unique interaction between these algorithms is a novel approach that combines the effectiveness of both algorithms and takes us closer to a generalized approach to object recognition. CORS allows recognition of objects through a larger range of poses using geometric primitives and performs well under heavy occlusion - about 35% of object surface is sufficient. Furthermore, geon composition of an object allows image understanding and reasoning even with novel objects. With reliable landmarking capability, the system improves vision-based robot navigation in GPS-denied environments. Feasibility of the CORS system was demonstrated with real stereo images captured from a Pioneer robot. The system can currently identify doors, door handles, staircases, trashcans and other relevant landmarks in the indoor environment.

  15. Enhanced Detection of Sea-Disposed Man-Made Objects in Backscatter Data

    NASA Astrophysics Data System (ADS)

    Edwards, M.; Davis, R. B.

    2016-12-01

    The Hawai'i Undersea Military Munitions Assessment (HUMMA) project developed software to increase data visualization capabilities applicable to seafloor reflectivity datasets acquired by a variety of bottom-mapping sonar systems. The purpose of these improvements is to detect different intensity values within an arbitrary amplitude range that may be associated with relative target reflectivity as well as extend the overall amplitude range across which detailed dynamic contrast may be effectively displayed. The backscatter dataset used to develop this software imaged tens of thousands of reflective targets resting on the seabed that were systematically sea disposed south of Oahu, Hawaii, around the end of World War II in waters ranging from 300-600 meters depth. Human-occupied and remotely operated vehicles conducted ground-truth video and photographic reconnaissance of thousands of these reflective targets, documenting and geo-referencing long curvilinear trials of items including munitions, paint cans, airplane parts, scuttled ships, cars and bundled anti-submarine nets. Edwards et al. [2012] determined that most individual trails consist of objects of one particular type. The software described in this presentation, in combination with the ground-truth images, was developed to help recognize different types of objects based on reflectivity, size, and shape from altitudes of tens of meters above the seabed. The fundamental goal of the software is to facilitate rapid underway detection and geo-location of specific sea-disposed objects so their impact on the environment can be assessed.

  16. Detection of Objects Hidden in Highly Scattering Media Using Time-Gated Imaging Methods

    NASA Technical Reports Server (NTRS)

    Galland, Pierre A.; Wang, L.; Liang, X.; Ho, P. P.; Alfano, R. R.

    2000-01-01

    Non-intrusive and non-invasive optical imaging techniques has generated great interest among researchers for their potential applications to biological study, device characterization, surface defect detection, and jet fuel dynamics. Non-linear optical parametric amplification gate (NLOPG) has been used to detect back-scattered images of objects hidden in diluted Intralipid solutions. To directly detect objects hidden in highly scattering media, the diffusive component of light needs to be sorted out from early arrived ballistic and snake photons. In an optical imaging system, images are collected in transmission or back-scattered geometry. The early arrival photons in the transmission approach, always carry the direct information of the hidden object embedded in the turbid medium. In the back-scattered approach, the result is not so forth coming. In the presence of a scattering host, the first arrival photons in back-scattered approach will be directly photons from the host material. In the presentation, NLOPG was applied to acquire time resolved back-scattered images under the phase matching condition. A time-gated amplified signal was obtained through this NLOPG process. The system's gain was approximately 100 times. The time-gate was achieved through phase matching condition where only coherent photons retain their phase. As a result, the diffusive photons, which were the primary contributor to the background, were removed. With a large dynamic range and high resolution, time-gated early light imaging has the potential for improving rocket/aircraft design by determining jets shape and particle sizes. Refinements to these techniques may enable drop size measurements in the highly scattering, optically dense region of multi-element rocket injectors. These types of measurements should greatly enhance the design of stable, and higher performing rocket engines.

  17. 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.

  18. The effects of changes in object location on object identity detection: A simultaneous EEG-fMRI study.

    PubMed

    Yang, Ping; Fan, Chenggui; Wang, Min; Fogelson, Noa; Li, Ling

    2017-08-15

    Object identity and location are bound together to form a unique integration that is maintained and processed in visual working memory (VWM). Changes in task-irrelevant object location have been shown to impair the retrieval of memorial representations and the detection of object identity changes. However, the neural correlates of this cognitive process remain largely unknown. In the present study, we aim to investigate the underlying brain activation during object color change detection and the modulatory effects of changes in object location and VWM load. To this end we used simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings, which can reveal the neural activity with both high temporal and high spatial resolution. Subjects responded faster and with greater accuracy in the repeated compared to the changed object location condition, when a higher VWM load was utilized. These results support the spatial congruency advantage theory and suggest that it is more pronounced with higher VWM load. Furthermore, the spatial congruency effect was associated with larger posterior N1 activity, greater activation of the right inferior frontal gyrus (IFG) and less suppression of the right supramarginal gyrus (SMG), when object location was repeated compared to when it was changed. The ERP-fMRI integrative analysis demonstrated that the object location discrimination-related N1 component is generated in the right SMG. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Aerial surveillance based on hierarchical object classification for ground target detection

    NASA Astrophysics Data System (ADS)

    Vázquez-Cervantes, Alberto; García-Huerta, Juan-Manuel; Hernández-Díaz, Teresa; Soto-Cajiga, J. A.; Jiménez-Hernández, Hugo

    2015-03-01

    Unmanned aerial vehicles have turned important in surveillance application due to the flexibility and ability to inspect and displace in different regions of interest. The instrumentation and autonomy of these vehicles have been increased; i.e. the camera sensor is now integrated. Mounted cameras allow flexibility to monitor several regions of interest, displacing and changing the camera view. A well common task performed by this kind of vehicles correspond to object localization and tracking. This work presents a hierarchical novel algorithm to detect and locate objects. The algorithm is based on a detection-by-example approach; this is, the target evidence is provided at the beginning of the vehicle's route. Afterwards, the vehicle inspects the scenario, detecting all similar objects through UTM-GPS coordinate references. Detection process consists on a sampling information process of the target object. Sampling process encode in a hierarchical tree with different sampling's densities. Coding space correspond to a huge binary space dimension. Properties such as independence and associative operators are defined in this space to construct a relation between the target object and a set of selected features. Different densities of sampling are used to discriminate from general to particular features that correspond to the target. The hierarchy is used as a way to adapt the complexity of the algorithm due to optimized battery duty cycle of the aerial device. Finally, this approach is tested in several outdoors scenarios, proving that the hierarchical algorithm works efficiently under several conditions.

  20. Identification and detection of simple 3D objects with severely blurred vision.

    PubMed

    Kallie, Christopher S; Legge, Gordon E; Yu, Deyue

    2012-12-05

    Detecting and recognizing three-dimensional (3D) objects is an important component of the visual accessibility of public spaces for people with impaired vision. The present study investigated the impact of environmental factors and object properties on the recognition of objects by subjects who viewed physical objects with severely reduced acuity. The experiment was conducted in an indoor testing space. We examined detection and identification of simple convex objects by normally sighted subjects wearing diffusing goggles that reduced effective acuity to 20/900. We used psychophysical methods to examine the effect on performance of important environmental variables: viewing distance (from 10-24 feet, or 3.05-7.32 m) and illumination (overhead fluorescent and artificial window), and object variables: shape (boxes and cylinders), size (heights from 2-6 feet, or 0.61-1.83 m), and color (gray and white). Object identification was significantly affected by distance, color, height, and shape, as well as interactions between illumination, color, and shape. A stepwise regression analysis showed that 64% of the variability in identification could be explained by object contrast values (58%) and object visual angle (6%). When acuity is severely limited, illumination, distance, color, height, and shape influence the identification and detection of simple 3D objects. These effects can be explained in large part by the impact of these variables on object contrast and visual angle. Basic design principles for improving object visibility are discussed.

  1. Optical vibration detection spectral analysis assembly and method for detecting vibration in an object of interest

    DOEpatents

    Hale, Thomas C.; Telschow, Kenneth L.

    1998-01-01

    A vibration detection assembly is described which includes an emitter of light which has object and reference beams, the object beam reflected off of a vibrating object of interest; and a photorefractive substance having a given response time and which passes the reflected object beam and the reference beam, the reference beam and the object beam interfering within the photorefractive substance to create a space charge field which develops within the response time of the photorefractive substance.

  2. Optical vibration detection spectral analysis assembly and method for detecting vibration in an object of interest

    DOEpatents

    Hale, T.C.; Telschow, K.L.

    1998-10-27

    A vibration detection assembly is described which includes an emitter of light which has object and reference beams, the object beam reflected off of a vibrating object of interest; and a photorefractive substance having a given response time and which passes the reflected object beam and the reference beam, the reference beam and the object beam interfering within the photorefractive substance to create a space charge field which develops within the response time of the photorefractive substance. 6 figs.

  3. Object detectability at increased ambient lighting conditions.

    PubMed

    Pollard, Benjamin J; Chawla, Amarpreet S; Delong, David M; Hashimoto, Noriyuki; Samei, Ehsan

    2008-06-01

    Under typical dark conditions encountered in diagnostic reading rooms, a reader's pupils will contract and dilate as the visual focus intermittently shifts between the high luminance display and the darker background wall, resulting in increased visual fatigue and the degradation of diagnostic performance. A controlled increase of ambient lighting may, however, reduce the severity of these pupillary adjustments by minimizing the difference between the luminance level to which the eyes adapt while viewing an image (L(adp)) and the luminance level of diffusely reflected light from the area surrounding the display (L(s)). Although ambient lighting in reading rooms has conventionally been kept at a minimum to maintain the perceived contrast of film images, proper Digital Imaging and Communications in Medicine (DICOM) calibration of modern medical-grade liquid crystal displays can compensate for minor lighting increases with very little loss of image contrast. This paper describes two psychophysical studies developed to evaluate and refine optimum reading room ambient lighting conditions through the use of observational tasks intended to simulate real clinical practices. The first study utilized the biologic contrast response of the human visual system to determine a range of representative L(adp) values for typical medical images. Readers identified low contrast horizontal objects in circular foregrounds of uniform luminance (5, 12, 20, and 30 cd/m2) embedded within digitized mammograms. The second study examined the effect of increased ambient lighting on the detection of subtle objects embedded in circular foregrounds of uniform luminance (5, 12, and 35 cd/m2) centered within a constant background of 12 cd/m2 luminance. The images were displayed under a dark room condition (1 lux) and an increased ambient lighting level (50 lux) such that the luminance level of the diffusely reflected light from the background wall was approximately equal to the image L(adp) value of

  4. Method for detecting an image of an object

    DOEpatents

    Chapman, Leroy Dean; Thomlinson, William C.; Zhong, Zhong

    1999-11-16

    A method for detecting an absorption, refraction and scatter image of an object by independently analyzing, detecting, digitizing, and combining images acquired on a high and a low angle side of a rocking curve of a crystal analyzer. An x-ray beam which is generated by any suitable conventional apparatus can be irradiated upon either a Bragg type crystal analyzer or a Laue type crystal analyzer. Images of the absorption, refraction and scattering effects are detected, such as on an image plate, and then digitized. The digitized images are simultaneously solved, preferably on a pixel-by-pixel basis, to derive a combined visual image which has dramatically improved contrast and spatial resolution over an image acquired through conventional radiology methods.

  5. 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.

  6. A New 3D Object Pose Detection Method Using LIDAR Shape Set

    PubMed Central

    Kim, Jung-Un

    2018-01-01

    In object detection systems for autonomous driving, LIDAR sensors provide very useful information. However, problems occur because the object representation is greatly distorted by changes in distance. To solve this problem, we propose a LIDAR shape set that reconstructs the shape surrounding the object more clearly by using the LIDAR point information projected on the object. The LIDAR shape set restores object shape edges from a bird’s eye view by filtering LIDAR points projected on a 2D pixel-based front view. In this study, we use this shape set for two purposes. The first is to supplement the shape set with a LIDAR Feature map, and the second is to divide the entire shape set according to the gradient of the depth and density to create a 2D and 3D bounding box proposal for each object. We present a multimodal fusion framework that classifies objects and restores the 3D pose of each object using enhanced feature maps and shape-based proposals. The network structure consists of a VGG -based object classifier that receives multiple inputs and a LIDAR-based Region Proposal Networks (RPN) that identifies object poses. It works in a very intuitive and efficient manner and can be extended to other classes other than vehicles. Our research has outperformed object classification accuracy (Average Precision, AP) and 3D pose restoration accuracy (3D bounding box recall rate) based on the latest studies conducted with KITTI data sets. PMID:29547551

  7. A New 3D Object Pose Detection Method Using LIDAR Shape Set.

    PubMed

    Kim, Jung-Un; Kang, Hang-Bong

    2018-03-16

    In object detection systems for autonomous driving, LIDAR sensors provide very useful information. However, problems occur because the object representation is greatly distorted by changes in distance. To solve this problem, we propose a LIDAR shape set that reconstructs the shape surrounding the object more clearly by using the LIDAR point information projected on the object. The LIDAR shape set restores object shape edges from a bird's eye view by filtering LIDAR points projected on a 2D pixel-based front view. In this study, we use this shape set for two purposes. The first is to supplement the shape set with a LIDAR Feature map, and the second is to divide the entire shape set according to the gradient of the depth and density to create a 2D and 3D bounding box proposal for each object. We present a multimodal fusion framework that classifies objects and restores the 3D pose of each object using enhanced feature maps and shape-based proposals. The network structure consists of a VGG -based object classifier that receives multiple inputs and a LIDAR-based Region Proposal Networks (RPN) that identifies object poses. It works in a very intuitive and efficient manner and can be extended to other classes other than vehicles. Our research has outperformed object classification accuracy (Average Precision, AP) and 3D pose restoration accuracy (3D bounding box recall rate) based on the latest studies conducted with KITTI data sets.

  8. 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

  9. Object-Oriented Query Language For Events Detection From Images Sequences

    NASA Astrophysics Data System (ADS)

    Ganea, Ion Eugen

    2015-09-01

    In this paper is presented a method to represent the events extracted from images sequences and the query language used for events detection. Using an object oriented model the spatial and temporal relationships between salient objects and also between events are stored and queried. This works aims to unify the storing and querying phases for video events processing. The object oriented language syntax used for events processing allow the instantiation of the indexes classes in order to improve the accuracy of the query results. The experiments were performed on images sequences provided from sport domain and it shows the reliability and the robustness of the proposed language. To extend the language will be added a specific syntax for constructing the templates for abnormal events and for detection of the incidents as the final goal of the research.

  10. 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.

  11. Shape detection of Gaborized outline versions of everyday objects

    PubMed Central

    Sassi, Michaël; Machilsen, Bart; Wagemans, Johan

    2012-01-01

    We previously tested the identifiability of six versions of Gaborized outlines of everyday objects, differing in the orientations assigned to elements inside and outside the outline. We found significant differences in identifiability between the versions, and related a number of stimulus metrics to identifiability [Sassi, M., Vancleef, K., Machilsen, B., Panis, S., & Wagemans, J. (2010). Identification of everyday objects on the basis of Gaborized outline versions. i-Perception, 1(3), 121–142]. In this study, after retesting the identifiability of new variants of three of the stimulus versions, we tested their robustness to local orientation jitter in a detection experiment. In general, our results replicated the key findings from the previous study, and allowed us to substantiate our earlier interpretations of the effects of our stimulus metrics and of the performance differences between the different stimulus versions. The results of the detection task revealed a different ranking order of stimulus versions than the identification task. By examining the parallels and differences between the effects of our stimulus metrics in the two tasks, we found evidence for a trade-off between shape detectability and identifiability. The generally simple and smooth shapes that yield the strongest contour integration and most robust detectability tend to lack the distinguishing features necessary for clear-cut identification. Conversely, contours that do contain such identifying features tend to be inherently more complex and, therefore, yield weaker integration and less robust detectability. PMID:23483752

  12. 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.

  13. Applying the Multiple Signal Classification Method to Silent Object Detection Using Ambient Noise

    NASA Astrophysics Data System (ADS)

    Mori, Kazuyoshi; Yokoyama, Tomoki; Hasegawa, Akio; Matsuda, Minoru

    2004-05-01

    The revolutionary concept of using ocean ambient noise positively to detect objects, called acoustic daylight imaging, has attracted much attention. The authors attempted the detection of a silent target object using ambient noise and a wide-band beam former consisting of an array of receivers. In experimental results obtained in air, using the wide-band beam former, we successfully applied the delay-sum array (DSA) method to detect a silent target object in an acoustic noise field generated by a large number of transducers. This paper reports some experimental results obtained by applying the multiple signal classification (MUSIC) method to a wide-band beam former to detect silent targets. The ocean ambient noise was simulated by transducers decentralized to many points in air. Both MUSIC and DSA detected a spherical target object in the noise field. The relative power levels near the target obtained with MUSIC were compared with those obtained by DSA. Then the effectiveness of the MUSIC method was evaluated according to the rate of increase in the maximum and minimum relative power levels.

  14. Exceptional Solar-System Objects

    NASA Astrophysics Data System (ADS)

    Zellner, Benjamin

    1990-12-01

    This is a target-of-opportunity proposal for HST observations to be executed if a previously unknown, truly exceptional solar-system object or phenomenon is discovered either in the normal course of HST work or by anyone, anywhere. Trails due to unknown moving objects will often appear on HST images made for other purposes. A short trail seen near the opposition point or at high ecliptic latitude could represent a major addition to our knowledge of the solar system. Thus we further propose that all short trials seen on HST images taken in favorable regions of the sky be given a quick analysis in the Observation Support System for their possible significance. If an unusual object is found we propose to: (1) Seek from the owner of data rights permission to proceed as may be appropriate; (2) Contact the Minor Planet Center for an evaluation of the significance of the discovery; and (3) For an object that appears to be of great significance where effective groundbased followup appears unlikely, request the HST schedule be replanned for followup images and physical studies using HST.

  15. Improved space object detection using short-exposure image data with daylight background.

    PubMed

    Becker, David; Cain, Stephen

    2018-05-10

    Space object detection is of great importance in the highly dependent yet competitive and congested space domain. The detection algorithms employed play a crucial role in fulfilling the detection component in the space situational awareness mission to detect, track, characterize, and catalog unknown space objects. Many current space detection algorithms use a matched filter or a spatial correlator on long-exposure data to make a detection decision at a single pixel point of a spatial image based on the assumption that the data follow a Gaussian distribution. Long-exposure imaging is critical to detection performance in these algorithms; however, for imaging under daylight conditions, it becomes necessary to create a long-exposure image as the sum of many short-exposure images. This paper explores the potential for increasing detection capabilities for small and dim space objects in a stack of short-exposure images dominated by a bright background. The algorithm proposed in this paper improves the traditional stack and average method of forming a long-exposure image by selectively removing short-exposure frames of data that do not positively contribute to the overall signal-to-noise ratio of the averaged image. The performance of the algorithm is compared to a traditional matched filter detector using data generated in MATLAB as well as laboratory-collected data. The results are illustrated on a receiver operating characteristic curve to highlight the increased probability of detection associated with the proposed algorithm.

  16. Structural damage detection-oriented multi-type sensor placement with multi-objective optimization

    NASA Astrophysics Data System (ADS)

    Lin, Jian-Fu; Xu, You-Lin; Law, Siu-Seong

    2018-05-01

    A structural damage detection-oriented multi-type sensor placement method with multi-objective optimization is developed in this study. The multi-type response covariance sensitivity-based damage detection method is first introduced. Two objective functions for optimal sensor placement are then introduced in terms of the response covariance sensitivity and the response independence. The multi-objective optimization problem is formed by using the two objective functions, and the non-dominated sorting genetic algorithm (NSGA)-II is adopted to find the solution for the optimal multi-type sensor placement to achieve the best structural damage detection. The proposed method is finally applied to a nine-bay three-dimensional frame structure. Numerical results show that the optimal multi-type sensor placement determined by the proposed method can avoid redundant sensors and provide satisfactory results for structural damage detection. The restriction on the number of each type of sensors in the optimization can reduce the searching space in the optimization to make the proposed method more effective. Moreover, how to select a most optimal sensor placement from the Pareto solutions via the utility function and the knee point method is demonstrated in the case study.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. Time and frequency constrained sonar signal design for optimal detection of elastic objects.

    PubMed

    Hamschin, Brandon; Loughlin, Patrick J

    2013-04-01

    In this paper, the task of model-based transmit signal design for optimizing detection is considered. Building on past work that designs the spectral magnitude for optimizing detection, two methods for synthesizing minimum duration signals with this spectral magnitude are developed. The methods are applied to the design of signals that are optimal for detecting elastic objects in the presence of additive noise and self-noise. Elastic objects are modeled as linear time-invariant systems with known impulse responses, while additive noise (e.g., ocean noise or receiver noise) and acoustic self-noise (e.g., reverberation or clutter) are modeled as stationary Gaussian random processes with known power spectral densities. The first approach finds the waveform that preserves the optimal spectral magnitude while achieving the minimum temporal duration. The second approach yields a finite-length time-domain sequence by maximizing temporal energy concentration, subject to the constraint that the spectral magnitude is close (in a least-squares sense) to the optimal spectral magnitude. The two approaches are then connected analytically, showing the former is a limiting case of the latter. Simulation examples that illustrate the theory are accompanied by discussions that address practical applicability and how one might satisfy the need for target and environmental models in the real-world.

  3. Quantization and training of object detection networks with low-precision weights and activations

    NASA Astrophysics Data System (ADS)

    Yang, Bo; Liu, Jian; Zhou, Li; Wang, Yun; Chen, Jie

    2018-01-01

    As convolutional neural networks have demonstrated state-of-the-art performance in object recognition and detection, there is a growing need for deploying these systems on resource-constrained mobile platforms. However, the computational burden and energy consumption of inference for these networks are significantly higher than what most low-power devices can afford. To address these limitations, this paper proposes a method to train object detection networks with low-precision weights and activations. The probability density functions of weights and activations of each layer are first directly estimated using piecewise Gaussian models. Then, the optimal quantization intervals and step sizes for each convolution layer are adaptively determined according to the distribution of weights and activations. As the most computationally expensive convolutions can be replaced by effective fixed point operations, the proposed method can drastically reduce computation complexity and memory footprint. Performing on the tiny you only look once (YOLO) and YOLO architectures, the proposed method achieves comparable accuracy to their 32-bit counterparts. As an illustration, the proposed 4-bit and 8-bit quantized versions of the YOLO model achieve a mean average precision of 62.6% and 63.9%, respectively, on the Pascal visual object classes 2012 test dataset. The mAP of the 32-bit full-precision baseline model is 64.0%.

  4. 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.

  5. 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.

  6. Parameterisation of non-homogeneities in buried object detection by means of thermography

    NASA Astrophysics Data System (ADS)

    Stepanić, Josip; Malinovec, Marina; Švaić, Srećko; Krstelj, Vjera

    2004-05-01

    Landmines and their natural environment form a system of complex dynamics with variable characteristics. A manifestation of that complexity within the context of thermography-based landmines detection is excessive noise in thermograms. That has severely suppressed application of thermography in landmines detection for the purposes of humanitarian demining. (To be differentiated from military demining and demining for military operations other than war [Land Mine Detection DOD's Research Program Needs a Comprehensive Evaluation Strategy, US GAO Report, GAO-01 239, 2001; International Mine Action Standards, Chapter 4.--Glossary. Available at: < http://www.mineactionstandards.org/IMAS_archive/Final/04.10.pdf>].) The discrepancy between the existing role and the actual potential of thermography in humanitarian demining motivated systematic approach to sources of noise in thermograms of buried objects. These sources are variations in mine orientation relative to soil normal, which modify the shape of mine signature on thermograms, as well as non-homogeneities in soil and vegetation layer above the mine, which modify the overall quality of thermograms. This paper analyses the influence of variable mines, and more generally the influence of axially symmetric buried object orientation on the quality of its signature on thermograms. The following two angles have been extracted to serve as parameters describing variation in orientation: (i) θ--angle between the local vertical axis and mine symmetry axis and (ii) ψ--angle between local vertical axis and soil surface normal. Their influence is compared to the influence of (iii) d--the object depth change, which serves as control parameter. The influences are quantified and ranked within a statistically planned experiment. The analysis has proved that among the parameters listed, the most influential one is statistical interaction dψ, followed with the statistical interaction dθ. According to statistical tests, these two

  7. Robust skin color-based moving object detection for video surveillance

    NASA Astrophysics Data System (ADS)

    Kaliraj, Kalirajan; Manimaran, Sudha

    2016-07-01

    Robust skin color-based moving object detection for video surveillance is proposed. The objective of the proposed algorithm is to detect and track the target under complex situations. The proposed framework comprises four stages, which include preprocessing, skin color-based feature detection, feature classification, and target localization and tracking. In the preprocessing stage, the input image frame is smoothed using averaging filter and transformed into YCrCb color space. In skin color detection, skin color regions are detected using Otsu's method of global thresholding. In the feature classification, histograms of both skin and nonskin regions are constructed and the features are classified into foregrounds and backgrounds based on Bayesian skin color classifier. The foreground skin regions are localized by a connected component labeling process. Finally, the localized foreground skin regions are confirmed as a target by verifying the region properties, and nontarget regions are rejected using the Euler method. At last, the target is tracked by enclosing the bounding box around the target region in all video frames. The experiment was conducted on various publicly available data sets and the performance was evaluated with baseline methods. It evidently shows that the proposed algorithm works well against slowly varying illumination, target rotations, scaling, fast, and abrupt motion changes.

  8. 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

  9. 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.

  10. 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.

  11. Iterative nonlinear joint transform correlation for the detection of objects in cluttered scenes

    NASA Astrophysics Data System (ADS)

    Haist, Tobias; Tiziani, Hans J.

    1999-03-01

    An iterative correlation technique with digital image processing in the feedback loop for the detection of small objects in cluttered scenes is proposed. A scanning aperture is combined with the method in order to improve the immunity against noise and clutter. Multiple reference objects or different views of one object are processed in parallel. We demonstrate the method by detecting a noisy and distorted face in a crowd with a nonlinear joint transform correlator.

  12. The algorithm for automatic detection of the calibration object

    NASA Astrophysics Data System (ADS)

    Artem, Kruglov; Irina, Ugfeld

    2017-06-01

    The problem of the automatic image calibration is considered in this paper. The most challenging task of the automatic calibration is a proper detection of the calibration object. The solving of this problem required the appliance of the methods and algorithms of the digital image processing, such as morphology, filtering, edge detection, shape approximation. The step-by-step process of the development of the algorithm and its adopting to the specific conditions of the log cuts in the image's background is presented. Testing of the automatic calibration module was carrying out under the conditions of the production process of the logging enterprise. Through the tests the average possibility of the automatic isolating of the calibration object is 86.1% in the absence of the type 1 errors. The algorithm was implemented in the automatic calibration module within the mobile software for the log deck volume measurement.

  13. One Shot Detection with Laplacian Object and Fast Matrix Cosine Similarity.

    PubMed

    Biswas, Sujoy Kumar; Milanfar, Peyman

    2016-03-01

    One shot, generic object detection involves searching for a single query object in a larger target image. Relevant approaches have benefited from features that typically model the local similarity patterns. In this paper, we combine local similarity (encoded by local descriptors) with a global context (i.e., a graph structure) of pairwise affinities among the local descriptors, embedding the query descriptors into a low dimensional but discriminatory subspace. Unlike principal components that preserve global structure of feature space, we actually seek a linear approximation to the Laplacian eigenmap that permits us a locality preserving embedding of high dimensional region descriptors. Our second contribution is an accelerated but exact computation of matrix cosine similarity as the decision rule for detection, obviating the computationally expensive sliding window search. We leverage the power of Fourier transform combined with integral image to achieve superior runtime efficiency that allows us to test multiple hypotheses (for pose estimation) within a reasonably short time. Our approach to one shot detection is training-free, and experiments on the standard data sets confirm the efficacy of our model. Besides, low computation cost of the proposed (codebook-free) object detector facilitates rather straightforward query detection in large data sets including movie videos.

  14. 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.

  15. A-Track: A new approach for detection of moving objects in FITS images

    NASA Astrophysics Data System (ADS)

    Atay, T.; Kaplan, M.; Kilic, Y.; Karapinar, N.

    2016-10-01

    We have developed a fast, open-source, cross-platform pipeline, called A-Track, for detecting the moving objects (asteroids and comets) in sequential telescope images in FITS format. The pipeline is coded in Python 3. The moving objects are detected using a modified line detection algorithm, called MILD. We tested the pipeline on astronomical data acquired by an SI-1100 CCD with a 1-meter telescope. We found that A-Track performs very well in terms of detection efficiency, stability, and processing time. The code is hosted on GitHub under the GNU GPL v3 license.

  16. 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.

  17. 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.

  18. Buried object remote detection technology for law enforcement

    NASA Astrophysics Data System (ADS)

    del Grande, Nancy K.; Clark, Gregory A.; Durbin, Philip F.; Fields, David J.; Hernandez, Jose E.; Sherwood, Robert J.

    1991-08-01

    A precise airborne temperature-sensing technology to detect buried objects for use by law enforcement is developed. Demonstrations have imaged the sites of buried foundations, walls and trenches; mapped underground waterways and aquifers; and been used to locate underground military objects. The methodology is incorporated in a commercially available, high signal-to-noise, dual-band infrared scanner with real-time, 12-bit digital image processing software and display. The method creates color-coded images based on surface temperature variations of 0.2 degree(s)C. Unlike other less-sensitive methods, it maps true (corrected) temperatures by removing the (decoupled) surface emissivity mask equivalent to 1 degree(s)C or 2 degree(s)C; this mask hinders interpretation of apparent (blackbody) temperatures. Once removed, it is possible to identify surface temperature patterns from small diffusivity changes at buried object sites which heat and cool differently from their surroundings. Objects made of different materials and buried at different depths are identified by their unique spectral, spatial, thermal, temporal, emissivity and diffusivity signatures. The authors have successfully located the sites of buried (inert) simulated land mines 0.1 to 0.2 m deep; sod-covered rock pathways alongside dry ditches, deeper than 0.2 m; pavement covered burial trenches and cemetery structures as deep as 0.8 m; and aquifers more than 6 m and less than 60 m deep. The technology could be adapted for drug interdiction and pollution control. For the former, buried tunnels, underground structures built beneath typical surface structures, roof-tops disguised by jungle canopies, and covered containers used for contraband would be located. For the latter, buried waste containers, sludge migration pathways from faulty containers, and the juxtaposition of groundwater channels, if present, nearby, would be depicted. The precise airborne temperature-sensing technology has a promising potential

  19. Human visual system-based smoking event detection

    NASA Astrophysics Data System (ADS)

    Odetallah, Amjad D.; Agaian, Sos S.

    2012-06-01

    Human action (e.g. smoking, eating, and phoning) analysis is an important task in various application domains like video surveillance, video retrieval, human-computer interaction systems, and so on. Smoke detection is a crucial task in many video surveillance applications and could have a great impact to raise the level of safety of urban areas, public parks, airplanes, hospitals, schools and others. The detection task is challenging since there is no prior knowledge about the object's shape, texture and color. In addition, its visual features will change under different lighting and weather conditions. This paper presents a new scheme of a system for detecting human smoking events, or small smoke, in a sequence of images. In developed system, motion detection and background subtraction are combined with motion-region-saving, skin-based image segmentation, and smoke-based image segmentation to capture potential smoke regions which are further analyzed to decide on the occurrence of smoking events. Experimental results show the effectiveness of the proposed approach. As well, the developed method is capable of detecting the small smoking events of uncertain actions with various cigarette sizes, colors, and shapes.

  20. Colour Terms Affect Detection of Colour and Colour-Associated Objects Suppressed from Visual Awareness.

    PubMed

    Forder, Lewis; Taylor, Olivia; Mankin, Helen; Scott, Ryan B; Franklin, Anna

    2016-01-01

    The idea that language can affect how we see the world continues to create controversy. A potentially important study in this field has shown that when an object is suppressed from visual awareness using continuous flash suppression (a form of binocular rivalry), detection of the object is differently affected by a preceding word prime depending on whether the prime matches or does not match the object. This may suggest that language can affect early stages of vision. We replicated this paradigm and further investigated whether colour terms likewise influence the detection of colours or colour-associated object images suppressed from visual awareness by continuous flash suppression. This method presents rapidly changing visual noise to one eye while the target stimulus is presented to the other. It has been shown to delay conscious perception of a target for up to several minutes. In Experiment 1 we presented greyscale photos of objects. They were either preceded by a congruent object label, an incongruent label, or white noise. Detection sensitivity (d') and hit rates were significantly poorer for suppressed objects preceded by an incongruent label compared to a congruent label or noise. In Experiment 2, targets were coloured discs preceded by a colour term. Detection sensitivity was significantly worse for suppressed colour patches preceded by an incongruent colour term as compared to a congruent term or white noise. In Experiment 3 targets were suppressed greyscale object images preceded by an auditory presentation of a colour term. On congruent trials the colour term matched the object's stereotypical colour and on incongruent trials the colour term mismatched. Detection sensitivity was significantly poorer on incongruent trials than congruent trials. Overall, these findings suggest that colour terms affect awareness of coloured stimuli and colour- associated objects, and provide new evidence for language-perception interaction in the brain.

  1. 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.

  2. Object detection in natural backgrounds predicted by discrimination performance and models

    NASA Technical Reports Server (NTRS)

    Rohaly, A. M.; Ahumada, A. J. Jr; Watson, A. B.

    1997-01-01

    Many models of visual performance predict image discriminability, the visibility of the difference between a pair of images. We compared the ability of three image discrimination models to predict the detectability of objects embedded in natural backgrounds. The three models were: a multiple channel Cortex transform model with within-channel masking; a single channel contrast sensitivity filter model; and a digital image difference metric. Each model used a Minkowski distance metric (generalized vector magnitude) to summate absolute differences between the background and object plus background images. For each model, this summation was implemented with three different exponents: 2, 4 and infinity. In addition, each combination of model and summation exponent was implemented with and without a simple contrast gain factor. The model outputs were compared to measures of object detectability obtained from 19 observers. Among the models without the contrast gain factor, the multiple channel model with a summation exponent of 4 performed best, predicting the pattern of observer d's with an RMS error of 2.3 dB. The contrast gain factor improved the predictions of all three models for all three exponents. With the factor, the best exponent was 4 for all three models, and their prediction errors were near 1 dB. These results demonstrate that image discrimination models can predict the relative detectability of objects in natural scenes.

  3. 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

  4. 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.

  5. Colour Terms Affect Detection of Colour and Colour-Associated Objects Suppressed from Visual Awareness

    PubMed Central

    Forder, Lewis; Taylor, Olivia; Mankin, Helen; Scott, Ryan B.; Franklin, Anna

    2016-01-01

    The idea that language can affect how we see the world continues to create controversy. A potentially important study in this field has shown that when an object is suppressed from visual awareness using continuous flash suppression (a form of binocular rivalry), detection of the object is differently affected by a preceding word prime depending on whether the prime matches or does not match the object. This may suggest that language can affect early stages of vision. We replicated this paradigm and further investigated whether colour terms likewise influence the detection of colours or colour-associated object images suppressed from visual awareness by continuous flash suppression. This method presents rapidly changing visual noise to one eye while the target stimulus is presented to the other. It has been shown to delay conscious perception of a target for up to several minutes. In Experiment 1 we presented greyscale photos of objects. They were either preceded by a congruent object label, an incongruent label, or white noise. Detection sensitivity (d’) and hit rates were significantly poorer for suppressed objects preceded by an incongruent label compared to a congruent label or noise. In Experiment 2, targets were coloured discs preceded by a colour term. Detection sensitivity was significantly worse for suppressed colour patches preceded by an incongruent colour term as compared to a congruent term or white noise. In Experiment 3 targets were suppressed greyscale object images preceded by an auditory presentation of a colour term. On congruent trials the colour term matched the object’s stereotypical colour and on incongruent trials the colour term mismatched. Detection sensitivity was significantly poorer on incongruent trials than congruent trials. Overall, these findings suggest that colour terms affect awareness of coloured stimuli and colour- associated objects, and provide new evidence for language-perception interaction in the brain. PMID:27023274

  6. Mind the gap: the minimal detectable separation distance between two objects during active electrolocation.

    PubMed

    Fechler, K; Holtkamp, D; Neusel, G; Sanguinetti-Scheck, J I; Budelli, R; von der Emde, G

    2012-12-01

    In a food-rewarded two-alternative forced-choice procedure, it was determined how well the weakly electric elephantnose fish Gnathonemus petersii can sense gaps between two objects, some of which were placed in front of complex backgrounds. The results show that at close distances, G. petersii is able to detect gaps between two small metal cubes (2 cm × 2 cm × 2 cm) down to a width of c. 1·5 mm. When larger objects (3 cm × 3 cm × 3 cm) were used, gaps with a width of 2-3 mm could still be detected. Discrimination performance was better (c. 1 mm gap size) when the objects were placed in front of a moving background consisting of plastic stripes or plant leaves, indicating that movement in the environment plays an important role for object identification. In addition, the smallest gap size that could be detected at increasing distances was determined. A linear relationship between object distance and gap size existed. Minimal detectable gap sizes increased from c. 1·5 mm at a distance of 1 cm, to 20 mm at a distance of 7 cm. Measurements and simulations of the electric stimuli occurring during gap detection revealed that the electric images of two close objects influence each other and superimpose. A large gap of 20 mm between two objects induced two clearly separated peaks in the electric image, while a 2 mm gap caused just a slight indentation in the image. Therefore, the fusion of electric images limits spatial resolution during active electrolocation. Relative movements either between the fish and the objects or between object and background might improve spatial resolution by accentuating the fine details of the electric images. © 2012 The Authors. Journal of Fish Biology © 2012 The Fisheries Society of the British Isles.

  7. 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.

  8. Thresholding Based on Maximum Weighted Object Correlation for Rail Defect Detection

    NASA Astrophysics Data System (ADS)

    Li, Qingyong; Huang, Yaping; Liang, Zhengping; Luo, Siwei

    Automatic thresholding is an important technique for rail defect detection, but traditional methods are not competent enough to fit the characteristics of this application. This paper proposes the Maximum Weighted Object Correlation (MWOC) thresholding method, fitting the features that rail images are unimodal and defect proportion is small. MWOC selects a threshold by optimizing the product of object correlation and the weight term that expresses the proportion of thresholded defects. Our experimental results demonstrate that MWOC achieves misclassification error of 0.85%, and outperforms the other well-established thresholding methods, including Otsu, maximum correlation thresholding, maximum entropy thresholding and valley-emphasis method, for the application of rail defect detection.

  9. Track-Before-Detect Algorithm for Faint Moving Objects based on Random Sampling and Consensus

    NASA Astrophysics Data System (ADS)

    Dao, P.; Rast, R.; Schlaegel, W.; Schmidt, V.; Dentamaro, A.

    2014-09-01

    There are many algorithms developed for tracking and detecting faint moving objects in congested backgrounds. One obvious application is detection of targets in images where each pixel corresponds to the received power in a particular location. In our application, a visible imager operated in stare mode observes geostationary objects as fixed, stars as moving and non-geostationary objects as drifting in the field of view. We would like to achieve high sensitivity detection of the drifters. The ability to improve SNR with track-before-detect (TBD) processing, where target information is collected and collated before the detection decision is made, allows respectable performance against dim moving objects. Generally, a TBD algorithm consists of a pre-processing stage that highlights potential targets and a temporal filtering stage. However, the algorithms that have been successfully demonstrated, e.g. Viterbi-based and Bayesian-based, demand formidable processing power and memory. We propose an algorithm that exploits the quasi constant velocity of objects, the predictability of the stellar clutter and the intrinsically low false alarm rate of detecting signature candidates in 3-D, based on an iterative method called "RANdom SAmple Consensus” and one that can run real-time on a typical PC. The technique is tailored for searching objects with small telescopes in stare mode. Our RANSAC-MT (Moving Target) algorithm estimates parameters of a mathematical model (e.g., linear motion) from a set of observed data which contains a significant number of outliers while identifying inliers. In the pre-processing phase, candidate blobs were selected based on morphology and an intensity threshold that would normally generate unacceptable level of false alarms. The RANSAC sampling rejects candidates that conform to the predictable motion of the stars. Data collected with a 17 inch telescope by AFRL/RH and a COTS lens/EM-CCD sensor by the AFRL/RD Satellite Assessment Center is

  10. Moving object detection via low-rank total variation regularization

    NASA Astrophysics Data System (ADS)

    Wang, Pengcheng; Chen, Qian; Shao, Na

    2016-09-01

    Moving object detection is a challenging task in video surveillance. Recently proposed Robust Principal Component Analysis (RPCA) can recover the outlier patterns from the low-rank data under some mild conditions. However, the l-penalty in RPCA doesn't work well in moving object detection because the irrepresentable condition is often not satisfied. In this paper, a method based on total variation (TV) regularization scheme is proposed. In our model, image sequences captured with a static camera are highly related, which can be described using a low-rank matrix. Meanwhile, the low-rank matrix can absorb background motion, e.g. periodic and random perturbation. The foreground objects in the sequence are usually sparsely distributed and drifting continuously, and can be treated as group outliers from the highly-related background scenes. Instead of l-penalty, we exploit the total variation of the foreground. By minimizing the total variation energy, the outliers tend to collapse and finally converge to be the exact moving objects. The TV-penalty is superior to the l-penalty especially when the outlier is in the majority for some pixels, and our method can estimate the outlier explicitly with less bias but higher variance. To solve the problem, a joint optimization function is formulated and can be effectively solved through the inexact Augmented Lagrange Multiplier (ALM) method. We evaluate our method along with several state-of-the-art approaches in MATLAB. Both qualitative and quantitative results demonstrate that our proposed method works effectively on a large range of complex scenarios.

  11. 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...

  12. Broad attention to multiple individual objects may facilitate change detection with complex auditory scenes.

    PubMed

    Irsik, Vanessa C; Vanden Bosch der Nederlanden, Christina M; Snyder, Joel S

    2016-11-01

    Attention and other processing constraints limit the perception of objects in complex scenes, which has been studied extensively in the visual sense. We used a change deafness paradigm to examine how attention to particular objects helps and hurts the ability to notice changes within complex auditory scenes. In a counterbalanced design, we examined how cueing attention to particular objects affected performance in an auditory change-detection task through the use of valid or invalid cues and trials without cues (Experiment 1). We further examined how successful encoding predicted change-detection performance using an object-encoding task and we addressed whether performing the object-encoding task along with the change-detection task affected performance overall (Experiment 2). Participants had more error for invalid compared to valid and uncued trials, but this effect was reduced in Experiment 2 compared to Experiment 1. When the object-encoding task was present, listeners who completed the uncued condition first had less overall error than those who completed the cued condition first. All participants showed less change deafness when they successfully encoded change-relevant compared to irrelevant objects during valid and uncued trials. However, only participants who completed the uncued condition first also showed this effect during invalid cue trials, suggesting a broader scope of attention. These findings provide converging evidence that attention to change-relevant objects is crucial for successful detection of acoustic changes and that encouraging broad attention to multiple objects is the best way to reduce change deafness. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  13. Detecting Inspection Objects of Power Line from Cable Inspection Robot LiDAR Data

    PubMed Central

    Qin, Xinyan; Wu, Gongping; Fan, Fei

    2018-01-01

    Power lines are extending to complex environments (e.g., lakes and forests), and the distribution of power lines in a tower is becoming complicated (e.g., multi-loop and multi-bundle). Additionally, power line inspection is becoming heavier and more difficult. Advanced LiDAR technology is increasingly being used to solve these difficulties. Based on precise cable inspection robot (CIR) LiDAR data and the distinctive position and orientation system (POS) data, we propose a novel methodology to detect inspection objects surrounding power lines. The proposed method mainly includes four steps: firstly, the original point cloud is divided into single-span data as a processing unit; secondly, the optimal elevation threshold is constructed to remove ground points without the existing filtering algorithm, improving data processing efficiency and extraction accuracy; thirdly, a single power line and its surrounding data can be respectively extracted by a structured partition based on a POS data (SPPD) algorithm from “layer” to “block” according to power line distribution; finally, a partition recognition method is proposed based on the distribution characteristics of inspection objects, highlighting the feature information and improving the recognition effect. The local neighborhood statistics and the 3D region growing method are used to recognize different inspection objects surrounding power lines in a partition. Three datasets were collected by two CIR LIDAR systems in our study. The experimental results demonstrate that an average 90.6% accuracy and average 98.2% precision at the point cloud level can be achieved. The successful extraction indicates that the proposed method is feasible and promising. Our study can be used to obtain precise dimensions of fittings for modeling, as well as automatic detection and location of security risks, so as to improve the intelligence level of power line inspection. PMID:29690560

  14. Detecting Inspection Objects of Power Line from Cable Inspection Robot LiDAR Data.

    PubMed

    Qin, Xinyan; Wu, Gongping; Lei, Jin; Fan, Fei; Ye, Xuhui

    2018-04-22

    Power lines are extending to complex environments (e.g., lakes and forests), and the distribution of power lines in a tower is becoming complicated (e.g., multi-loop and multi-bundle). Additionally, power line inspection is becoming heavier and more difficult. Advanced LiDAR technology is increasingly being used to solve these difficulties. Based on precise cable inspection robot (CIR) LiDAR data and the distinctive position and orientation system (POS) data, we propose a novel methodology to detect inspection objects surrounding power lines. The proposed method mainly includes four steps: firstly, the original point cloud is divided into single-span data as a processing unit; secondly, the optimal elevation threshold is constructed to remove ground points without the existing filtering algorithm, improving data processing efficiency and extraction accuracy; thirdly, a single power line and its surrounding data can be respectively extracted by a structured partition based on a POS data (SPPD) algorithm from "layer" to "block" according to power line distribution; finally, a partition recognition method is proposed based on the distribution characteristics of inspection objects, highlighting the feature information and improving the recognition effect. The local neighborhood statistics and the 3D region growing method are used to recognize different inspection objects surrounding power lines in a partition. Three datasets were collected by two CIR LIDAR systems in our study. The experimental results demonstrate that an average 90.6% accuracy and average 98.2% precision at the point cloud level can be achieved. The successful extraction indicates that the proposed method is feasible and promising. Our study can be used to obtain precise dimensions of fittings for modeling, as well as automatic detection and location of security risks, so as to improve the intelligence level of power line inspection.

  15. Positron emission mammography (PEM): Effect of activity concentration, object size, and object contrast on phantom lesion detection

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

    MacDonald, Lawrence R.; Wang, Carolyn L.; Eissa, Marna

    2012-10-15

    Purpose: To characterize the relationship between lesion detection sensitivity and injected activity as a function of lesion size and contrast on the PEM (positron emission mammography) Flex Solo II scanner using phantom experiments. Methods: Phantom lesions (spheres 4, 8, 12, 16, and 20 mm diameter) were randomly located in uniform background. Sphere activity concentrations were 3 to 21 times the background activity concentration (BGc). BGc was a surrogate for injected activity; BGc ranged from 0.44-4.1 kBq/mL, corresponding to 46-400 MBq injections. Seven radiologists read 108 images containing zero, one, or two spheres. Readers used a 5-point confidence scale to scoremore » the presence of spheres. Results: Sensitivity was 100% for lesions {>=}12 mm under all conditions except for one 12 mm sphere with the lowest contrast and lowest BGc (60% sensitivity). Sensitivity was 100% for 8 mm spheres when either contrast or BGc was high, and 100% for 4 mm spheres only when both contrast and BGc were highest. Sphere contrast recovery coefficients (CRC) were 49%, 34%, 26%, 14%, and 2.8% for the largest to smallest spheres. Cumulative specificity was 98%. Conclusions: Phantom lesion detection sensitivity depends more on sphere size and contrast than on BGc. Detection sensitivity remained {>=}90% for injected activities as low as 100 MBq, for lesions {>=}8 mm. Low CRC in 4 mm objects results in moderate detection sensitivity even for 400 MBq injected activity, making it impractical to optimize injected activity for such lesions. Low CRC indicates that when lesions <8 mm are observed on PEM images they are highly tracer avid with greater potential of clinical significance. High specificity (98%) suggests that image statistical noise does not lead to false positive findings. These results apply to the 85 mm thick object used to obtain them; lesion detectability should be better (worse) for thinner (thicker) objects based on the reduced (increased) influence of photon

  16. Object Detection Based on Template Matching through Use of Best-So-Far ABC

    PubMed Central

    2014-01-01

    Best-so-far ABC is a modified version of the artificial bee colony (ABC) algorithm used for optimization tasks. This algorithm is one of the swarm intelligence (SI) algorithms proposed in recent literature, in which the results demonstrated that the best-so-far ABC can produce higher quality solutions with faster convergence than either the ordinary ABC or the current state-of-the-art ABC-based algorithm. In this work, we aim to apply the best-so-far ABC-based approach for object detection based on template matching by using the difference between the RGB level histograms corresponding to the target object and the template object as the objective function. Results confirm that the proposed method was successful in both detecting objects and optimizing the time used to reach the solution. PMID:24812556

  17. Sensor feature fusion for detecting buried objects

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

    Clark, G.A.; Sengupta, S.K.; Sherwood, R.J.

    1993-04-01

    Given multiple registered images of the earth`s surface from dual-band sensors, our system fuses information from the sensors to reduce the effects of clutter and improve the ability to detect buried or surface target sites. The sensor suite currently includes two sensors (5 micron and 10 micron wavelengths) and one ground penetrating radar (GPR) of the wide-band pulsed synthetic aperture type. We use a supervised teaming pattern recognition approach to detect metal and plastic land mines buried in soil. The overall process consists of four main parts: Preprocessing, feature extraction, feature selection, and classification. These parts are used in amore » two step process to classify a subimage. Thee first step, referred to as feature selection, determines the features of sub-images which result in the greatest separability among the classes. The second step, image labeling, uses the selected features and the decisions from a pattern classifier to label the regions in the image which are likely to correspond to buried mines. We extract features from the images, and use feature selection algorithms to select only the most important features according to their contribution to correct detections. This allows us to save computational complexity and determine which of the sensors add value to the detection system. The most important features from the various sensors are fused using supervised teaming pattern classifiers (including neural networks). We present results of experiments to detect buried land mines from real data, and evaluate the usefulness of fusing feature information from multiple sensor types, including dual-band infrared and ground penetrating radar. The novelty of the work lies mostly in the combination of the algorithms and their application to the very important and currently unsolved operational problem of detecting buried land mines from an airborne standoff platform.« less

  18. 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.

  19. A Real-Time Method to Estimate Speed of Object Based on Object Detection and Optical Flow Calculation

    NASA Astrophysics Data System (ADS)

    Liu, Kaizhan; Ye, Yunming; Li, Xutao; Li, Yan

    2018-04-01

    In recent years Convolutional Neural Network (CNN) has been widely used in computer vision field and makes great progress in lots of contents like object detection and classification. Even so, combining Convolutional Neural Network, which means making multiple CNN frameworks working synchronously and sharing their output information, could figure out useful message that each of them cannot provide singly. Here we introduce a method to real-time estimate speed of object by combining two CNN: YOLOv2 and FlowNet. In every frame, YOLOv2 provides object size; object location and object type while FlowNet providing the optical flow of whole image. On one hand, object size and object location help to select out the object part of optical flow image thus calculating out the average optical flow of every object. On the other hand, object type and object size help to figure out the relationship between optical flow and true speed by means of optics theory and priori knowledge. Therefore, with these two key information, speed of object can be estimated. This method manages to estimate multiple objects at real-time speed by only using a normal camera even in moving status, whose error is acceptable in most application fields like manless driving or robot vision.

  20. 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.

  1. Multi-class geospatial object detection based on a position-sensitive balancing framework for high spatial resolution remote sensing imagery

    NASA Astrophysics Data System (ADS)

    Zhong, Yanfei; Han, Xiaobing; Zhang, Liangpei

    2018-04-01

    Multi-class geospatial object detection from high spatial resolution (HSR) remote sensing imagery is attracting increasing attention in a wide range of object-related civil and engineering applications. However, the distribution of objects in HSR remote sensing imagery is location-variable and complicated, and how to accurately detect the objects in HSR remote sensing imagery is a critical problem. Due to the powerful feature extraction and representation capability of deep learning, the deep learning based region proposal generation and object detection integrated framework has greatly promoted the performance of multi-class geospatial object detection for HSR remote sensing imagery. However, due to the translation caused by the convolution operation in the convolutional neural network (CNN), although the performance of the classification stage is seldom influenced, the localization accuracies of the predicted bounding boxes in the detection stage are easily influenced. The dilemma between translation-invariance in the classification stage and translation-variance in the object detection stage has not been addressed for HSR remote sensing imagery, and causes position accuracy problems for multi-class geospatial object detection with region proposal generation and object detection. In order to further improve the performance of the region proposal generation and object detection integrated framework for HSR remote sensing imagery object detection, a position-sensitive balancing (PSB) framework is proposed in this paper for multi-class geospatial object detection from HSR remote sensing imagery. The proposed PSB framework takes full advantage of the fully convolutional network (FCN), on the basis of a residual network, and adopts the PSB framework to solve the dilemma between translation-invariance in the classification stage and translation-variance in the object detection stage. In addition, a pre-training mechanism is utilized to accelerate the training procedure

  2. A light and faster regional convolutional neural network for object detection in optical remote sensing images

    NASA Astrophysics Data System (ADS)

    Ding, Peng; Zhang, Ye; Deng, Wei-Jian; Jia, Ping; Kuijper, Arjan

    2018-07-01

    Detection of objects from satellite optical remote sensing images is very important for many commercial and governmental applications. With the development of deep convolutional neural networks (deep CNNs), the field of object detection has seen tremendous advances. Currently, objects in satellite remote sensing images can be detected using deep CNNs. In general, optical remote sensing images contain many dense and small objects, and the use of the original Faster Regional CNN framework does not yield a suitably high precision. Therefore, after careful analysis we adopt dense convoluted networks, a multi-scale representation and various combinations of improvement schemes to enhance the structure of the base VGG16-Net for improving the precision. We propose an approach to reduce the test-time (detection time) and memory requirements. To validate the effectiveness of our approach, we perform experiments using satellite remote sensing image datasets of aircraft and automobiles. The results show that the improved network structure can detect objects in satellite optical remote sensing images more accurately and efficiently.

  3. Detection of blob objects in microscopic zebrafish images based on gradient vector diffusion.

    PubMed

    Li, Gang; Liu, Tianming; Nie, Jingxin; Guo, Lei; Malicki, Jarema; Mara, Andrew; Holley, Scott A; Xia, Weiming; Wong, Stephen T C

    2007-10-01

    The zebrafish has become an important vertebrate animal model for the study of developmental biology, functional genomics, and disease mechanisms. It is also being used for drug discovery. Computerized detection of blob objects has been one of the important tasks in quantitative phenotyping of zebrafish. We present a new automated method that is able to detect blob objects, such as nuclei or cells in microscopic zebrafish images. This method is composed of three key steps. The first step is to produce a diffused gradient vector field by a physical elastic deformable model. In the second step, the flux image is computed on the diffused gradient vector field. The third step performs thresholding and nonmaximum suppression based on the flux image. We report the validation and experimental results of this method using zebrafish image datasets from three independent research labs. Both sensitivity and specificity of this method are over 90%. This method is able to differentiate closely juxtaposed or connected blob objects, with high sensitivity and specificity in different situations. It is characterized by a good, consistent performance in blob object detection.

  4. Object-based change detection method using refined Markov random field

    NASA Astrophysics Data System (ADS)

    Peng, Daifeng; Zhang, Yongjun

    2017-01-01

    In order to fully consider the local spatial constraints between neighboring objects in object-based change detection (OBCD), an OBCD approach is presented by introducing a refined Markov random field (MRF). First, two periods of images are stacked and segmented to produce image objects. Second, object spectral and textual histogram features are extracted and G-statistic is implemented to measure the distance among different histogram distributions. Meanwhile, object heterogeneity is calculated by combining spectral and textual histogram distance using adaptive weight. Third, an expectation-maximization algorithm is applied for determining the change category of each object and the initial change map is then generated. Finally, a refined change map is produced by employing the proposed refined object-based MRF method. Three experiments were conducted and compared with some state-of-the-art unsupervised OBCD methods to evaluate the effectiveness of the proposed method. Experimental results demonstrate that the proposed method obtains the highest accuracy among the methods used in this paper, which confirms its validness and effectiveness in OBCD.

  5. Schlieren System and method for moving objects

    NASA Technical Reports Server (NTRS)

    Weinstein, Leonard M. (Inventor)

    1995-01-01

    A system and method are provided for recording density changes in a flow field surrounding a moving object. A mask having an aperture for regulating the passage of images is placed in front of an image recording medium. An optical system is placed in front of the mask. A transition having a light field-of-view and a dark field-of-view is located beyond the test object. The optical system focuses an image of the transition at the mask such that the aperture causes a band of light to be defined on the image recording medium. The optical system further focuses an image of the object through the aperture of the mask so that the image of the object appears on the image recording medium. Relative motion is minimized between the mask and the transition. Relative motion is also minimized between the image recording medium and the image of the object. In this way, the image of the object and density changes in a flow field surrounding the object are recorded on the image recording medium when the object crosses the transition in front of the optical system.

  6. Detecting concealed objects at a checkpoint

    DOEpatents

    McMakin, Douglas L [Richland, WA; Hall, Thomas E [Kennewick, WA; Sheen, David M [Richland, WA; Severtsen, Ronald H [Richland, WA

    2008-07-29

    Disclosed are systems, methods, devices, and apparatus to interrogate a clothed individual with electromagnetic radiation to determine if a concealed object is being carried. This determination includes establishing data corresponding to an image of the individual with a pair of opposed, semi-cylindrical array panels each configured to interrogate the individual with electromagnetic radiation in the 200 MHz to 1 THz range.

  7. Evaluation of Moving Object Detection Based on Various Input Noise Using Fixed Camera

    NASA Astrophysics Data System (ADS)

    Kiaee, N.; Hashemizadeh, E.; Zarrinpanjeh, N.

    2017-09-01

    Detecting and tracking objects in video has been as a research area of interest in the field of image processing and computer vision. This paper evaluates the performance of a novel method for object detection algorithm in video sequences. This process helps us to know the advantage of this method which is being used. The proposed framework compares the correct and wrong detection percentage of this algorithm. This method was evaluated with the collected data in the field of urban transport which include car and pedestrian in fixed camera situation. The results show that the accuracy of the algorithm will decreases because of image resolution reduction.

  8. Object-oriented knowledge representation for expert systems

    NASA Technical Reports Server (NTRS)

    Scott, Stephen L.

    1991-01-01

    Object oriented techniques have generated considerable interest in the Artificial Intelligence (AI) community in recent years. This paper discusses an approach for representing expert system knowledge using classes, objects, and message passing. The implementation is in version 4.3 of NASA's C Language Integrated Production System (CLIPS), an expert system tool that does not provide direct support for object oriented design. The method uses programmer imposed conventions and keywords to structure facts, and rules to provide object oriented capabilities.

  9. Detection and Localization of Subsurface Two-Dimensional Metallic Objects

    NASA Astrophysics Data System (ADS)

    Meschino, S.; Pajewski, L.; Schettini, G.

    2009-04-01

    "Roma Tre" University, Applied Electronics Dept.v. Vasca Navale 84, 00146 Rome, Italy Non-invasive identification of buried objects in the near-field of a receiver array is a subject of great interest, due to its application to the remote sensing of the earth's subsurface, to the detection of landmines, pipes, conduits, to the archaeological site characterization, and more. In this work, we present a Sub-Array Processing (SAP) approach for the detection and localization of subsurface perfectly-conducting circular cylinders. We consider a plane wave illuminating the region of interest, which is assumed to be a homogeneous, unlossy medium of unknown permittivity containing one or more targets. In a first step, we partition the receiver array so that the field scattered from the targets result to be locally plane at each sub-array. Then, we apply a Direction of Arrival (DOA) technique to obtain a set of angles for each locally plane wave, and triangulate these directions obtaining a collection of crossing crowding in the expected object locations [1]. We compare several DOA algorithms such as the traditional Bartlett and Capon Beamforming, the Pisarenko Harmonic Decomposition (PHD), the Minimum-Norm method, the Multiple Signal Classification (MUSIC) and the Estimation of Signal Parameters via Rotational Techinque (ESPRIT) [2]. In a second stage, we develop a statistical Poisson based model to manage the crossing pattern in order to extract the probable target's centre position. In particular, if the crossings are Poisson distributed, it is possible to feature two different distribution parameters [3]. These two parameters perform two density rate for the crossings, so that we can previously divide the crossing pattern in a certain number of equal-size windows and we can collect the windows of the crossing pattern with low rate parameters (that probably are background windows) and remove them. In this way we can consider only the high rate parameter windows (that most

  10. 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.

  11. Distribution majorization of corner points by reinforcement learning for moving object detection

    NASA Astrophysics Data System (ADS)

    Wu, Hao; Yu, Hao; Zhou, Dongxiang; Cheng, Yongqiang

    2018-04-01

    Corner points play an important role in moving object detection, especially in the case of free-moving camera. Corner points provide more accurate information than other pixels and reduce the computation which is unnecessary. Previous works only use intensity information to locate the corner points, however, the information that former and the last frames provided also can be used. We utilize the information to focus on more valuable area and ignore the invaluable area. The proposed algorithm is based on reinforcement learning, which regards the detection of corner points as a Markov process. In the Markov model, the video to be detected is regarded as environment, the selections of blocks for one corner point are regarded as actions and the performance of detection is regarded as state. Corner points are assigned to be the blocks which are seperated from original whole image. Experimentally, we select a conventional method which uses marching and Random Sample Consensus algorithm to obtain objects as the main framework and utilize our algorithm to improve the result. The comparison between the conventional method and the same one with our algorithm show that our algorithm reduce 70% of the false detection.

  12. Wide field imaging - I. Applications of neural networks to object detection and star/galaxy classification

    NASA Astrophysics Data System (ADS)

    Andreon, S.; Gargiulo, G.; Longo, G.; Tagliaferri, R.; Capuano, N.

    2000-12-01

    Astronomical wide-field imaging performed with new large-format CCD detectors poses data reduction problems of unprecedented scale, which are difficult to deal with using traditional interactive tools. We present here NExt (Neural Extractor), a new neural network (NN) based package capable of detecting objects and performing both deblending and star/galaxy classification in an automatic way. Traditionally, in astronomical images, objects are first distinguished from the noisy background by searching for sets of connected pixels having brightnesses above a given threshold; they are then classified as stars or as galaxies through diagnostic diagrams having variables chosen according to the astronomer's taste and experience. In the extraction step, assuming that images are well sampled, NExt requires only the simplest a priori definition of `what an object is' (i.e. it keeps all structures composed of more than one pixel) and performs the detection via an unsupervised NN, approaching detection as a clustering problem that has been thoroughly studied in the artificial intelligence literature. The first part of the NExt procedure consists of an optimal compression of the redundant information contained in the pixels via a mapping from pixel intensities to a subspace individualized through principal component analysis. At magnitudes fainter than the completeness limit, stars are usually almost indistinguishable from galaxies, and therefore the parameters characterizing the two classes do not lie in disconnected subspaces, thus preventing the use of unsupervised methods. We therefore adopted a supervised NN (i.e. a NN that first finds the rules to classify objects from examples and then applies them to the whole data set). In practice, each object is classified depending on its membership of the regions mapping the input feature space in the training set. In order to obtain an objective and reliable classification, instead of using an arbitrarily defined set of features

  13. A visual model for object detection based on active contours and level-set method.

    PubMed

    Satoh, Shunji

    2006-09-01

    A visual model for object detection is proposed. In order to make the detection ability comparable with existing technical methods for object detection, an evolution equation of neurons in the model is derived from the computational principle of active contours. The hierarchical structure of the model emerges naturally from the evolution equation. One drawback involved with initial values of active contours is alleviated by introducing and formulating convexity, which is a visual property. Numerical experiments show that the proposed model detects objects with complex topologies and that it is tolerant of noise. A visual attention model is introduced into the proposed model. Other simulations show that the visual properties of the model are consistent with the results of psychological experiments that disclose the relation between figure-ground reversal and visual attention. We also demonstrate that the model tends to perceive smaller regions as figures, which is a characteristic observed in human visual perception.

  14. 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.

  15. Handheld microwave bomb-detecting imaging system

    NASA Astrophysics Data System (ADS)

    Gorwara, Ashok; Molchanov, Pavlo

    2017-05-01

    Proposed novel imaging technique will provide all weather high-resolution imaging and recognition capability for RF/Microwave signals with good penetration through highly scattered media: fog, snow, dust, smoke, even foliage, camouflage, walls and ground. Image resolution in proposed imaging system is not limited by diffraction and will be determined by processor and sampling frequency. Proposed imaging system can simultaneously cover wide field of view, detect multiple targets and can be multi-frequency, multi-function. Directional antennas in imaging system can be close positioned and installed in cell phone size handheld device, on small aircraft or distributed around protected border or object. Non-scanning monopulse system allows dramatically decrease in transmitting power and at the same time provides increased imaging range by integrating 2-3 orders more signals than regular scanning imaging systems.

  16. What are the underlying units of perceived animacy? Chasing detection is intrinsically object-based.

    PubMed

    van Buren, Benjamin; Gao, Tao; Scholl, Brian J

    2017-10-01

    One of the most foundational questions that can be asked about any visual process is the nature of the underlying 'units' over which it operates (e.g., features, objects, or spatial regions). Here we address this question-for the first time, to our knowledge-in the context of the perception of animacy. Even simple geometric shapes appear animate when they move in certain ways. Do such percepts arise whenever any visual feature moves appropriately, or do they require that the relevant features first be individuated as discrete objects? Observers viewed displays in which one disc (the "wolf") chased another (the "sheep") among several moving distractor discs. Critically, two pairs of discs were also connected by visible lines. In the Unconnected condition, both lines connected pairs of distractors; but in the Connected condition, one connected the wolf to a distractor, and the other connected the sheep to a different distractor. Observers in the Connected condition were much less likely to describe such displays using mental state terms. Furthermore, signal detection analyses were used to explore the objective ability to discriminate chasing displays from inanimate control displays in which the wolf moved toward the sheep's mirror-image. Chasing detection was severely impaired on Connected trials: observers could readily detect an object chasing another object, but not a line-end chasing another line-end, a line-end chasing an object, or an object chasing a line-end. We conclude that the underlying units of perceived animacy are discrete visual objects.

  17. 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...

  18. Propagation and Detection of Neutrinos from Distant Objects

    NASA Astrophysics Data System (ADS)

    Bottino, A.; Kim, C. W.; Kim, Jewan; Lam, W. P.

    We discuss how an initial composition of wave packets representing the neutrinos, emitted by distant objects such as supernovae, is modified as the neutrinos travel a long distance to the earth and how these modifications affect the detection of such neutrinos. In particular, observed neutrino masses are shown to depend on the mass square difference of the i-th and j-th flavors i.e., mi2 - mj2, L (the distance traveled), and a resolution time of the detector as well as on how neutrinos emerge from the star.

  19. Controlled biological and biomimetic systems for landmine detection.

    PubMed

    Habib, Maki K

    2007-08-30

    Humanitarian demining requires to accurately detect, locate and deactivate every single landmine and other buried mine-like objects as safely and as quickly as possible, and in the most non-invasive manner. The quality of landmine detection affects directly the efficiency and safety of this process. Most of the available methods to detect explosives and landmines are limited by their sensitivity and/or operational complexities. All landmines leak with time small amounts of their explosives that can be found on surrounding ground and plant life. Hence, explosive signatures represent the robust primary indicator of landmines. Accordingly, developing innovative technologies and efficient techniques to identify in real-time explosives residue in mined areas represents an attractive and promising approach. Biological and biologically inspired detection technology has the potential to compete with or be used in conjunction with other artificial technology to complement performance strengths. Biological systems are sensitive to many different scents concurrently, a property that has proven difficult to replicate artificially. Understanding biological systems presents unique opportunities for developing new capabilities through direct use of trained bio-systems, integration of living and non-living components, or inspiring new design by mimicking biological capabilities. It is expected that controlled bio-systems, biotechnology and microbial techniques will contribute to the advancement of mine detection and other application domains. This paper provides directions, evaluation and analysis on the progress of controlled biological and biomimetic systems for landmine detection. It introduces and discusses different approaches developed, underlining their relative advantages and limitations, and highlighting trends, safety and ecology concern, and possible future directions.

  20. Learning to detect and combine the features of an object

    PubMed Central

    Suchow, Jordan W.; Pelli, Denis G.

    2013-01-01

    To recognize an object, it is widely supposed that we first detect and then combine its features. Familiar objects are recognized effortlessly, but unfamiliar objects—like new faces or foreign-language letters—are hard to distinguish and must be learned through practice. Here, we describe a method that separates detection and combination and reveals how each improves as the observer learns. We dissociate the steps by two independent manipulations: For each step, we do or do not provide a bionic crutch that performs it optimally. Thus, the two steps may be performed solely by the human, solely by the crutches, or cooperatively, when the human takes one step and a crutch takes the other. The crutches reveal a double dissociation between detecting and combining. Relative to the two-step ideal, the human observer’s overall efficiency for unconstrained identification equals the product of the efficiencies with which the human performs the steps separately. The two-step strategy is inefficient: Constraining the ideal to take two steps roughly halves its identification efficiency. In contrast, we find that humans constrained to take two steps perform just as well as when unconstrained, which suggests that they normally take two steps. Measuring threshold contrast (the faintness of a barely identifiable letter) as it improves with practice, we find that detection is inefficient and learned slowly. Combining is learned at a rate that is 4× higher and, after 1,000 trials, 7× more efficient. This difference explains much of the diversity of rates reported in perceptual learning studies, including effects of complexity and familiarity. PMID:23267067

  1. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1987-01-01

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

  3. Zero-Copy Objects System

    NASA Technical Reports Server (NTRS)

    Burleigh, Scott C.

    2011-01-01

    Zero-Copy Objects System software enables application data to be encapsulated in layers of communication protocol without being copied. Indirect referencing enables application source data, either in memory or in a file, to be encapsulated in place within an unlimited number of protocol headers and/or trailers. Zero-copy objects (ZCOs) are abstract data access representations designed to minimize I/O (input/output) in the encapsulation of application source data within one or more layers of communication protocol structure. They are constructed within the heap space of a Simple Data Recorder (SDR) data store to which all participating layers of the stack must have access. Each ZCO contains general information enabling access to the core source data object (an item of application data), together with (a) a linked list of zero or more specific extents that reference portions of this source data object, and (b) linked lists of protocol header and trailer capsules. The concatenation of the headers (in ascending stack sequence), the source data object extents, and the trailers (in descending stack sequence) constitute the transmitted data object constructed from the ZCO. This scheme enables a source data object to be encapsulated in a succession of protocol layers without ever having to be copied from a buffer at one layer of the protocol stack to an encapsulating buffer at a lower layer of the stack. For large source data objects, the savings in copy time and reduction in memory consumption may be considerable.

  4. Change detection from remotely sensed images: From pixel-based to object-based approaches

    NASA Astrophysics Data System (ADS)

    Hussain, Masroor; Chen, Dongmei; Cheng, Angela; Wei, Hui; Stanley, David

    2013-06-01

    The appetite for up-to-date information about earth's surface is ever increasing, as such information provides a base for a large number of applications, including local, regional and global resources monitoring, land-cover and land-use change monitoring, and environmental studies. The data from remote sensing satellites provide opportunities to acquire information about land at varying resolutions and has been widely used for change detection studies. A large number of change detection methodologies and techniques, utilizing remotely sensed data, have been developed, and newer techniques are still emerging. This paper begins with a discussion of the traditionally pixel-based and (mostly) statistics-oriented change detection techniques which focus mainly on the spectral values and mostly ignore the spatial context. This is succeeded by a review of object-based change detection techniques. Finally there is a brief discussion of spatial data mining techniques in image processing and change detection from remote sensing data. The merits and issues of different techniques are compared. The importance of the exponential increase in the image data volume and multiple sensors and associated challenges on the development of change detection techniques are highlighted. With the wide use of very-high-resolution (VHR) remotely sensed images, object-based methods and data mining techniques may have more potential in change detection.

  5. Buried object remote detection technology for law enforcement

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

    Del Grande, N.K.; Clark, G.A.; Durbin, P.F.

    1991-03-01

    We have developed a precise airborne temperature-sensing technology to detect buried objects for use by law enforcement. Demonstrations have imaged the sites of buried foundations, walls and trenches; mapped underground waterways and aquifers; and been used to locate underground military objects. Our patented methodology is incorporated in a commercially available, high signal-to-noise, dual-band infrared scanner with real-time, 12-bit digital image processing software and display. Our method creates color-coded images based on surface temperature variations of 0.2 {degrees}C. Unlike other less-sensitive methods, it maps true (corrected) temperatures by removing the (decoupled) surface emissivity mask equivalent to 1{degrees}C or 2{degrees}C; this maskmore » hinders interpretation of apparent (blackbody) temperatures. Once removed, were are able to identify surface temperature patterns from small diffusivity changes at buried object sites which heat and cool differently from their surroundings. Objects made of different materials and buried at different depths are identified by their unique spectra, spatial, thermal, temporal, emissivity and diffusivity signatures. We have successfully located the sites of buried (inert) simulated land mines 0.1 to 0.2 m deep; sod-covered rock pathways alongside dry ditches, deeper than 0.2 m; pavement covered burial trenches and cemetery structures as deep as 0.8 m; and aquifers more than 6 m and less 60 m deep. Our technology could be adapted for drug interdiction and pollution control. 16 refs., 14 figs.« less

  6. Utilization of an Airborne Plant Chlorophyll Imaging System for Detection of Septic System Malfunction

    NASA Technical Reports Server (NTRS)

    Spiering, Bruce A.; Carter, Gregory A.

    2001-01-01

    Malfunctioning, or leaking, sewer systems increase the supply of water and nutrients to surface vegetation. Excess nutrients and harmful bacteria in the effluent pollute ground water and local water bodies and are dangerous to humans and the aquatic ecosystems. An airborne multispectral plant chlorophyll imaging system (PCIS) was used to identify growth patterns in the vegetation covering onsite and public sewer systems. The objective was to evaluate overall performance of the PCIS as well as to determine the best operational configuration for this application. The imaging system was flown in a light aircraft over selected locations Mobile County, Alabama. Calibration panels were used to help characterize instrument performance. Results demonstrated that the PCIS performed well and was capable of detecting septic leakage patterns from altitudes as high as 915 m. From 915 m, 6 of 18 sites were suspected to have sewage leakage. Subsequent ground inspections confirmed leakage on 3 of the 6 sites. From 610 m, 3 of 8 known leakage sites were detected. Tree cover and shadows near residential structures prevented detection of several known malfunctioning systems. Also some leakages known to occur in clear areas were not detected. False detections occurred in areas characterized by surface water drainage problems or recent excavation.

  7. Multi-class geospatial object detection and geographic image classification based on collection of part detectors

    NASA Astrophysics Data System (ADS)

    Cheng, Gong; Han, Junwei; Zhou, Peicheng; Guo, Lei

    2014-12-01

    The rapid development of remote sensing technology has facilitated us the acquisition of remote sensing images with higher and higher spatial resolution, but how to automatically understand the image contents is still a big challenge. In this paper, we develop a practical and rotation-invariant framework for multi-class geospatial object detection and geographic image classification based on collection of part detectors (COPD). The COPD is composed of a set of representative and discriminative part detectors, where each part detector is a linear support vector machine (SVM) classifier used for the detection of objects or recurring spatial patterns within a certain range of orientation. Specifically, when performing multi-class geospatial object detection, we learn a set of seed-based part detectors where each part detector corresponds to a particular viewpoint of an object class, so the collection of them provides a solution for rotation-invariant detection of multi-class objects. When performing geographic image classification, we utilize a large number of pre-trained part detectors to discovery distinctive visual parts from images and use them as attributes to represent the images. Comprehensive evaluations on two remote sensing image databases and comparisons with some state-of-the-art approaches demonstrate the effectiveness and superiority of the developed framework.

  8. Evaluation of methods for detection of fluorescence labeled subcellular objects in microscope images.

    PubMed

    Ruusuvuori, Pekka; Aijö, Tarmo; Chowdhury, Sharif; Garmendia-Torres, Cecilia; Selinummi, Jyrki; Birbaumer, Mirko; Dudley, Aimée M; Pelkmans, Lucas; Yli-Harja, Olli

    2010-05-13

    Several algorithms have been proposed for detecting fluorescently labeled subcellular objects in microscope images. Many of these algorithms have been designed for specific tasks and validated with limited image data. But despite the potential of using extensive comparisons between algorithms to provide useful information to guide method selection and thus more accurate results, relatively few studies have been performed. To better understand algorithm performance under different conditions, we have carried out a comparative study including eleven spot detection or segmentation algorithms from various application fields. We used microscope images from well plate experiments with a human osteosarcoma cell line and frames from image stacks of yeast cells in different focal planes. These experimentally derived images permit a comparison of method performance in realistic situations where the number of objects varies within image set. We also used simulated microscope images in order to compare the methods and validate them against a ground truth reference result. Our study finds major differences in the performance of different algorithms, in terms of both object counts and segmentation accuracies. These results suggest that the selection of detection algorithms for image based screens should be done carefully and take into account different conditions, such as the possibility of acquiring empty images or images with very few spots. Our inclusion of methods that have not been used before in this context broadens the set of available detection methods and compares them against the current state-of-the-art methods for subcellular particle detection.

  9. 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. 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.

  11. Detection of radio continuum emission from Herbig-Haro objects 1 and 2 and from their central exciting source

    NASA Technical Reports Server (NTRS)

    Pravdo, S. H.; Rodriguez, L. F.; Curiel, S.; Canto, J.; Torrelles, J. M.; Becker, R. H.; Sellgren, K.

    1985-01-01

    The region in Orion containing HH 1 and HH 2 was observed with the VLA at 20, 6, and 2 cm on several occasions from 1981 to 1984. At lower resolution, four continuum sources were detected. Two of these sources coincide positionally with HH 1 and HH 2. At 6 cm and higher resolution, HH 1 is resolved into at least two components. The emission is probably bremsstrahlung originating in the same region where the visible line emission is produced. This is the first detection of radio continuum from classic Herbig-Haro objects. At a position closely centered between HH 1 and HH 2, an object that can be interpreted as the energy source of the system was detected. The central source spectrum is S(nu) of about nu to the alpha power, where alpha = 0.4 + or - 0.2, suggesting a stellar wind. Finally, the fourth radio continuum source coincides positionally with an H2O maser and is probably excited by an independent star. There is evidence of time variability in its radio flux. No emission was detected from the Cohen-Schwartz (1979) star at the 0.1 mJy level.

  12. 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.

  13. 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.

  14. System and method for disrupting suspect objects

    DOEpatents

    Gladwell, T. Scott; Garretson, Justin R; Hobart, Clinton G; Monda, Mark J

    2013-07-09

    A system and method for disrupting at least one component of a suspect object is provided. The system includes a source for passing radiation through the suspect object, a screen for receiving the radiation passing through the suspect object and generating at least one image therefrom, a weapon having a discharge deployable therefrom, and a targeting unit. The targeting unit displays the image(s) of the suspect object and aims the weapon at a disruption point on the displayed image such that the weapon may be positioned to deploy the discharge at the disruption point whereby the suspect object is disabled.

  15. Collision detection and modeling of rigid and deformable objects in laparoscopic simulator

    NASA Astrophysics Data System (ADS)

    Dy, Mary-Clare; Tagawa, Kazuyoshi; Tanaka, Hiromi T.; Komori, Masaru

    2015-03-01

    Laparoscopic simulators are viable alternatives for surgical training and rehearsal. Haptic devices can also be incorporated with virtual reality simulators to provide additional cues to the users. However, to provide realistic feedback, the haptic device must be updated by 1kHz. On the other hand, realistic visual cues, that is, the collision detection and deformation between interacting objects must be rendered at least 30 fps. Our current laparoscopic simulator detects the collision between a point on the tool tip, and on the organ surfaces, in which haptic devices are attached on actual tool tips for realistic tool manipulation. The triangular-mesh organ model is rendered using a mass spring deformation model, or finite element method-based models. In this paper, we investigated multi-point-based collision detection on the rigid tool rods. Based on the preliminary results, we propose a method to improve the collision detection scheme, and speed up the organ deformation reaction. We discuss our proposal for an efficient method to compute simultaneous multiple collision between rigid (laparoscopic tools) and deformable (organs) objects, and perform the subsequent collision response, with haptic feedback, in real-time.

  16. Vision-based algorithms for near-host object detection and multilane sensing

    NASA Astrophysics Data System (ADS)

    Kenue, Surender K.

    1995-01-01

    Vision-based sensing can be used for lane sensing, adaptive cruise control, collision warning, and driver performance monitoring functions of intelligent vehicles. Current computer vision algorithms are not robust for handling multiple vehicles in highway scenarios. Several new algorithms are proposed for multi-lane sensing, near-host object detection, vehicle cut-in situations, and specifying regions of interest for object tracking. These algorithms were tested successfully on more than 6000 images taken from real-highway scenes under different daytime lighting conditions.

  17. An object-based classification method for automatic detection of lunar impact craters from topographic data

    NASA Astrophysics Data System (ADS)

    Vamshi, Gasiganti T.; Martha, Tapas R.; Vinod Kumar, K.

    2016-05-01

    Identification of impact craters is a primary requirement to study past geological processes such as impact history. They are also used as proxies for measuring relative ages of various planetary or satellite bodies and help to understand the evolution of planetary surfaces. In this paper, we present a new method using object-based image analysis (OBIA) technique to detect impact craters of wide range of sizes from topographic data. Multiresolution image segmentation of digital terrain models (DTMs) available from the NASA's LRO mission was carried out to create objects. Subsequently, objects were classified into impact craters using shape and morphometric criteria resulting in 95% detection accuracy. The methodology developed in a training area in parts of Mare Imbrium in the form of a knowledge-based ruleset when applied in another area, detected impact craters with 90% accuracy. The minimum and maximum sizes (diameters) of impact craters detected in parts of Mare Imbrium by our method are 29 m and 1.5 km, respectively. Diameters of automatically detected impact craters show good correlation (R2 > 0.85) with the diameters of manually detected impact craters.

  18. Combining TerraSAR-X and SPOT-5 data for object-based landslide detection

    NASA Astrophysics Data System (ADS)

    Friedl, B.; Hölbling, D.; Füreder, P.

    2012-04-01

    Landslide detection and classification is an essential requirement in pre- and post-disaster hazard analysis. In earlier studies landslide detection often was achieved through time-consuming and cost-intensive field surveys and visual orthophoto interpretation. Recent studies show that Earth Observation (EO) data offer new opportunities for fast, reliable and accurate landslide detection and classification, which may conduce to an effective landslide monitoring and landslide hazard management. To ensure the fast recognition and classification of landslides at a regional scale, a (semi-)automated object-based landslide detection approach is established for a study site situated in the Huaguoshan catchment, Southern Taiwan. The study site exhibits a high vulnerability to landslides and debris flows, which are predominantly typhoon-induced. Through the integration of optical satellite data (SPOT-5 with 2.5 m GSD), SAR (Synthetic Aperture Radar) data (TerraSAR-X Spotlight with 2.95 m GSD) and digital elevation information (DEM with 5 m GSD) including its derived products (e.g. slope, curvature, flow accumulation) landslides may be examined in a more efficient way as if relying on single data sources only. The combination of optical and SAR data in an object-based image analysis (OBIA) domain for landslide detection and classification has not been investigated so far, even if SAR imagery show valuable properties for landslide detection, which differ from optical data (e.g. high sensitivity to surface roughness and soil moisture). The main purpose of this study is to recognize and analyze existing landslides by applying object-based image analysis making use of eCognition software. OBIA provides a framework for examining features defined by spectral, spatial, textural, contextual as well as hierarchical properties. Objects are derived through image segmentation and serve as input for the classification process, which relies on transparent rulesets, representing knowledge

  19. A novel method for overlapping community detection using Multi-objective optimization

    NASA Astrophysics Data System (ADS)

    Ebrahimi, Morteza; Shahmoradi, Mohammad Reza; Heshmati, Zainabolhoda; Salehi, Mostafa

    2018-09-01

    The problem of community detection as one of the most important applications of network science can be addressed effectively by multi-objective optimization. In this paper, we aim to present a novel efficient method based on this approach. Also, in this study the idea of using all Pareto fronts to detect overlapping communities is introduced. The proposed method has two main advantages compared to other multi-objective optimization based approaches. The first advantage is scalability, and the second is the ability to find overlapping communities. Despite most of the works, the proposed method is able to find overlapping communities effectively. The new algorithm works by extracting appropriate communities from all the Pareto optimal solutions, instead of choosing the one optimal solution. Empirical experiments on different features of separated and overlapping communities, on both synthetic and real networks show that the proposed method performs better in comparison with other methods.

  20. Objective tropical cyclone extratropical transition detection in high-resolution reanalysis and climate model data

    DOE PAGES

    Zarzycki, Colin M.; Thatcher, Diana R.; Jablonowski, Christiane

    2017-01-22

    This paper describes an objective technique for detecting the extratropical transition (ET) of tropical cyclones (TCs) in high-resolution gridded climate data. The algorithm is based on previous observational studies using phase spaces to define the symmetry and vertical thermal structure of cyclones. Storm tracking is automated, allowing for direct analysis of climate data. Tracker performance in the North Atlantic is assessed using 23 years of data from the variable-resolution Community Atmosphere Model (CAM) at two different resolutions (DX 55 km and 28 km), the Climate Forecast System Reanalysis (CFSR, DX 38 km), and the ERA-Interim Reanalysis (ERA-I, DX 80 km).more » The mean spatiotemporal climatologies and seasonal cycles of objectively detected ET in the observationally constrained CFSR and ERA-I are well matched to previous observational studies, demonstrating the capability of the scheme to adequately find events. High resolution CAM reproduces TC and ET statistics that are in general agreement with reanalyses. One notable model bias, however, is significantly longer time between ET onset and ET completion in CAM, particularly for TCs that lose symmetry prior to developing a cold-core structure and becoming extratropical cyclones, demonstrating the capability of this method to expose model biases in simulated cyclones beyond the tropical phase.« less

  1. Contour symmetry detection: the influence of axis orientation and number of objects.

    PubMed

    Friedenberg, J; Bertamini, M

    2000-09-01

    Participants discriminated symmetrical from random contours connected by straight lines to form part of one- or two-objects. In experiment one, symmetrical contours were translated or reflected and presented at vertical, horizontal, and oblique axis orientations with orientation constant within blocks. Translated two-object contours were detected more easily than one, replicating a "lock-and-key" effect obtained previously for vertical orientations only [M. Bertamini, J.D. Friedenberg, M. Kubovy, Acta Psychologica, 95 (1997) 119-140]. A second experiment extended these results to a wider variety of axis orientations under mixed block conditions. The pattern of performance for translation and reflection at different orientations corresponded in both experiments, suggesting that orientation is processed similarly in the detection of these symmetries.

  2. 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.

  3. Automatic flatness detection system for micro part

    NASA Astrophysics Data System (ADS)

    Luo, Yi; Wang, Xiaodong; Shan, Zhendong; Li, Kehong

    2016-01-01

    An automatic flatness detection system for micro rings is developed. It is made up of machine vision module, ring supporting module and control system. An industry CCD camera with the resolution of 1628×1236 pixel, a telecentric with magnification of two, and light sources are used to collect the vision information. A rotary stage with a polished silicon wafer is used to support the ring. The silicon wafer provides a mirror image and doubles the gap caused by unevenness of the ring. The control system comprise an industry computer and software written in LabVIEW Get Kernel and Convolute Function are selected to reduce noise and distortion, Laplacian Operator is used to sharp the image, and IMAQ Threshold function is used to separate the target object from the background. Based on this software, system repeating precision is 2.19 μm, less than one pixel. The designed detection system can easily identify the ring warpage larger than 5 μm, and if the warpage is less than 25 μm, it can be used in ring assembly and satisfied the final positionary and perpendicularity error requirement of the component.

  4. Traffic intensity monitoring using multiple object detection with traffic surveillance cameras

    NASA Astrophysics Data System (ADS)

    Hamdan, H. G. Muhammad; Khalifah, O. O.

    2017-11-01

    Object detection and tracking is a field of research that has many applications in the current generation with increasing number of cameras on the streets and lower cost for Internet of Things(IoT). In this paper, a traffic intensity monitoring system is implemented based on the Macroscopic Urban Traffic model is proposed using computer vision as its source. The input of this program is extracted from a traffic surveillance camera which has another program running a neural network classification which can identify and differentiate the vehicle type is implanted. The neural network toolbox is trained with positive and negative input to increase accuracy. The accuracy of the program is compared to other related works done and the trends of the traffic intensity from a road is also calculated. relevant articles in literature searches, great care should be taken in constructing both. Lastly the limitation and the future work is concluded.

  5. An object correlation and maneuver detection approach for space surveillance

    NASA Astrophysics Data System (ADS)

    Huang, Jian; Hu, Wei-Dong; Xin, Qin; Du, Xiao-Yong

    2012-10-01

    Object correlation and maneuver detection are persistent problems in space surveillance and maintenance of a space object catalog. We integrate these two problems into one interrelated problem, and consider them simultaneously under a scenario where space objects only perform a single in-track orbital maneuver during the time intervals between observations. We mathematically formulate this integrated scenario as a maximum a posteriori (MAP) estimation. In this work, we propose a novel approach to solve the MAP estimation. More precisely, the corresponding posterior probability of an orbital maneuver and a joint association event can be approximated by the Joint Probabilistic Data Association (JPDA) algorithm. Subsequently, the maneuvering parameters are estimated by optimally solving the constrained non-linear least squares iterative process based on the second-order cone programming (SOCP) algorithm. The desired solution is derived according to the MAP criterions. The performance and advantages of the proposed approach have been shown by both theoretical analysis and simulation results. We hope that our work will stimulate future work on space surveillance and maintenance of a space object catalog.

  6. Demand artifact: objectively detecting biased participants in advertising research.

    PubMed

    Miller, Felicia; Schertzer, Susan

    2014-12-01

    Detecting and reducing the effect of biased participants continues to be an important task for researchers. However, the lack of objective measures to assess demand artifact has made it difficult to effectively address this issue. This paper reports two experiments that apply a theory-based post-experimental inquiry that can systematically identify biased participants in consumer research. The results demonstrate how easily and effectively researchers can incorporate this tool into experimental studies of all types and reduce the likelihood of systematic error.

  7. Acoustic and electromagnetic wave interaction in the detection and identification of buried objects

    NASA Astrophysics Data System (ADS)

    Lawrence, Daniel Edward

    2002-09-01

    In order to facilitate the development of a hybrid acoustic and electromagnetic (EM) system for buried object detection, a number of analytical solutions and a novel numerical technique are developed to analyze the complex interaction between acoustic and EM scattering. The essence of the interaction lies in the fact that identifiable acoustic properties of an object, such as acoustic resonances, can be observed in the scattered EM Doppler spectrum. Using a perturbation approach, analytical solutions are derived for the EM scattering from infinitely long circular cylinders, both metallic and dielectric, under acoustic vibration in a homogeneous background medium. Results indicate that both the shape variation and dielectric constant contribute to the scattered EM Doppler spectrum. To model the effect of a cylinder beneath an acoustically excited half-space, a new analytical solution is presented for EM scattering from a cylinder beneath a slightly rough surface. The solution is achieved by using plane-wave expansion of the fields and an iterative technique to account for the multiple interactions between the cylinder and rough surface. Following a similar procedure, a novel solution for elastic-wave scattering from a solid cylinder embedded in a solid half-space is developed and used to calculate the surface displacement. Simulations indicate that only a finite range of spatial surface frequencies, corresponding to surface roughness on the order of the EM wavelength; affect the EM scattering from buried objects and suggest that object detection can be improved if the acoustic excitation induces surface roughness outside this range. To extend the study to non-canonical scenarios, a novel numerical approach is introduced in which time-varying impedance boundary conditions (IBCs) are used in conjunction with the method of moments (MoM) to model the EM scattering from vibrating metallic objects of arbitrary shape. It is shown that the standard IBC provides a first

  8. 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

  9. Nucleic acid detection system and method for detecting influenza

    DOEpatents

    Cai, Hong; Song, Jian

    2015-03-17

    The invention provides a rapid, sensitive and specific nucleic acid detection system which utilizes isothermal nucleic acid amplification in combination with a lateral flow chromatographic device, or DNA dipstick, for DNA-hybridization detection. The system of the invention requires no complex instrumentation or electronic hardware, and provides a low cost nucleic acid detection system suitable for highly sensitive pathogen detection. Hybridization to single-stranded DNA amplification products using the system of the invention provides a sensitive and specific means by which assays can be multiplexed for the detection of multiple target sequences.

  10. Association and dissociation between detection and discrimination of objects of expertise: Evidence from visual search.

    PubMed

    Golan, Tal; Bentin, Shlomo; DeGutis, Joseph M; Robertson, Lynn C; Harel, Assaf

    2014-02-01

    Expertise in face recognition is characterized by high proficiency in distinguishing between individual faces. However, faces also enjoy an advantage at the early stage of basic-level detection, as demonstrated by efficient visual search for faces among nonface objects. In the present study, we asked (1) whether the face advantage in detection is a unique signature of face expertise, or whether it generalizes to other objects of expertise, and (2) whether expertise in face detection is intrinsically linked to expertise in face individuation. We compared how groups with varying degrees of object and face expertise (typical adults, developmental prosopagnosics [DP], and car experts) search for objects within and outside their domains of expertise (faces, cars, airplanes, and butterflies) among a variable set of object distractors. Across all three groups, search efficiency (indexed by reaction time slopes) was higher for faces and airplanes than for cars and butterflies. Notably, the search slope for car targets was considerably shallower in the car experts than in nonexperts. Although the mean face slope was slightly steeper among the DPs than in the other two groups, most of the DPs' search slopes were well within the normative range. This pattern of results suggests that expertise in object detection is indeed associated with expertise at the subordinate level, that it is not specific to faces, and that the two types of expertise are distinct facilities. We discuss the potential role of experience in bridging between low-level discriminative features and high-level naturalistic categories.

  11. An architecture for object-oriented intelligent control of power systems in space

    NASA Technical Reports Server (NTRS)

    Holmquist, Sven G.; Jayaram, Prakash; Jansen, Ben H.

    1993-01-01

    A control system for autonomous distribution and control of electrical power during space missions is being developed. This system should free the astronauts from localizing faults and reconfiguring loads if problems with the power distribution and generation components occur. The control system uses an object-oriented simulation model of the power system and first principle knowledge to detect, identify, and isolate faults. Each power system component is represented as a separate object with knowledge of its normal behavior. The reasoning process takes place at three different levels of abstraction: the Physical Component Model (PCM) level, the Electrical Equivalent Model (EEM) level, and the Functional System Model (FSM) level, with the PCM the lowest level of abstraction and the FSM the highest. At the EEM level the power system components are reasoned about as their electrical equivalents, e.g, a resistive load is thought of as a resistor. However, at the PCM level detailed knowledge about the component's specific characteristics is taken into account. The FSM level models the system at the subsystem level, a level appropriate for reconfiguration and scheduling. The control system operates in two modes, a reactive and a proactive mode, simultaneously. In the reactive mode the control system receives measurement data from the power system and compares these values with values determined through simulation to detect the existence of a fault. The nature of the fault is then identified through a model-based reasoning process using mainly the EEM. Compound component models are constructed at the EEM level and used in the fault identification process. In the proactive mode the reasoning takes place at the PCM level. Individual components determine their future health status using a physical model and measured historical data. In case changes in the health status seem imminent the component warns the control system about its impending failure. The fault isolation

  12. Embedded object concept with a telepresence robot system

    NASA Astrophysics Data System (ADS)

    Vallius, Tero; Röning, Juha

    2005-10-01

    This paper presents the Embedded Object Concept (EOC) and a telepresence robot system which is a test case for the EOC. The EOC utilizes common object-oriented methods used in software by applying them to combined Lego-like software-hardware entities. These entities represent objects in object-oriented design methods, and they are the building blocks of embedded systems. The goal of the EOC is to make the designing of embedded systems faster and easier. This concept enables people without comprehensive knowledge in electronics design to create new embedded systems, and for experts it shortens the design time of new embedded systems. We present the current status of the EOC, including two generations of embedded objects named Atomi objects. The first generation of the Atomi objects has been tested with different applications, and found to be functional, but not optimal. The second generation aims to correct the issues found with the first generation, and it is being tested in a relatively complex test case. The test case is a telepresence robot consisting of a two wheeled human height robot and its computer counter part. The robot has been constructed using incremental device development, which is made possible by the architecture of the EOC. The robot contains video and audio exchange capability, and a controlling and balancing system for driving with two wheels. The robot is built in two versions, the first consisting of a PDA device and Atomi objects, and the second consisting of only Atomi objects. The robot is currently incomplete, but for the most part it has been successfully tested.

  13. Active terahertz wave imaging system for detecting hidden objects

    NASA Astrophysics Data System (ADS)

    Gan, Yuner; Liu, Ming; Zhao, Yuejin

    2016-11-01

    Terahertz wave can penetrate the common dielectric materials such as clothing, cardboard boxes, plastics and so on. Besides, the low photon energy and non-ionizing characteristic of the terahertz wave are especially suitable for the safety inspection of the human body. Terahertz imaging technology has a tremendous potential in the field of security inspection such as stations, airports and other public places. Terahertz wave imaging systems are divided into two categories: active terahertz imaging systems and passive terahertz imaging systems. So far, most terahertz imaging systems work at point to point mechanical scan pattern with the method of passive imaging. The imaging results of passive imaging tend to have low contrast and the image is not clear enough. This paper designs and implements an active terahertz wave imaging system combining terahertz wave transmitting and receiving with a Cassegrain antenna. The terahertz wave at the frequency of 94GHz is created by impact ionization avalanche transit time (IMPATT) diode, focused on the feed element for Cassegrain antenna by high density polyethylene (HDPE) lens, and transmitted to the human body by Cassegrain antenna. The reflected terahertz wave goes the same way it was emitted back to the feed element for Cassegrain antenna, focused on the horn antenna of detector by another high density polyethylene lens. The scanning method is the use of two-dimensional planar mirror, one responsible for horizontal scanning, and another responsible for vertical scanning. Our system can achieve a clear human body image, has better sensitivity and resolution than passive imaging system, and costs much lower than other active imaging system in the meantime.

  14. 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

  15. 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

  16. Buried nonmetallic object detection using bistatic ground penetrating radar with variable antenna elevation angle and height

    NASA Astrophysics Data System (ADS)

    Zhang, Yu; Orfeo, Dan; Burns, Dylan; Miller, Jonathan; Huston, Dryver; Xia, Tian

    2017-04-01

    Ground penetrating radar (GPR) has been shown to be an effective device for detecting buried objects that have little or no metal content, such as plastic, ceramic, and concrete pipes. In this paper, buried non-metallic object detection is evaluated for different antenna elevation angles and heights using a bistatic air-launched GPR. Due to the large standoff distance between antennas and the ground surface, the air-launched GPR has larger spreading loss than the hand-held GPR and vehicle-mounted GPR. Moreover, nonmetallic objects may have similar dielectric property to the buried medium, which results in further difficulty for accurate detection using air-launched GPR. To study such effects, both GPR simulations and GPR laboratory experiments are performed with various setups where antennas are placed at different heights and angles. In the experiments, the test surface areas are configured with and without rocks in order to examine surface clutter effect. The experimental results evaluate the feasibility and effectiveness of bistatic air-launched GPR for detecting buried nonmetallic objects, which provide valuable insights for subsurface scanning with unmanned aerial vehicle (UAV) mounted GPR.

  17. Portable modular detection system

    DOEpatents

    Brennan, James S [Rodeo, CA; Singh, Anup [Danville, CA; Throckmorton, Daniel J [Tracy, CA; Stamps, James F [Livermore, CA

    2009-10-13

    Disclosed herein are portable and modular detection devices and systems for detecting electromagnetic radiation, such as fluorescence, from an analyte which comprises at least one optical element removably attached to at least one alignment rail. Also disclosed are modular detection devices and systems having an integrated lock-in amplifier and spatial filter and assay methods using the portable and modular detection devices.

  18. a New Object-Based Framework to Detect Shodows in High-Resolution Satellite Imagery Over Urban Areas

    NASA Astrophysics Data System (ADS)

    Tatar, N.; Saadatseresht, M.; Arefi, H.; Hadavand, A.

    2015-12-01

    In this paper a new object-based framework to detect shadow areas in high resolution satellite images is proposed. To produce shadow map in pixel level state of the art supervised machine learning algorithms are employed. Automatic ground truth generation based on Otsu thresholding on shadow and non-shadow indices is used to train the classifiers. It is followed by segmenting the image scene and create image objects. To detect shadow objects, a majority voting on pixel-based shadow detection result is designed. GeoEye-1 multi-spectral image over an urban area in Qom city of Iran is used in the experiments. Results shows the superiority of our proposed method over traditional pixel-based, visually and quantitatively.

  19. Objective response detection in an electroencephalogram during somatosensory stimulation.

    PubMed

    Simpson, D M; Tierra-Criollo, C J; Leite, R T; Zayen, E J; Infantosi, A F

    2000-06-01

    Techniques for objective response detection aim to identify the presence of evoked potentials based purely on statistical principles. They have been shown to be potentially more sensitive than the conventional approach of subjective evaluation by experienced clinicians and could be of great clinical use. Three such techniques to detect changes in an electroencephalogram (EEG) synchronous with the stimuli, namely, magnitude-squared coherence (MSC), the phase-synchrony measure (PSM) and the spectral F test (SFT) were applied to EEG signals of 12 normal subjects under conventional somatosensory pulse stimulation to the tibial nerve. The SFT, which uses only the power spectrum, showed the poorest performance, while the PSM, based only on the phase spectrum, gave results almost as good as those of the MSC, which uses both phase and power spectra. With the latter two techniques, stimulus responses were evident in the frequency range of 20-80 Hz in all subjects after 200 stimuli (5 Hz stimulus frequency), whereas for visual recognition at least 500 stimuli are usually applied. Based on these results and on simulations, the phase-based techniques appear promising for the automated detection and monitoring of somatosensory evoked potentials.

  20. 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.

  1. Object Detection from MMS Imagery Using Deep Learning for Generation of Road Orthophotos

    NASA Astrophysics Data System (ADS)

    Li, Y.; Sakamoto, M.; Shinohara, T.; Satoh, T.

    2018-05-01

    In recent years, extensive research has been conducted to automatically generate high-accuracy and high-precision road orthophotos using images and laser point cloud data acquired from a mobile mapping system (MMS). However, it is necessary to mask out non-road objects such as vehicles, bicycles, pedestrians and their shadows in MMS images in order to eliminate erroneous textures from the road orthophoto. Hence, we proposed a novel vehicle and its shadow detection model based on Faster R-CNN for automatically and accurately detecting the regions of vehicles and their shadows from MMS images. The experimental results show that the maximum recall of the proposed model was high - 0.963 (intersection-over-union > 0.7) - and the model could identify the regions of vehicles and their shadows accurately and robustly from MMS images, even when they contain varied vehicles, different shadow directions, and partial occlusions. Furthermore, it was confirmed that the quality of road orthophoto generated using vehicle and its shadow masks was significantly improved as compared to those generated using no masks or using vehicle masks only.

  2. Microcontroller based driver alertness detection systems to detect drowsiness

    NASA Astrophysics Data System (ADS)

    Adenin, Hasibah; Zahari, Rahimi; Lim, Tiong Hoo

    2018-04-01

    The advancement of embedded system for detecting and preventing drowsiness in a vehicle is a major challenge for road traffic accident systems. To prevent drowsiness while driving, it is necessary to have an alert system that can detect a decline in driver concentration and send a signal to the driver. Studies have shown that traffc accidents usually occur when the driver is distracted while driving. In this paper, we have reviewed a number of detection systems to monitor the concentration of a car driver and propose a portable Driver Alertness Detection System (DADS) to determine the level of concentration of the driver based on pixelated coloration detection technique using facial recognition. A portable camera will be placed at the front visor to capture facial expression and the eye activities. We evaluate DADS using 26 participants and have achieved 100% detection rate with good lighting condition and a low detection rate at night.

  3. Foreign object detection via texture recognition and a neural classifier

    NASA Astrophysics Data System (ADS)

    Patel, Devesh; Hannah, I.; Davies, E. R.

    1993-10-01

    It is rate to find pieces of stone, wood, metal, or glass in food packets, but when they occur, these foreign objects (FOs) cause distress to the consumer and concern to the manufacturer. Using x-ray imaging to detect FOs within food bags, hard contaminants such as stone or metal appear darker, whereas soft contaminants such as wood or rubber appear slightly lighter than the food substrate. In this paper we concentrate on the detection of soft contaminants such as small pieces of wood in bags of frozen corn kernels. Convolution masks are used to generate textural features which are then classified into corresponding homogeneous regions on the image using an artificial neural network (ANN) classifier. The separate ANN outputs are combined using a majority operator, and region discrepancies are removed by a median filter. Comparisons with classical classifiers showed the ANN approach to have the best overall combination of characteristics for our particular problem. The detected boundaries are in good agreement with the visually perceived segmentations.

  4. Monocular correspondence detection for symmetrical objects by template matching

    NASA Astrophysics Data System (ADS)

    Vilmar, G.; Besslich, Philipp W., Jr.

    1990-09-01

    We describe a possibility to reconstruct 3-D information from a single view of an 3-D bilateral symmetric object. The symmetry assumption allows us to obtain a " second view" from a different viewpoint by a simple reflection of the monocular image. Therefore we have to solve the correspondence problem in a special case where known feature-based or area-based binocular approaches fail. In principle our approach is based on a frequency domain template matching of the features on the epipolar lines. During a training period our system " learns" the assignment of correspondence models to image features. The object shape is interpolated when no template matches to the image features. This fact is an important advantage of this methodology because no " real world" image holds the symmetry assumption perfectly. To simplify the training process we used single views on human faces (e. g. passport photos) but our system is trainable on any other kind of objects.

  5. Concept of electro-optical sensor module for sniper detection system

    NASA Astrophysics Data System (ADS)

    Trzaskawka, Piotr; Dulski, Rafal; Kastek, Mariusz

    2010-10-01

    The paper presents an initial concept of the electro-optical sensor unit for sniper detection purposes. This unit, comprising of thermal and daylight cameras, can operate as a standalone device but its primary application is a multi-sensor sniper and shot detection system. Being a part of a larger system it should contribute to greater overall system efficiency and lower false alarm rate thanks to data and sensor fusion techniques. Additionally, it is expected to provide some pre-shot detection capabilities. Generally acoustic (or radar) systems used for shot detection offer only "after-the-shot" information and they cannot prevent enemy attack, which in case of a skilled sniper opponent usually means trouble. The passive imaging sensors presented in this paper, together with active systems detecting pointed optics, are capable of detecting specific shooter signatures or at least the presence of suspected objects in the vicinity. The proposed sensor unit use thermal camera as a primary sniper and shot detection tool. The basic camera parameters such as focal plane array size and type, focal length and aperture were chosen on the basis of assumed tactical characteristics of the system (mainly detection range) and current technology level. In order to provide costeffective solution the commercially available daylight camera modules and infrared focal plane arrays were tested, including fast cooled infrared array modules capable of 1000 fps image acquisition rate. The daylight camera operates as a support, providing corresponding visual image, easier to comprehend for a human operator. The initial assumptions concerning sensor operation were verified during laboratory and field test and some example shot recording sequences are presented.

  6. A Fully Automated Method to Detect and Segment a Manufactured Object in an Underwater Color Image

    NASA Astrophysics Data System (ADS)

    Barat, Christian; Phlypo, Ronald

    2010-12-01

    We propose a fully automated active contours-based method for the detection and the segmentation of a moored manufactured object in an underwater image. Detection of objects in underwater images is difficult due to the variable lighting conditions and shadows on the object. The proposed technique is based on the information contained in the color maps and uses the visual attention method, combined with a statistical approach for the detection and an active contour for the segmentation of the object to overcome the above problems. In the classical active contour method the region descriptor is fixed and the convergence of the method depends on the initialization. With our approach, this dependence is overcome with an initialization using the visual attention results and a criterion to select the best region descriptor. This approach improves the convergence and the processing time while providing the advantages of a fully automated method.

  7. Region Based CNN for Foreign Object Debris Detection on Airfield Pavement.

    PubMed

    Cao, Xiaoguang; Wang, Peng; Meng, Cai; Bai, Xiangzhi; Gong, Guoping; Liu, Miaoming; Qi, Jun

    2018-03-01

    In this paper, a novel algorithm based on convolutional neural network (CNN) is proposed to detect foreign object debris (FOD) based on optical imaging sensors. It contains two modules, the improved region proposal network (RPN) and spatial transformer network (STN) based CNN classifier. In the improved RPN, some extra select rules are designed and deployed to generate high quality candidates with fewer numbers. Moreover, the efficiency of CNN detector is significantly improved by introducing STN layer. Compared to faster R-CNN and single shot multiBox detector (SSD), the proposed algorithm achieves better result for FOD detection on airfield pavement in the experiment.

  8. Object-based change detection: dimension of damage in residential areas of Abu Suruj, Sudan

    NASA Astrophysics Data System (ADS)

    Demharter, Timo; Michel, Ulrich; Ehlers, Manfred; Reinartz, Peter

    2011-11-01

    Given the importance of Change Detection, especially in the field of crisis management, this paper discusses the advantage of object-based Change Detection. This project and the used methods give an opportunity to coordinate relief actions strategically. The principal objective of this project was to develop an algorithm which allows to detect rapidly damaged and destroyed buildings in the area of Abu Suruj. This Sudanese village is located in West-Darfur and has become the victim of civil war. The software eCognition Developer was used to per-form an object-based Change Detection on two panchromatic Quickbird 2 images from two different time slots. The first image shows the area before, the second image shows the area after the massacres in this region. Seeking a classification for the huts of the Sudanese town Abu Suruj was reached by first segmenting the huts and then classifying them on the basis of geo-metrical and brightness-related values. The huts were classified as "new", "destroyed" and "preserved" with the help of a automated algorithm. Finally the results were presented in the form of a map which displays the different conditions of the huts. The accuracy of the project is validated by an accuracy assessment resulting in an Overall Classification Accuracy of 90.50 percent. These change detection results allow aid organizations to provide quick and efficient help where it is needed the most.

  9. System for controlled acoustic rotation of objects

    NASA Technical Reports Server (NTRS)

    Barmatz, M. B. (Inventor)

    1983-01-01

    A system is described for use with acoustically levitated objects, which enables close control of rotation of the object. One system includes transducers that propagate acoustic waves along the three dimensions (X, Y, Z) of a chamber of rectangular cross section. Each transducers generates one wave which is resonant to a corresponding chamber dimension to acoustically levitate an object, and additional higher frequency resonant wavelengths for controlling rotation of the object. The three chamber dimensions and the corresponding three levitation modes (resonant wavelengths) are all different, to avoid degeneracy, or interference, of waves with one another, that could have an effect on object rotation. Only the higher frequencies, with pairs of them having the same wavelength, are utilized to control rotation, so that rotation is controlled independently of levitation and about any arbitrarily chosen axis.

  10. Parallel Flux Tensor Analysis for Efficient Moving Object Detection

    DTIC Science & Technology

    2011-07-01

    computing as well as parallelization to enable real time performance in analyzing complex video [3, 4 ]. There are a number of challenging computer vision... 4 . TITLE AND SUBTITLE Parallel Flux Tensor Analysis for Efficient Moving Object Detection 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT...We use the trace of the flux tensor matrix, referred to as Tr JF , that is defined below, Tr JF = ∫ Ω W (x− y)(I2xt(y) + I2yt(y) + I2tt(y))dy ( 4 ) as

  11. Power System Information Delivering System Based on Distributed Object

    NASA Astrophysics Data System (ADS)

    Tanaka, Tatsuji; Tsuchiya, Takehiko; Tamura, Setsuo; Seki, Tomomichi; Kubota, Kenji

    In recent years, improvement in computer performance and development of computer network technology or the distributed information processing technology has a remarkable thing. Moreover, the deregulation is starting and will be spreading in the electric power industry in Japan. Consequently, power suppliers are required to supply low cost power with high quality services to customers. Corresponding to these movements the authors have been proposed SCOPE (System Configuration Of PowEr control system) architecture for distributed EMS/SCADA (Energy Management Systems / Supervisory Control and Data Acquisition) system based on distributed object technology, which offers the flexibility and expandability adapting those movements. In this paper, the authors introduce a prototype of the power system information delivering system, which was developed based on SCOPE architecture. This paper describes the architecture and the evaluation results of this prototype system. The power system information delivering system supplies useful power systems information such as electric power failures to the customers using Internet and distributed object technology. This system is new type of SCADA system which monitors failure of power transmission system and power distribution system with geographic information integrated way.

  12. The detection of objects in a turbid underwater medium using orbital angular momentum (OAM)

    NASA Astrophysics Data System (ADS)

    Cochenour, Brandon; Rodgers, Lila; Laux, Alan; Mullen, Linda; Morgan, Kaitlyn; Miller, Jerome K.; Johnson, Eric G.

    2017-05-01

    We present an investigation of the optical property of orbital angular momentum (OAM) for use in the detection of objects obscured by a turbid underwater channel. In our experiment, a target is illuminated by a Gaussian beam. An optical vortex is formed by passing the object-reflected and backscattered light through a diffractive spiral phase plate at the receiver, which allows for the spatial separation of coherent and non-coherent light. This provides a method for discriminating target from environment. Initial laboratory results show that the ballistic target return can be detected 2-3 orders of magnitude below the backscatter clutter level. Furthermore, the detection of this coherent component is accomplished with the use of a complicated optical heterodyning scheme. The results suggest new optical sensing techniques for underwater imaging or LIDAR.

  13. Infrared detection, recognition and identification of handheld objects

    NASA Astrophysics Data System (ADS)

    Adomeit, Uwe

    2012-10-01

    A main criterion for comparison and selection of thermal imagers for military applications is their nominal range performance. This nominal range performance is calculated for a defined task and standardized target and environmental conditions. The only standardization available to date is STANAG 4347. The target defined there is based on a main battle tank in front view. Because of modified military requirements, this target is no longer up-to-date. Today, different topics of interest are of interest, especially differentiation between friend and foe and identification of humans. There is no direct way to differentiate between friend and foe in asymmetric scenarios, but one clue can be that someone is carrying a weapon. This clue can be transformed in the observer tasks detection: a person is carrying or is not carrying an object, recognition: the object is a long / medium / short range weapon or civil equipment and identification: the object can be named (e. g. AK-47, M-4, G36, RPG7, Axe, Shovel etc.). These tasks can be assessed experimentally and from the results of such an assessment, a standard target for handheld objects may be derived. For a first assessment, a human carrying 13 different handheld objects in front of his chest was recorded at four different ranges with an IR-dual-band camera. From the recorded data, a perception experiment was prepared. It was conducted with 17 observers in a 13-alternative forced choice, unlimited observation time arrangement. The results of the test together with Minimum Temperature Difference Perceived measurements of the camera and temperature difference and critical dimension derived from the recorded imagery allowed defining a first standard target according to the above tasks. This standard target consist of 2.5 / 3.5 / 5 DRI line pairs on target, 0.24 m critical size and 1 K temperature difference. The values are preliminary and have to be refined in the future. Necessary are different aspect angles, different

  14. Generalized Detectability for Discrete Event Systems

    PubMed Central

    Shu, Shaolong; Lin, Feng

    2011-01-01

    In our previous work, we investigated detectability of discrete event systems, which is defined as the ability to determine the current and subsequent states of a system based on observation. For different applications, we defined four types of detectabilities: (weak) detectability, strong detectability, (weak) periodic detectability, and strong periodic detectability. In this paper, we extend our results in three aspects. (1) We extend detectability from deterministic systems to nondeterministic systems. Such a generalization is necessary because there are many systems that need to be modeled as nondeterministic discrete event systems. (2) We develop polynomial algorithms to check strong detectability. The previous algorithms are based on observer whose construction is of exponential complexity, while the new algorithms are based on a new automaton called detector. (3) We extend detectability to D-detectability. While detectability requires determining the exact state of a system, D-detectability relaxes this requirement by asking only to distinguish certain pairs of states. With these extensions, the theory on detectability of discrete event systems becomes more applicable in solving many practical problems. PMID:21691432

  15. Moving object detection in top-view aerial videos improved by image stacking

    NASA Astrophysics Data System (ADS)

    Teutsch, Michael; Krüger, Wolfgang; Beyerer, Jürgen

    2017-08-01

    Image stacking is a well-known method that is used to improve the quality of images in video data. A set of consecutive images is aligned by applying image registration and warping. In the resulting image stack, each pixel has redundant information about its intensity value. This redundant information can be used to suppress image noise, resharpen blurry images, or even enhance the spatial image resolution as done in super-resolution. Small moving objects in the videos usually get blurred or distorted by image stacking and thus need to be handled explicitly. We use image stacking in an innovative way: image registration is applied to small moving objects only, and image warping blurs the stationary background that surrounds the moving objects. Our video data are coming from a small fixed-wing unmanned aerial vehicle (UAV) that acquires top-view gray-value images of urban scenes. Moving objects are mainly cars but also other vehicles such as motorcycles. The resulting images, after applying our proposed image stacking approach, are used to improve baseline algorithms for vehicle detection and segmentation. We improve precision and recall by up to 0.011, which corresponds to a reduction of the number of false positive and false negative detections by more than 3 per second. Furthermore, we show how our proposed image stacking approach can be implemented efficiently.

  16. Detecting sub-lunar mass compact objects toward the Local Group galaxies

    NASA Astrophysics Data System (ADS)

    Inoue, Kaiki Taro

    2018-01-01

    By monitoring a large number of stars in the Local Group galaxies, we can detect nanolensing events by sub-lunar mass compact objects (SULCOs) such as primordial black holes (PBHs) and rogue (free-floating) dwarf planets in the Milky Way halo. In contarst to microlensing by stellar-mass objects, the finite-source size effect becomes important and the lensing time duration becomes shorter (∼10 1 - 4s). Using stars with V < 26 in M33 as sources, for one-night observation, we would be able to detect 10 3 - 4 nanolensing events caused by SULCOs in the Milky Way halo with a mass of 10-9M⊙ to 10-7M⊙ for sources with S/N > 5 if SULCOs constitute all the dark matter components. Moreover, we expect 10 1 - 2 events in which bright blue stars with S/N > 100 are weakly amplified due to lensing by SULCOs with a mass range of 10-11M⊙ to 10-9M⊙ . Thus the method would open a new window on SULCOs in the Milky Way halo that would otherwise not be observable.

  17. DIAC object recognition system

    NASA Astrophysics Data System (ADS)

    Buurman, Johannes

    1992-03-01

    This paper describes the object recognition system used in an intelligent robot cell. It is used to recognize and estimate pose and orientation of parts as they enter the cell. The parts are mostly metal and consist of polyhedral and cylindrical shapes. The system uses feature-based stereo vision to acquire a wireframe of the observed part. Features are defined as straight lines and ellipses, which lead to a wireframe of straight lines and circular arcs (the latter using a new algorithm). This wireframe is compared to a number of wire frame models obtained from the CAD database. Experimental results show that image processing hardware and parallelization may add considerably to the speed of the system.

  18. The Deep Lens Survey : Real--time Optical Transient and Moving Object Detection

    NASA Astrophysics Data System (ADS)

    Becker, Andy; Wittman, David; Stubbs, Chris; Dell'Antonio, Ian; Loomba, Dinesh; Schommer, Robert; Tyson, J. Anthony; Margoniner, Vera; DLS Collaboration

    2001-12-01

    We report on the real-time optical transient program of the Deep Lens Survey (DLS). Meeting the DLS core science weak-lensing objective requires repeated visits to the same part of the sky, 20 visits for 63 sub-fields in 4 filters, on a 4-m telescope. These data are reduced in real-time, and differenced against each other on all available timescales. Our observing strategy is optimized to allow sensitivity to transients on several minute, one day, one month, and one year timescales. The depth of the survey allows us to detect and classify both moving and stationary transients down to ~ 25th magnitude, a relatively unconstrained region of astronomical variability space. All transients and moving objects, including asteroids, Kuiper belt (or trans-Neptunian) objects, variable stars, supernovae, 'unknown' bursts with no apparent host, orphan gamma-ray burst afterglows, as well as airplanes, are posted on the web in real-time for use by the community. We emphasize our sensitivity to detect and respond in real-time to orphan afterglows of gamma-ray bursts, and present one candidate orphan in the field of Abell 1836. See http://dls.bell-labs.com/transients.html.

  19. Parallel object-oriented decision tree system

    DOEpatents

    Kamath,; Chandrika, Cantu-Paz [Dublin, CA; Erick, [Oakland, CA

    2006-02-28

    A data mining decision tree system that uncovers patterns, associations, anomalies, and other statistically significant structures in data by reading and displaying data files, extracting relevant features for each of the objects, and using a method of recognizing patterns among the objects based upon object features through a decision tree that reads the data, sorts the data if necessary, determines the best manner to split the data into subsets according to some criterion, and splits the data.

  20. 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.

  1. Reengineering legacy software to object-oriented systems

    NASA Technical Reports Server (NTRS)

    Pitman, C.; Braley, D.; Fridge, E.; Plumb, A.; Izygon, M.; Mears, B.

    1994-01-01

    NASA has a legacy of complex software systems that are becoming increasingly expensive to maintain. Reengineering is one approach to modemizing these systems. Object-oriented technology, other modem software engineering principles, and automated tools can be used to reengineer the systems and will help to keep maintenance costs of the modemized systems down. The Software Technology Branch at the NASA/Johnson Space Center has been developing and testing reengineering methods and tools for several years. The Software Technology Branch is currently providing training and consulting support to several large reengineering projects at JSC, including the Reusable Objects Software Environment (ROSE) project, which is reengineering the flight analysis and design system (over 2 million lines of FORTRAN code) into object-oriented C++. Many important lessons have been learned during the past years; one of these is that the design must never be allowed to diverge from the code during maintenance and enhancement. Future work on open, integrated environments to support reengineering is being actively planned.

  2. 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

  3. 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 ...

  4. Investigation of the relative orientation of the system of optical sensors to monitor the technosphere objects

    NASA Astrophysics Data System (ADS)

    Petrochenko, Andrey; Konyakhin, Igor

    2017-06-01

    In connection with the development of robotics have become increasingly popular variety of three-dimensional reconstruction of the system mapping and image-set received from the optical sensors. The main objective of technical and robot vision is the detection, tracking and classification of objects of the space in which these systems and robots operate [15,16,18]. Two-dimensional images sometimes don't contain sufficient information to address those or other problems: the construction of the map of the surrounding area for a route; object identification, tracking their relative position and movement; selection of objects and their attributes to complement the knowledge base. Three-dimensional reconstruction of the surrounding space allows you to obtain information on the relative positions of objects, their shape, surface texture. Systems, providing training on the basis of three-dimensional reconstruction of the results of the comparison can produce two-dimensional images of three-dimensional model that allows for the recognition of volume objects on flat images. The problem of the relative orientation of industrial robots with the ability to build threedimensional scenes of controlled surfaces is becoming actual nowadays.

  5. Detection of Illicit Drugs with the EURITRACK System

    NASA Astrophysics Data System (ADS)

    Perot, B.; Carasco, C.; Valkovic, V.; Sudac, D.; Franulovic, A.

    2009-03-01

    The EURopean Illicit TRAfficking Countermeasures Kit (EURITRACK) inspection system has been developed within the 6th EU Framework Program to complement X-ray scanners in the detection of explosives and other illicit materials hidden in cargo containers. Gamma rays are produced inside the cargo materials by 14 MeV tagged neutron beams, which yields information about the chemical composition of the transported goods. In the beginning of year 2007, the EURITRACK system was implemented in the Seaport of Rijeka, Croatia, primarily to carry out a demonstration using real containers to conduct a series of detection tests. This article reports tests performed with real samples of illicit drugs hidden in a metallic cargo with an average density of 0.2 g/cm3. Heroin and cocaine have been distinguished from benign substances based on their chemical composition. Marijuana, which chemical composition is similar to benign materials, cannot be distinguished from common organic goods. However, the detection of an unexpected organic substance inside the metallic cargo indicates that a suspicious object has been hidden in the container.

  6. Investigation of an EMI sensor for detection of large metallic objects in the presence of metallic clutter

    NASA Astrophysics Data System (ADS)

    Black, Christopher; McMichael, Ian; Riggs, Lloyd

    2005-06-01

    Electromagnetic induction (EMI) sensors and magnetometers have successfully detected surface laid, buried, and visually obscured metallic objects. Potential military activities could require detection of these objects at some distance from a moving vehicle in the presence of metallic clutter. Results show that existing EMI sensors have limited range capabilities and suffer from false alarms due to clutter. This paper presents results of an investigation of an EMI sensor designed for detecting large metallic objects on a moving platform in a high clutter environment. The sensor was developed by the U.S. Army RDECOM CERDEC NVESD in conjunction with the Johns Hopkins University Applied Physics Laboratory.

  7. An approach to detecting deliberately introduced defects and micro-defects in 3D printed objects

    NASA Astrophysics Data System (ADS)

    Straub, Jeremy

    2017-05-01

    In prior work, Zeltmann, et al. demonstrated the negative impact that can be created by defects of various sizes in 3D printed objects. These defects may make the object unsuitable for its application or even present a hazard, if the object is being used for a safety-critical application. With the uses of 3D printing proliferating and consumer access to printers increasing, the desire of a nefarious individual or group to subvert the desired printing quality and safety attributes of a printer or printed object must be considered. Several different approaches to subversion may exist. Attackers may physically impair the functionality of the printer or launch a cyber-attack. Detecting introduced defects, from either attack, is critical to maintaining public trust in 3D printed objects and the technology. This paper presents an alternate approach. It applies a quality assurance technology based on visible light sensing to this challenge and assesses its capability for detecting introduced defects of multiple sizes.

  8. Performance bounds for matched field processing in subsurface object detection applications

    NASA Astrophysics Data System (ADS)

    Sahin, Adnan; Miller, Eric L.

    1998-09-01

    In recent years there has been considerable interest in the use of ground penetrating radar (GPR) for the non-invasive detection and localization of buried objects. In a previous work, we have considered the use of high resolution array processing methods for solving these problems for measurement geometries in which an array of electromagnetic receivers observes the fields scattered by the subsurface targets in response to a plane wave illumination. Our approach uses the MUSIC algorithm in a matched field processing (MFP) scheme to determine both the range and the bearing of the objects. In this paper we derive the Cramer-Rao bounds (CRB) for this MUSIC-based approach analytically. Analysis of the theoretical CRB has shown that there exists an optimum inter-element spacing of array elements for which the CRB is minimum. Furthermore, the optimum inter-element spacing minimizing CRB is smaller than the conventional half wavelength criterion. The theoretical bounds are then verified for two estimators using Monte-Carlo simulations. The first estimator is the MUSIC-based MFP and the second one is the maximum likelihood based MFP. The two approaches differ in the cost functions they optimize. We observe that Monte-Carlo simulated error variances always lie above the values established by CRB. Finally, we evaluate the performance of our MUSIC-based algorithm in the presence of model mismatches. Since the detection algorithm strongly depends on the model used, we have tested the performance of the algorithm when the object radius used in the model is different from the true radius. This analysis reveals that the algorithm is still capable of localizing the objects with a bias depending on the degree of mismatch.

  9. A Multimodal Emotion Detection System during Human-Robot Interaction

    PubMed Central

    Alonso-Martín, Fernando; Malfaz, María; Sequeira, João; Gorostiza, Javier F.; Salichs, Miguel A.

    2013-01-01

    In this paper, a multimodal user-emotion detection system for social robots is presented. This system is intended to be used during human–robot interaction, and it is integrated as part of the overall interaction system of the robot: the Robotics Dialog System (RDS). Two modes are used to detect emotions: the voice and face expression analysis. In order to analyze the voice of the user, a new component has been developed: Gender and Emotion Voice Analysis (GEVA), which is written using the Chuck language. For emotion detection in facial expressions, the system, Gender and Emotion Facial Analysis (GEFA), has been also developed. This last system integrates two third-party solutions: Sophisticated High-speed Object Recognition Engine (SHORE) and Computer Expression Recognition Toolbox (CERT). Once these new components (GEVA and GEFA) give their results, a decision rule is applied in order to combine the information given by both of them. The result of this rule, the detected emotion, is integrated into the dialog system through communicative acts. Hence, each communicative act gives, among other things, the detected emotion of the user to the RDS so it can adapt its strategy in order to get a greater satisfaction degree during the human–robot dialog. Each of the new components, GEVA and GEFA, can also be used individually. Moreover, they are integrated with the robotic control platform ROS (Robot Operating System). Several experiments with real users were performed to determine the accuracy of each component and to set the final decision rule. The results obtained from applying this decision rule in these experiments show a high success rate in automatic user emotion recognition, improving the results given by the two information channels (audio and visual) separately. PMID:24240598

  10. Evaluation of a miniature microscope objective designed for fluorescence array microscopy detection of Mycobacterium tuberculosis.

    PubMed

    McCall, Brian; Olsen, Randall J; Nelles, Nicole J; Williams, Dawn L; Jackson, Kevin; Richards-Kortum, Rebecca; Graviss, Edward A; Tkaczyk, Tomasz S

    2014-03-01

    A prototype miniature objective that was designed for a point-of-care diagnostic array microscope for detection of Mycobacterium tuberculosis and previously fabricated and presented in a proof of concept is evaluated for its effectiveness in detecting acid-fast bacteria. To evaluate the ability of the microscope to resolve submicron features and details in the image of acid-fast microorganisms stained with a fluorescent dye, and to evaluate the accuracy of clinical diagnoses made with digital images acquired with the objective. The lens prescription data for the microscope design are presented. A test platform is built by combining parts of a standard microscope, a prototype objective, and a digital single-lens reflex camera. Counts of acid-fast bacteria made with the prototype objective are compared to counts obtained with a standard microscope over matched fields of view. Two sets of 20 smears, positive and negative, are diagnosed by 2 pathologists as sputum smear positive or sputum smear negative, using both a standard clinical microscope and the prototype objective under evaluation. The results are compared to a reference diagnosis of the same sample. More bacteria are counted in matched fields of view in digital images taken with the prototype objective than with the standard clinical microscope. All diagnostic results are found to be highly concordant. An array microscope built with this miniature lens design will be able to detect M tuberculosis with high sensitivity and specificity.

  11. Design of tracking and detecting lens system by diffractive optical method

    NASA Astrophysics Data System (ADS)

    Yang, Jiang; Qi, Bo; Ren, Ge; Zhou, Jianwei

    2016-10-01

    Many target-tracking applications require an optical system to acquire the target for tracking and identification. This paper describes a new detecting optical system that can provide automatic flying object detecting, tracking and measuring in visible band. The main feature of the detecting lens system is the combination of diffractive optics with traditional lens design by a technique was invented by Schupmann. Diffractive lens has great potential for developing the larger aperture and lightweight lens. First, the optical system scheme was described. Then the Schupmann achromatic principle with diffractive lens and corrective optics is introduced. According to the technical features and requirements of the optical imaging system for detecting and tracking, we designed a lens system with flat surface Fresnel lens and cancels the optical system chromatic aberration by another flat surface Fresnel lens with effective focal length of 1980mm, an F-Number of F/9.9 and a field of view of 2ωω = 14.2', spatial resolution of 46 lp/mm and a working wavelength range of 0.6 0.85um. At last, the system is compact and easy to fabricate and assembly, the diffuse spot size and MTF function and other analysis provide good performance.

  12. A telepresence robot system realized by embedded object concept

    NASA Astrophysics Data System (ADS)

    Vallius, Tero; Röning, Juha

    2006-10-01

    This paper presents the Embedded Object Concept (EOC) and a telepresence robot system which is a test case for the EOC. The EOC utilizes common object-oriented methods used in software by applying them to combined Lego-like software-hardware entities. These entities represent objects in object-oriented design methods, and they are the building blocks of embedded systems. The goal of the EOC is to make the designing embedded systems faster and easier. This concept enables people without comprehensive knowledge in electronics design to create new embedded systems, and for experts it shortens the design time of new embedded systems. We present the current status of a telepresence robot created with second-generation Atomi-objects, which is the name for our implementation of the embedded objects. The telepresence robot is a relatively complex test case for the EOC. The robot has been constructed using incremental device development, which is made possible by the architecture of the EOC. The robot contains video and audio exchange capability and a controlling system for driving with two wheels. The robot is built in two versions, the first consisting of a PC device and Atomi-objects, and the second consisting of only Atomi-objects. The robot is currently incomplete, but most of it has been successfully tested.

  13. Region Based CNN for Foreign Object Debris Detection on Airfield Pavement

    PubMed Central

    Cao, Xiaoguang; Wang, Peng; Meng, Cai; Gong, Guoping; Liu, Miaoming; Qi, Jun

    2018-01-01

    In this paper, a novel algorithm based on convolutional neural network (CNN) is proposed to detect foreign object debris (FOD) based on optical imaging sensors. It contains two modules, the improved region proposal network (RPN) and spatial transformer network (STN) based CNN classifier. In the improved RPN, some extra select rules are designed and deployed to generate high quality candidates with fewer numbers. Moreover, the efficiency of CNN detector is significantly improved by introducing STN layer. Compared to faster R-CNN and single shot multiBox detector (SSD), the proposed algorithm achieves better result for FOD detection on airfield pavement in the experiment. PMID:29494524

  14. 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.

  15. Open-area concealed-weapon detection system

    NASA Astrophysics Data System (ADS)

    Pati, P.; Mather, P.

    2011-06-01

    Concealed Weapon Detection (CWD) has become a significant challenge to present day security needs; individuals carrying weapons into airplanes, schools, and secured establishments are threat to public security. Although controlled screening, of people for concealed weapons, has been employed in many establishments, procedures and equipment are designed to work in restricted environments like airport passport control, military checkpoints, hospitals, school and university entrance. Furthermore, screening systems do not effectively decipher between threat and non-threat metal objects, thus leading to high rate of false alarms which can become a liability to daily operational needs of establishments. Therefore, the design and development of a new CWD system to operate in a large open area environment with large numbers of people reduced incidences of false alarms and increased location accuracy is essential.

  16. 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.

  17. Object-oriented fault tree models applied to system diagnosis

    NASA Technical Reports Server (NTRS)

    Iverson, David L.; Patterson-Hine, F. A.

    1990-01-01

    When a diagnosis system is used in a dynamic environment, such as the distributed computer system planned for use on Space Station Freedom, it must execute quickly and its knowledge base must be easily updated. Representing system knowledge as object-oriented augmented fault trees provides both features. The diagnosis system described here is based on the failure cause identification process of the diagnostic system described by Narayanan and Viswanadham. Their system has been enhanced in this implementation by replacing the knowledge base of if-then rules with an object-oriented fault tree representation. This allows the system to perform its task much faster and facilitates dynamic updating of the knowledge base in a changing diagnosis environment. Accessing the information contained in the objects is more efficient than performing a lookup operation on an indexed rule base. Additionally, the object-oriented fault trees can be easily updated to represent current system status. This paper describes the fault tree representation, the diagnosis algorithm extensions, and an example application of this system. Comparisons are made between the object-oriented fault tree knowledge structure solution and one implementation of a rule-based solution. Plans for future work on this system are also discussed.

  18. Sequential feature selection for detecting buried objects using forward looking ground penetrating radar

    NASA Astrophysics Data System (ADS)

    Shaw, Darren; Stone, Kevin; Ho, K. C.; Keller, James M.; Luke, Robert H.; Burns, Brian P.

    2016-05-01

    Forward looking ground penetrating radar (FLGPR) has the benefit of detecting objects at a significant standoff distance. The FLGPR signal is radiated over a large surface area and the radar signal return is often weak. Improving detection, especially for buried in road targets, while maintaining an acceptable false alarm rate remains to be a challenging task. Various kinds of features have been developed over the years to increase the FLGPR detection performance. This paper focuses on investigating the use of as many features as possible for detecting buried targets and uses the sequential feature selection technique to automatically choose the features that contribute most for improving performance. Experimental results using data collected at a government test site are presented.

  19. The objects of visuospatial short-term memory: Perceptual organization and change detection.

    PubMed

    Nikolova, Atanaska; Macken, Bill

    2016-01-01

    We used a colour change-detection paradigm where participants were required to remember colours of six equally spaced circles. Items were superimposed on a background so as to perceptually group them within (a) an intact ring-shaped object, (b) a physically segmented but perceptually completed ring-shaped object, or (c) a corresponding background segmented into three arc-shaped objects. A nonpredictive cue at the location of one of the circles was followed by the memory items, which in turn were followed by a test display containing a probe indicating the circle to be judged same/different. Reaction times for correct responses revealed a same-object advantage; correct responses were faster to probes on the same object as the cue than to equidistant probes on a segmented object. This same-object advantage was identical for physically and perceptually completed objects, but was only evident in reaction times, and not in accuracy measures. Not only, therefore, is it important to consider object-level perceptual organization of stimulus elements when assessing the influence of a range of factors (e.g., number and complexity of elements) in visuospatial short-term memory, but a more detailed picture of the structure of information in memory may be revealed by measuring speed as well as accuracy.

  20. The objects of visuospatial short-term memory: Perceptual organization and change detection

    PubMed Central

    Nikolova, Atanaska; Macken, Bill

    2016-01-01

    We used a colour change-detection paradigm where participants were required to remember colours of six equally spaced circles. Items were superimposed on a background so as to perceptually group them within (a) an intact ring-shaped object, (b) a physically segmented but perceptually completed ring-shaped object, or (c) a corresponding background segmented into three arc-shaped objects. A nonpredictive cue at the location of one of the circles was followed by the memory items, which in turn were followed by a test display containing a probe indicating the circle to be judged same/different. Reaction times for correct responses revealed a same-object advantage; correct responses were faster to probes on the same object as the cue than to equidistant probes on a segmented object. This same-object advantage was identical for physically and perceptually completed objects, but was only evident in reaction times, and not in accuracy measures. Not only, therefore, is it important to consider object-level perceptual organization of stimulus elements when assessing the influence of a range of factors (e.g., number and complexity of elements) in visuospatial short-term memory, but a more detailed picture of the structure of information in memory may be revealed by measuring speed as well as accuracy. PMID:26286369

  1. Digital tripwire: a small automated human detection system

    NASA Astrophysics Data System (ADS)

    Fischer, Amber D.; Redd, Emmett; Younger, A. Steven

    2009-05-01

    A low cost, lightweight, easily deployable imaging sensor that can dependably discriminate threats from other activities within its field of view and, only then, alert the distant duty officer by transmitting a visual confirmation of the threat would provide a valuable asset to modern defense. At present, current solutions suffer from a multitude of deficiencies - size, cost, power endurance, but most notably, an inability to assess an image and conclude that it contains a threat. The human attention span cannot maintain critical surveillance over banks of displays constantly conveying such images from the field. DigitalTripwire is a small, self-contained, automated human-detection system capable of running for 1-5 days on two AA batteries. To achieve such long endurance, the DigitalTripwire system utilizes an FPGA designed with sleep functionality. The system uses robust vision algorithms, such as a partially unsupervised innovative backgroundmodeling algorithm, which employ several data reduction strategies to operate in real-time, and achieve high detection rates. When it detects human activity, either mounted or dismounted, it sends an alert including images to notify the command center. In this paper, we describe the hardware and software design of the DigitalTripwire system. In addition, we provide detection and false alarm rates across several challenging data sets demonstrating the performance of the vision algorithms in autonomously analyzing the video stream and classifying moving objects into four primary categories - dismounted human, vehicle, non-human, or unknown. Performance results across several challenging data sets are provided.

  2. Luminance gradient at object borders communicates object location to the human oculomotor system.

    PubMed

    Kilpeläinen, Markku; Georgeson, Mark A

    2018-01-25

    The locations of objects in our environment constitute arguably the most important piece of information our visual system must convey to facilitate successful visually guided behaviour. However, the relevant objects are usually not point-like and do not have one unique location attribute. Relatively little is known about how the visual system represents the location of such large objects as visual processing is, both on neural and perceptual level, highly edge dominated. In this study, human observers made saccades to the centres of luminance defined squares (width 4 deg), which appeared at random locations (8 deg eccentricity). The phase structure of the square was manipulated such that the points of maximum luminance gradient at the square's edges shifted from trial to trial. The average saccade endpoints of all subjects followed those shifts in remarkable quantitative agreement. Further experiments showed that the shifts were caused by the edge manipulations, not by changes in luminance structure near the centre of the square or outside the square. We conclude that the human visual system programs saccades to large luminance defined square objects based on edge locations derived from the points of maximum luminance gradients at the square's edges.

  3. Moving object localization using optical flow for pedestrian detection from a moving vehicle.

    PubMed

    Hariyono, Joko; Hoang, Van-Dung; Jo, Kang-Hyun

    2014-01-01

    This paper presents a pedestrian detection method from a moving vehicle using optical flows and histogram of oriented gradients (HOG). A moving object is extracted from the relative motion by segmenting the region representing the same optical flows after compensating the egomotion of the camera. To obtain the optical flow, two consecutive images are divided into grid cells 14 × 14 pixels; then each cell is tracked in the current frame to find corresponding cell in the next frame. Using at least three corresponding cells, affine transformation is performed according to each corresponding cell in the consecutive images, so that conformed optical flows are extracted. The regions of moving object are detected as transformed objects, which are different from the previously registered background. Morphological process is applied to get the candidate human regions. In order to recognize the object, the HOG features are extracted on the candidate region and classified using linear support vector machine (SVM). The HOG feature vectors are used as input of linear SVM to classify the given input into pedestrian/nonpedestrian. The proposed method was tested in a moving vehicle and also confirmed through experiments using pedestrian dataset. It shows a significant improvement compared with original HOG using ETHZ pedestrian dataset.

  4. Using object-oriented analysis techniques to support system testing

    NASA Astrophysics Data System (ADS)

    Zucconi, Lin

    1990-03-01

    Testing of real-time control systems can be greatly facilitated by use of object-oriented and structured analysis modeling techniques. This report describes a project where behavior, process and information models built for a real-time control system were used to augment and aid traditional system testing. The modeling techniques used were an adaptation of the Ward/Mellor method for real-time systems analysis and design (Ward85) for object-oriented development. The models were used to simulate system behavior by means of hand execution of the behavior or state model and the associated process (data and control flow) and information (data) models. The information model, which uses an extended entity-relationship modeling technique, is used to identify application domain objects and their attributes (instance variables). The behavioral model uses state-transition diagrams to describe the state-dependent behavior of the object. The process model uses a transformation schema to describe the operations performed on or by the object. Together, these models provide a means of analyzing and specifying a system in terms of the static and dynamic properties of the objects which it manipulates. The various models were used to simultaneously capture knowledge about both the objects in the application domain and the system implementation. Models were constructed, verified against the software as-built and validated through informal reviews with the developer. These models were then hand-executed.

  5. A portrait of the extreme solar system object 2012 DR30

    NASA Astrophysics Data System (ADS)

    Kiss, Cs.; Szabó, Gy.; Horner, J.; Conn, B. C.; Müller, T. G.; Vilenius, E.; Sárneczky, K.; Kiss, L. L.; Bannister, M.; Bayliss, D.; Pál, A.; Góbi, S.; Verebélyi, E.; Lellouch, E.; Santos-Sanz, P.; Ortiz, J. L.; Duffard, R.; Morales, N.

    2013-07-01

    2012 DR30 is a recently discovered solar system object on a unique orbit, with a high eccentricity of 0.9867, a perihelion distance of 14.54 AU, and a semi-major axis of 1109 AU, in this respect outscoring the vast majority of trans-Neptunian objects (TNOs). We performed Herschel/PACS and optical photometry to uncover the sizeand albedo of 2012 DR30, together with its thermal and surface properties. The body is 185 km in diameter and has a relatively low V-band geometric albedo of ~8%. Although the colours of the object indicate that 2012 DR30 is an RI taxonomy class TNO or Centaur, we detected an absorption feature in the Z-band that is uncommon among these bodies. A dynamical analysis of the target's orbit shows that 2012 DR30 moves on a relatively unstable orbit and was most likely only recently placed on its current orbit from the most distant and still highly unexplored regions of the solar system. If categorised on dynamical grounds 2012 DR30 is the largest Damocloid and/or high inclination Centaur observed so far. Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.Appendices are available in electronic form at http://www.aanda.org

  6. Evaluating fuzzy operators of an object-based image analysis for detecting landslides and their changes

    NASA Astrophysics Data System (ADS)

    Feizizadeh, Bakhtiar; Blaschke, Thomas; Tiede, Dirk; Moghaddam, Mohammad Hossein Rezaei

    2017-09-01

    This article presents a method of object-based image analysis (OBIA) for landslide delineation and landslide-related change detection from multi-temporal satellite images. It uses both spatial and spectral information on landslides, through spectral analysis, shape analysis, textural measurements using a gray-level co-occurrence matrix (GLCM), and fuzzy logic membership functionality. Following an initial segmentation step, particular combinations of various information layers were investigated to generate objects. This was achieved by applying multi-resolution segmentation to IRS-1D, SPOT-5, and ALOS satellite imagery in sequential steps of feature selection and object classification, and using slope and flow direction derivatives from a digital elevation model together with topographically-oriented gray level co-occurrence matrices. Fuzzy membership values were calculated for 11 different membership functions using 20 landslide objects from a landslide training data. Six fuzzy operators were used for the final classification and the accuracies of the resulting landslide maps were compared. A Fuzzy Synthetic Evaluation (FSE) approach was adapted for validation of the results and for an accuracy assessment using the landslide inventory database. The FSE approach revealed that the AND operator performed best with an accuracy of 93.87% for 2005 and 94.74% for 2011, closely followed by the MEAN Arithmetic operator, while the OR and AND (*) operators yielded relatively low accuracies. An object-based change detection was then applied to monitor landslide-related changes that occurred in northern Iran between 2005 and 2011. Knowledge rules to detect possible landslide-related changes were developed by evaluating all possible landslide-related objects for both time steps.

  7. Standoff detection of hidden objects using backscattered ultra-intense laser-produced x-rays

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

    Kuwabara, H.; Mori, Y.; Kitagawa, Y.

    2013-08-28

    Ultra-intense laser-produced sub-ps X-ray pulses can detect backscattered signals from objects hidden in aluminium containers. Coincident measurements using primary X-rays enable differentiation among acrylic, copper, and lead blocks inside the container. Backscattering reveals the shapes of the objects, while their material composition can be identified from the modification methods of the energy spectra of backscattered X-ray beams. This achievement is an important step toward more effective homeland security.

  8. Finite Element Modeling and Long Wave Infrared Imaging for Detection and Identification of Buried Objects

    DTIC Science & Technology

    surface temperature profile of a sandbox containing buried objects using a long-wave infrared camera. Images were recorded for several days under ambient...time of day . Best detection of buried objects corresponded to shallow depths for observed intervals where maxima/minima ambient temperatures coincided

  9. 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.

  10. Statistical Track-Before-Detect Methods Applied to Faint Optical Observations of Resident Space Objects

    NASA Astrophysics Data System (ADS)

    Fujimoto, K.; Yanagisawa, T.; Uetsuhara, M.

    Automated detection and tracking of faint objects in optical, or bearing-only, sensor imagery is a topic of immense interest in space surveillance. Robust methods in this realm will lead to better space situational awareness (SSA) while reducing the cost of sensors and optics. They are especially relevant in the search for high area-to-mass ratio (HAMR) objects, as their apparent brightness can change significantly over time. A track-before-detect (TBD) approach has been shown to be suitable for faint, low signal-to-noise ratio (SNR) images of resident space objects (RSOs). TBD does not rely upon the extraction of feature points within the image based on some thresholding criteria, but rather directly takes as input the intensity information from the image file. Not only is all of the available information from the image used, TBD avoids the computational intractability of the conventional feature-based line detection (i.e., "string of pearls") approach to track detection for low SNR data. Implementation of TBD rooted in finite set statistics (FISST) theory has been proposed recently by Vo, et al. Compared to other TBD methods applied so far to SSA, such as the stacking method or multi-pass multi-period denoising, the FISST approach is statistically rigorous and has been shown to be more computationally efficient, thus paving the path toward on-line processing. In this paper, we intend to apply a multi-Bernoulli filter to actual CCD imagery of RSOs. The multi-Bernoulli filter can explicitly account for the birth and death of multiple targets in a measurement arc. TBD is achieved via a sequential Monte Carlo implementation. Preliminary results with simulated single-target data indicate that a Bernoulli filter can successfully track and detect objects with measurement SNR as low as 2.4. Although the advent of fast-cadence scientific CMOS sensors have made the automation of faint object detection a realistic goal, it is nonetheless a difficult goal, as measurements

  11. Detecting multiple moving objects in crowded environments with coherent motion regions

    DOEpatents

    Cheriyadat, Anil M.; Radke, Richard J.

    2013-06-11

    Coherent motion regions extend in time as well as space, enforcing consistency in detected objects over long time periods and making the algorithm robust to noisy or short point tracks. As a result of enforcing the constraint that selected coherent motion regions contain disjoint sets of tracks defined in a three-dimensional space including a time dimension. An algorithm operates directly on raw, unconditioned low-level feature point tracks, and minimizes a global measure of the coherent motion regions. At least one discrete moving object is identified in a time series of video images based on the trajectory similarity factors, which is a measure of a maximum distance between a pair of feature point tracks.

  12. A Foreign Object Damage Event Detector Data Fusion System for Turbofan Engines

    NASA Technical Reports Server (NTRS)

    Turso, James A.; Litt, Jonathan S.

    2004-01-01

    A Data Fusion System designed to provide a reliable assessment of the occurrence of Foreign Object Damage (FOD) in a turbofan engine is presented. The FOD-event feature level fusion scheme combines knowledge of shifts in engine gas path performance obtained using a Kalman filter, with bearing accelerometer signal features extracted via wavelet analysis, to positively identify a FOD event. A fuzzy inference system provides basic probability assignments (bpa) based on features extracted from the gas path analysis and bearing accelerometers to a fusion algorithm based on the Dempster-Shafer-Yager Theory of Evidence. Details are provided on the wavelet transforms used to extract the foreign object strike features from the noisy data and on the Kalman filter-based gas path analysis. The system is demonstrated using a turbofan engine combined-effects model (CEM), providing both gas path and rotor dynamic structural response, and is suitable for rapid-prototyping of control and diagnostic systems. The fusion of the disparate data can provide significantly more reliable detection of a FOD event than the use of either method alone. The use of fuzzy inference techniques combined with Dempster-Shafer-Yager Theory of Evidence provides a theoretical justification for drawing conclusions based on imprecise or incomplete data.

  13. A Secure and Robust Object-Based Video Authentication System

    NASA Astrophysics Data System (ADS)

    He, Dajun; Sun, Qibin; Tian, Qi

    2004-12-01

    An object-based video authentication system, which combines watermarking, error correction coding (ECC), and digital signature techniques, is presented for protecting the authenticity between video objects and their associated backgrounds. In this system, a set of angular radial transformation (ART) coefficients is selected as the feature to represent the video object and the background, respectively. ECC and cryptographic hashing are applied to those selected coefficients to generate the robust authentication watermark. This content-based, semifragile watermark is then embedded into the objects frame by frame before MPEG4 coding. In watermark embedding and extraction, groups of discrete Fourier transform (DFT) coefficients are randomly selected, and their energy relationships are employed to hide and extract the watermark. The experimental results demonstrate that our system is robust to MPEG4 compression, object segmentation errors, and some common object-based video processing such as object translation, rotation, and scaling while securely preventing malicious object modifications. The proposed solution can be further incorporated into public key infrastructure (PKI).

  14. Keypoint Density-Based Region Proposal for Fine-Grained Object Detection and Classification Using Regions with Convolutional Neural Network Features

    DTIC Science & Technology

    2015-12-15

    Keypoint Density-based Region Proposal for Fine-Grained Object Detection and Classification using Regions with Convolutional Neural Network ... Convolutional Neural Networks (CNNs) enable them to outperform conventional techniques on standard object detection and classification tasks, their...detection accuracy and speed on the fine-grained Caltech UCSD bird dataset (Wah et al., 2011). Recently, Convolutional Neural Networks (CNNs), a deep

  15. An object cue is more effective than a word in ERP-based detection of deception.

    PubMed

    Cutmore, Tim R H; Djakovic, Tatjana; Kebbell, Mark R; Shum, David H K

    2009-03-01

    Recent studies of deception have used a form of the guilty knowledge test along with the oddball P300 event-related potential (ERP) to uncover hidden memories. These studies typically have used words as the cuing stimuli. In the present study, a mock crime was enacted by participants to prime their episodic memory and different memory cue types (Words, Pictures of Objects and Faces) were created to investigate their relative efficacy in identifying guilt. A peak-to peak (p-p) P300 response was computed for rare known non-guilty item (target), rare guilty knowledge item (probe) and frequently presented unknown items (irrelevant). Difference in this P300 measure between the probe and irrelevant was the key dependent variable. Object cues were found to be the most effective, particularly at the parietal site. A bootstrap procedure commonly used to detect deception in individual participants by comparing their probe and irrelevant P300 p-p showed the object cues to provide the best discrimination. Furthermore, using all three of the cue types together provided high detection accuracy (94%). These results confirm prior findings on the utility of ERPs for detecting deception. More importantly, they provide support for the hypothesis that direct cueing with a picture of the crime object may be more effective than using a word (consistent with the picture superiority effect reported in the literature). Finally, a face cue (e.g., crime victim) may also provide a useful probe for detection of guilty knowledge but this stimulus form needs to be chosen with due caution.

  16. Reduction of Subjective and Objective System Complexity

    NASA Technical Reports Server (NTRS)

    Watson, Michael D.

    2015-01-01

    Occam's razor is often used in science to define the minimum criteria to establish a physical or philosophical idea or relationship. Albert Einstein is attributed the saying "everything should be made as simple as possible, but not simpler". These heuristic ideas are based on a belief that there is a minimum state or set of states for a given system or phenomena. In looking at system complexity, these heuristics point us to an idea that complexity can be reduced to a minimum. How then, do we approach a reduction in complexity? Complexity has been described as a subjective concept and an objective measure of a system. Subjective complexity is based on human cognitive comprehension of the functions and inter relationships of a system. Subjective complexity is defined by the ability to fully comprehend the system. Simplifying complexity, in a subjective sense, is thus gaining a deeper understanding of the system. As Apple's Jonathon Ive has stated," It's not just minimalism or the absence of clutter. It involves digging through the depth of complexity. To be truly simple, you have to go really deep". Simplicity is not the absence of complexity but a deeper understanding of complexity. Subjective complexity, based on this human comprehension, cannot then be discerned from the sociological concept of ignorance. The inability to comprehend a system can be either a lack of knowledge, an inability to understand the intricacies of a system, or both. Reduction in this sense is based purely on a cognitive ability to understand the system and no system then may be truly complex. From this view, education and experience seem to be the keys to reduction or eliminating complexity. Objective complexity, is the measure of the systems functions and interrelationships which exist independent of human comprehension. Jonathon Ive's statement does not say that complexity is removed, only that the complexity is understood. From this standpoint, reduction of complexity can be approached

  17. Object-Based Change Detection Using High-Resolution Remotely Sensed Data and GIS

    NASA Astrophysics Data System (ADS)

    Sofina, N.; Ehlers, M.

    2012-08-01

    High resolution remotely sensed images provide current, detailed, and accurate information for large areas of the earth surface which can be used for change detection analyses. Conventional methods of image processing permit detection of changes by comparing remotely sensed multitemporal images. However, for performing a successful analysis it is desirable to take images from the same sensor which should be acquired at the same time of season, at the same time of a day, and - for electro-optical sensors - in cloudless conditions. Thus, a change detection analysis could be problematic especially for sudden catastrophic events. A promising alternative is the use of vector-based maps containing information about the original urban layout which can be related to a single image obtained after the catastrophe. The paper describes a methodology for an object-based search of destroyed buildings as a consequence of a natural or man-made catastrophe (e.g., earthquakes, flooding, civil war). The analysis is based on remotely sensed and vector GIS data. It includes three main steps: (i) generation of features describing the state of buildings; (ii) classification of building conditions; and (iii) data import into a GIS. One of the proposed features is a newly developed 'Detected Part of Contour' (DPC). Additionally, several features based on the analysis of textural information corresponding to the investigated vector objects are calculated. The method is applied to remotely sensed images of areas that have been subjected to an earthquake. The results show the high reliability of the DPC feature as an indicator for change.

  18. Method For Detecting The Presence Of A Ferromagnetic Object

    DOEpatents

    Roybal, Lyle G.

    2000-11-21

    A method for detecting a presence or an absence of a ferromagnetic object within a sensing area may comprise the steps of sensing, during a sample time, a magnetic field adjacent the sensing area; producing surveillance data representative of the sensed magnetic field; determining an absolute value difference between a maximum datum and a minimum datum comprising the surveillance data; and determining whether the absolute value difference has a positive or negative sign. The absolute value difference and the corresponding positive or negative sign thereof forms a representative surveillance datum that is indicative of the presence or absence in the sensing area of the ferromagnetic material.

  19. ALLFlight: detection of moving objects in IR and ladar images

    NASA Astrophysics Data System (ADS)

    Doehler, H.-U.; Peinecke, Niklas; Lueken, Thomas; Schmerwitz, Sven

    2013-05-01

    Supporting a helicopter pilot during landing and takeoff in degraded visual environment (DVE) is one of the challenges within DLR's project ALLFlight (Assisted Low Level Flight and Landing on Unprepared Landing Sites). Different types of sensors (TV, Infrared, mmW radar and laser radar) are mounted onto DLR's research helicopter FHS (flying helicopter simulator) for gathering different sensor data of the surrounding world. A high performance computer cluster architecture acquires and fuses all the information to get one single comprehensive description of the outside situation. While both TV and IR cameras deliver images with frame rates of 25 Hz or 30 Hz, Ladar and mmW radar provide georeferenced sensor data with only 2 Hz or even less. Therefore, it takes several seconds to detect or even track potential moving obstacle candidates in mmW or Ladar sequences. Especially if the helicopter is flying with higher speed, it is very important to minimize the detection time of obstacles in order to initiate a re-planning of the helicopter's mission timely. Applying feature extraction algorithms on IR images in combination with data fusion algorithms of extracted features and Ladar data can decrease the detection time appreciably. Based on real data from flight tests, the paper describes applied feature extraction methods for moving object detection, as well as data fusion techniques for combining features from TV/IR and Ladar data.

  20. Mining the Kilo-Degree Survey for solar system objects

    NASA Astrophysics Data System (ADS)

    Mahlke, M.; Bouy, H.; Altieri, B.; Verdoes Kleijn, G.; Carry, B.; Bertin, E.; de Jong, J. T. A.; Kuijken, K.; McFarland, J.; Valentijn, E.

    2018-02-01

    Context. The search for minor bodies in the solar system promises insights into its formation history. Wide imaging surveys offer the opportunity to serendipitously discover and identify these traces of planetary formation and evolution. Aim. We aim to present a method to acquire position, photometry, and proper motion measurements of solar system objects (SSOs) in surveys using dithered image sequences. The application of this method on the Kilo-Degree Survey (KiDS) is demonstrated. Methods: Optical images of 346 deg2 fields of the sky are searched in up to four filters using the AstrOmatic software suite to reduce the pixel to catalog data. The SSOs within the acquired sources are selected based on a set of criteria depending on their number of observation, motion, and size. The Virtual Observatory SkyBoT tool is used to identify known objects. Results: We observed 20 221 SSO candidates, with an estimated false-positive content of less than 0.05%. Of these SSO candidates, 53.4% are identified by SkyBoT. KiDS can detect previously unknown SSOs because of its depth and coverage at high ecliptic latitude, including parts of the Southern Hemisphere. Thus we expect the large fraction of the 46.6% of unidentified objects to be truly new SSOs. Conclusions: Our method is applicable to a variety of dithered surveys such as DES, LSST, and Euclid. It offers a quick and easy-to-implement search for SSOs. SkyBoT can then be used to estimate the completeness of the recovered sample. The tables of raw data are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/610/A21

  1. Detecting Target Objects by Natural Language Instructions Using an RGB-D Camera

    PubMed Central

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

    2016-01-01

    Controlling robots by natural language (NL) is increasingly attracting attention for its versatility, convenience and no need of extensive training for users. Grounding is a crucial challenge of this problem to enable robots to understand NL instructions from humans. This paper mainly explores the object grounding problem and concretely studies how to detect target objects by the NL instructions using an RGB-D camera in robotic manipulation applications. In particular, a simple yet robust vision algorithm is applied to segment objects of interest. With the metric information of all segmented objects, the object attributes and relations between objects are further extracted. The NL instructions that incorporate multiple cues for object specifications are parsed into domain-specific annotations. The annotations from NL and extracted information from the RGB-D camera are matched in a computational state estimation framework to search all possible object grounding states. The final grounding is accomplished by selecting the states which have the maximum probabilities. An RGB-D scene dataset associated with different groups of NL instructions based on different cognition levels of the robot are collected. Quantitative evaluations on the dataset illustrate the advantages of the proposed method. The experiments of NL controlled object manipulation and NL-based task programming using a mobile manipulator show its effectiveness and practicability in robotic applications. PMID:27983604

  2. A combined use of multispectral and SAR images for ship detection and characterization through object based image analysis

    NASA Astrophysics Data System (ADS)

    Aiello, Martina; Gianinetto, Marco

    2017-10-01

    Marine routes represent a huge portion of commercial and human trades, therefore surveillance, security and environmental protection themes are gaining increasing importance. Being able to overcome the limits imposed by terrestrial means of monitoring, ship detection from satellite has recently prompted a renewed interest for a continuous monitoring of illegal activities. This paper describes an automatic Object Based Image Analysis (OBIA) approach to detect vessels made of different materials in various sea environments. The combined use of multispectral and SAR images allows for a regular observation unrestricted by lighting and atmospheric conditions and complementarity in terms of geographic coverage and geometric detail. The method developed adopts a region growing algorithm to segment the image in homogeneous objects, which are then classified through a decision tree algorithm based on spectral and geometrical properties. Then, a spatial analysis retrieves the vessels' position, length and heading parameters and a speed range is associated. Optimization of the image processing chain is performed by selecting image tiles through a statistical index. Vessel candidates are detected over amplitude SAR images using an adaptive threshold Constant False Alarm Rate (CFAR) algorithm prior the object based analysis. Validation is carried out by comparing the retrieved parameters with the information provided by the Automatic Identification System (AIS), when available, or with manual measurement when AIS data are not available. The estimation of length shows R2=0.85 and estimation of heading R2=0.92, computed as the average of R2 values obtained for both optical and radar images.

  3. 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.

  4. Real-time detection of natural objects using AM-coded spectral matching imager

    NASA Astrophysics Data System (ADS)

    Kimachi, Akira

    2004-12-01

    This paper describes application of the amplitude-modulation (AM)-coded spectral matching imager (SMI) to real-time detection of natural objects such as human beings, animals, vegetables, or geological objects or phenomena, which are much more liable to change with time than artificial products while often exhibiting characteristic spectral functions associated with some specific activity states. The AM-SMI produces correlation between spectral functions of the object and a reference at each pixel of the correlation image sensor (CIS) in every frame, based on orthogonal amplitude modulation (AM) of each spectral channel and simultaneous demodulation of all channels on the CIS. This principle makes the SMI suitable to monitoring dynamic behavior of natural objects in real-time by looking at a particular spectral reflectance or transmittance function. A twelve-channel multispectral light source was developed with improved spatial uniformity of spectral irradiance compared to a previous one. Experimental results of spectral matching imaging of human skin and vegetable leaves are demonstrated, as well as a preliminary feasibility test of imaging a reflective object using a test color chart.

  5. Real-time detection of natural objects using AM-coded spectral matching imager

    NASA Astrophysics Data System (ADS)

    Kimachi, Akira

    2005-01-01

    This paper describes application of the amplitude-modulation (AM)-coded spectral matching imager (SMI) to real-time detection of natural objects such as human beings, animals, vegetables, or geological objects or phenomena, which are much more liable to change with time than artificial products while often exhibiting characteristic spectral functions associated with some specific activity states. The AM-SMI produces correlation between spectral functions of the object and a reference at each pixel of the correlation image sensor (CIS) in every frame, based on orthogonal amplitude modulation (AM) of each spectral channel and simultaneous demodulation of all channels on the CIS. This principle makes the SMI suitable to monitoring dynamic behavior of natural objects in real-time by looking at a particular spectral reflectance or transmittance function. A twelve-channel multispectral light source was developed with improved spatial uniformity of spectral irradiance compared to a previous one. Experimental results of spectral matching imaging of human skin and vegetable leaves are demonstrated, as well as a preliminary feasibility test of imaging a reflective object using a test color chart.

  6. On the detection of other planetary systems by astrometric techniques

    NASA Technical Reports Server (NTRS)

    Black, D. C.; Scargle, J. D.

    1982-01-01

    A quantitative method for astrometrically detecting perturbations induced in a star's motion by the presence of a planetary object is described. A periodogram is defined, wherein signals observed from a star show exactly periodic variations, which can be extracted from observational data using purely statistical methods. A detection threshold is defined for the frequency of occurrence of some detectable signal, e.g., the Nyquist frequency. Possible effects of a stellar orbital eccentricity and multiple companions are discussed, noting that assumption of a circular orbit assures the spectral purity of the signal described. The periodogram technique was applied to 12 yr of astrometric data from the U.S. Naval Observatory for three stars with low mass stellar companions. Periodic perturbations were confirmed. A comparison of the accuracy of different astrometric systems shows that the detection accuracy of a system is determined by the measurement accuracy and the number of observations, although the detection efficiency can be maximized by minimizing the number of data points for the case when observational errors are proportional to the square root of the number of data points. It is suggested that a space-based astrometric telescope is best suited to take advantage of the method.

  7. An object-oriented data reduction system in Fortran

    NASA Technical Reports Server (NTRS)

    Bailey, J.

    1992-01-01

    A data reduction system for the AAO two-degree field project is being developed using an object-oriented approach. Rather than use an object-oriented language (such as C++) the system is written in Fortran and makes extensive use of existing subroutine libraries provided by the UK Starlink project. Objects are created using the extensible N-dimensional Data Format (NDF) which itself is based on the Hierarchical Data System (HDS). The software consists of a class library, with each class corresponding to a Fortran subroutine with a standard calling sequence. The methods of the classes provide operations on NDF objects at a similar level of functionality to the applications of conventional data reduction systems. However, because they are provided as callable subroutines, they can be used as building blocks for more specialist applications. The class library is not dependent on a particular software environment thought it can be used effectively in ADAM applications. It can also be used from standalone Fortran programs. It is intended to develop a graphical user interface for use with the class library to form the 2dF data reduction system.

  8. System Detects Vibrational Instabilities

    NASA Technical Reports Server (NTRS)

    Bozeman, Richard J., Jr.

    1990-01-01

    Sustained vibrations at two critical frequencies trigger diagnostic response or shutdown. Vibration-analyzing electronic system detects instabilities of combustion in rocket engine. Controls pulse-mode firing of engine and identifies vibrations above threshold amplitude at 5.9 and/or 12kHz. Adapted to other detection and/or control schemes involving simultaneous real-time detection of signals above or below preset amplitudes at two or more specified frequencies. Potential applications include rotating machinery and encoders and decoders in security systems.

  9. An automatically tuning intrusion detection system.

    PubMed

    Yu, Zhenwei; Tsai, Jeffrey J P; Weigert, Thomas

    2007-04-01

    An intrusion detection system (IDS) is a security layer used to detect ongoing intrusive activities in information systems. Traditionally, intrusion detection relies on extensive knowledge of security experts, in particular, on their familiarity with the computer system to be protected. To reduce this dependence, various data-mining and machine learning techniques have been deployed for intrusion detection. An IDS is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current systems depends on the system operators in working out the tuning solution and in integrating it into the detection model. In this paper, an automatically tuning IDS (ATIDS) is presented. The proposed system will automatically tune the detection model on-the-fly according to the feedback provided by the system operator when false predictions are encountered. The system is evaluated using the KDDCup'99 intrusion detection dataset. Experimental results show that the system achieves up to 35% improvement in terms of misclassification cost when compared with a system lacking the tuning feature. If only 10% false predictions are used to tune the model, the system still achieves about 30% improvement. Moreover, when tuning is not delayed too long, the system can achieve about 20% improvement, with only 1.3% of the false predictions used to tune the model. The results of the experiments show that a practical system can be built based on ATIDS: system operators can focus on verification of predictions with low confidence, as only those predictions determined to be false will be used to tune the detection model.

  10. Multiple Object Based RFID System Using Security Level

    NASA Astrophysics Data System (ADS)

    Kim, Jiyeon; Jung, Jongjin; Ryu, Ukjae; Ko, Hoon; Joe, Susan; Lee, Yongjun; Kim, Boyeon; Chang, Yunseok; Lee, Kyoonha

    2007-12-01

    RFID systems are increasingly applied for operational convenience in wide range of industries and individual life. However, it is uneasy for a person to control many tags because common RFID systems have the restriction that a tag used to identify just a single object. In addition, RFID systems can make some serious problems in violation of privacy and security because of their radio frequency communication. In this paper, we propose a multiple object RFID tag which can keep multiple object identifiers for different applications in a same tag. The proposed tag allows simultaneous access for their pair applications. We also propose an authentication protocol for multiple object tag to prevent serious problems of security and privacy in RFID applications. Especially, we focus on efficiency of the authentication protocol by considering security levels of applications. In the proposed protocol, the applications go through different authentication procedures according to security level of the object identifier stored in the tag. We implemented the proposed RFID scheme and made experimental results about efficiency and stability for the scheme.

  11. A Benchmark Dataset and Saliency-guided Stacked Autoencoders for Video-based Salient Object Detection.

    PubMed

    Li, Jia; Xia, Changqun; Chen, Xiaowu

    2017-10-12

    Image-based salient object detection (SOD) has been extensively studied in past decades. However, video-based SOD is much less explored due to the lack of large-scale video datasets within which salient objects are unambiguously defined and annotated. Toward this end, this paper proposes a video-based SOD dataset that consists of 200 videos. In constructing the dataset, we manually annotate all objects and regions over 7,650 uniformly sampled keyframes and collect the eye-tracking data of 23 subjects who free-view all videos. From the user data, we find that salient objects in a video can be defined as objects that consistently pop-out throughout the video, and objects with such attributes can be unambiguously annotated by combining manually annotated object/region masks with eye-tracking data of multiple subjects. To the best of our knowledge, it is currently the largest dataset for videobased salient object detection. Based on this dataset, this paper proposes an unsupervised baseline approach for video-based SOD by using saliencyguided stacked autoencoders. In the proposed approach, multiple spatiotemporal saliency cues are first extracted at the pixel, superpixel and object levels. With these saliency cues, stacked autoencoders are constructed in an unsupervised manner that automatically infers a saliency score for each pixel by progressively encoding the high-dimensional saliency cues gathered from the pixel and its spatiotemporal neighbors. In experiments, the proposed unsupervised approach is compared with 31 state-of-the-art models on the proposed dataset and outperforms 30 of them, including 19 imagebased classic (unsupervised or non-deep learning) models, six image-based deep learning models, and five video-based unsupervised models. Moreover, benchmarking results show that the proposed dataset is very challenging and has the potential to boost the development of video-based SOD.

  12. Parallel object-oriented data mining system

    DOEpatents

    Kamath, Chandrika; Cantu-Paz, Erick

    2004-01-06

    A data mining system uncovers patterns, associations, anomalies and other statistically significant structures in data. Data files are read and displayed. Objects in the data files are identified. Relevant features for the objects are extracted. Patterns among the objects are recognized based upon the features. Data from the Faint Images of the Radio Sky at Twenty Centimeters (FIRST) sky survey was used to search for bent doubles. This test was conducted on data from the Very Large Array in New Mexico which seeks to locate a special type of quasar (radio-emitting stellar object) called bent doubles. The FIRST survey has generated more than 32,000 images of the sky to date. Each image is 7.1 megabytes, yielding more than 100 gigabytes of image data in the entire data set.

  13. System for sterilizing objects. [cleaning space vehicle systems

    NASA Technical Reports Server (NTRS)

    Bryan, C. J.; Wright, E. E., Jr.; Moyers, C. V. (Inventor)

    1981-01-01

    A system for producing a stream of humidified sterilizing gas for sterilizing objects such as the water systems of space vehicles and the like includes a source of sterilant gas which is fed to a mixing chamber which has inlet and outlet ports. The level of the water only partially fills the mixing chamber so as to provide an empty space adjacent the top of the chamber. A heater is provided for heating the water in the chamber so as to produce a humidified atmosphere. The sterilant gas is fed through an arcuate shaped tubular member connected to the inlet port of the mixing chamber for producing a vortex type of flow of sterilant gas into the chamber for humidification. A tubular member extends from the mixing chamber for supplying the humidified sterilant gas to the object for being sterilized. Scrubbers are provided for removing the sterilant gas after use.

  14. Support vector machine as a binary classifier for automated object detection in remotely sensed data

    NASA Astrophysics Data System (ADS)

    Wardaya, P. D.

    2014-02-01

    In the present paper, author proposes the application of Support Vector Machine (SVM) for the analysis of satellite imagery. One of the advantages of SVM is that, with limited training data, it may generate comparable or even better results than the other methods. The SVM algorithm is used for automated object detection and characterization. Specifically, the SVM is applied in its basic nature as a binary classifier where it classifies two classes namely, object and background. The algorithm aims at effectively detecting an object from its background with the minimum training data. The synthetic image containing noises is used for algorithm testing. Furthermore, it is implemented to perform remote sensing image analysis such as identification of Island vegetation, water body, and oil spill from the satellite imagery. It is indicated that SVM provides the fast and accurate analysis with the acceptable result.

  15. Color Image Processing and Object Tracking System

    NASA Technical Reports Server (NTRS)

    Klimek, Robert B.; Wright, Ted W.; Sielken, Robert S.

    1996-01-01

    This report describes a personal computer based system for automatic and semiautomatic tracking of objects on film or video tape, developed to meet the needs of the Microgravity Combustion and Fluids Science Research Programs at the NASA Lewis Research Center. The system consists of individual hardware components working under computer control to achieve a high degree of automation. The most important hardware components include 16-mm and 35-mm film transports, a high resolution digital camera mounted on a x-y-z micro-positioning stage, an S-VHS tapedeck, an Hi8 tapedeck, video laserdisk, and a framegrabber. All of the image input devices are remotely controlled by a computer. Software was developed to integrate the overall operation of the system including device frame incrementation, grabbing of image frames, image processing of the object's neighborhood, locating the position of the object being tracked, and storing the coordinates in a file. This process is performed repeatedly until the last frame is reached. Several different tracking methods are supported. To illustrate the process, two representative applications of the system are described. These applications represent typical uses of the system and include tracking the propagation of a flame front and tracking the movement of a liquid-gas interface with extremely poor visibility.

  16. 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.

  17. A food contaminant detection system based on high-Tc SQUIDs

    NASA Astrophysics Data System (ADS)

    Tanaka, Saburo; Fujita, H.; Hatsukade, Y.; Nagaishi, T.; Nishi, K.; Ota, H.; Otani, T.; Suzuki, S.

    2006-05-01

    We have designed and constructed a computer controlled food contaminant detection system for practical use, based on high-Tc SQUID detectors. The system, which features waterproof stainless steel construction, is acceptable under the HACCP (Hazard Analysis and Critical Control Point) programme guidelines. The outer dimensions of the system are 1500 mm length × 477 mm width × 1445 mm height, and it can accept objects up to 200 mm wide × 80 mm high. An automatic liquid nitrogen filling system was installed in the standard model. This system employed a double-layered permeable metallic shield with a thickness of 1 mm as a magnetically shielded box. The distribution of the magnetic field in the box was simulated by FEM; the gap between each shield layer was optimized before fabrication. A shielding factor of 732 in the Z-component was achieved. This value is high enough to safely operate the system in a non-laboratory environment, i.e., a factory. During testing, we successfully detected a steel contaminant as small as 0.3 mm in diameter at a distance of 75 mm.

  18. The Perception of Concurrent Sound Objects in Harmonic Complexes Impairs Gap Detection

    ERIC Educational Resources Information Center

    Leung, Ada W. S.; Jolicoeur, Pierre; Vachon, Francois; Alain, Claude

    2011-01-01

    Since the introduction of the concept of auditory scene analysis, there has been a paucity of work focusing on the theoretical explanation of how attention is allocated within a complex auditory scene. Here we examined signal detection in situations that promote either the fusion of tonal elements into a single sound object or the segregation of a…

  19. 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.

  20. Intrusion Detection in Database Systems

    NASA Astrophysics Data System (ADS)

    Javidi, Mohammad M.; Sohrabi, Mina; Rafsanjani, Marjan Kuchaki

    Data represent today a valuable asset for organizations and companies and must be protected. Ensuring the security and privacy of data assets is a crucial and very difficult problem in our modern networked world. Despite the necessity of protecting information stored in database systems (DBS), existing security models are insufficient to prevent misuse, especially insider abuse by legitimate users. One mechanism to safeguard the information in these databases is to use an intrusion detection system (IDS). The purpose of Intrusion detection in database systems is to detect transactions that access data without permission. In this paper several database Intrusion detection approaches are evaluated.

  1. 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.

  2. Stray light suppression of optical and mechanical system for telescope detection

    NASA Astrophysics Data System (ADS)

    Wang, Lei; Ma, Wenli

    2013-09-01

    During telescope detection, there is atmosphere overflow and other stray light affecting the system which leads to background disturbance. Thus reduce the detection capability of the system. So it is very necessary to design mechanical structure to suppress the stray light for the telescope detection system. It can both improve the signal-to-noise and contrast of the object. This paper designs the optical and mechanical structure of the 400mm telescope. And then the main baffle, baffle vane, field stop and coating technology are used to eliminate the effect of stray light on the optical and mechanical system. Finally, software is used to analyze and simulate stray light on the whole optical and mechanical system. Using PST as the evaluating standard, separate and integrated analysis of the suppressing effect of main baffle, baffle vane and field aperture is completed. And also get the results of PST before and after eliminating the stray light. Meanwhile, the results of stray light analysis can be used to guide the design of the optical and mechanical structure. The analysis results demonstrate that reasonable optical and mechanical structure and stray light suppression measure can highly reduce the PST and also improve the detection capability of the telescope system, and the designed outside baffle, inside baffle, vanes and coating technique etc. can decrease the PST approximately 1 to 3 level.

  3. 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...

  4. 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.

  5. Solar system fault detection

    DOEpatents

    Farrington, R.B.; Pruett, J.C. Jr.

    1984-05-14

    A fault detecting apparatus and method are provided for use with an active solar system. The apparatus provides an indication as to whether one or more predetermined faults have occurred in the solar system. The apparatus includes a plurality of sensors, each sensor being used in determining whether a predetermined condition is present. The outputs of the sensors are combined in a pre-established manner in accordance with the kind of predetermined faults to be detected. Indicators communicate with the outputs generated by combining the sensor outputs to give the user of the solar system and the apparatus an indication as to whether a predetermined fault has occurred. Upon detection and indication of any predetermined fault, the user can take appropriate corrective action so that the overall reliability and efficiency of the active solar system are increased.

  6. Solar system fault detection

    DOEpatents

    Farrington, Robert B.; Pruett, Jr., James C.

    1986-01-01

    A fault detecting apparatus and method are provided for use with an active solar system. The apparatus provides an indication as to whether one or more predetermined faults have occurred in the solar system. The apparatus includes a plurality of sensors, each sensor being used in determining whether a predetermined condition is present. The outputs of the sensors are combined in a pre-established manner in accordance with the kind of predetermined faults to be detected. Indicators communicate with the outputs generated by combining the sensor outputs to give the user of the solar system and the apparatus an indication as to whether a predetermined fault has occurred. Upon detection and indication of any predetermined fault, the user can take appropriate corrective action so that the overall reliability and efficiency of the active solar system are increased.

  7. Experiences Building an Object-Oriented System in C++

    NASA Technical Reports Server (NTRS)

    Madany, Peter W.; Campbell, Roy H.; Kougiouris, Panagiotis

    1991-01-01

    This paper describes tools that we built to support the construction of an object-oriented operating system in C++. The tools provide the automatic deletion of unwanted objects, first-class classes, dynamically loadable classes, and class-oriented debugging. As a consequence of our experience building Choices, we advocate these features as useful, simplifying and unifying many aspects of system programming.

  8. Web-of-Objects (WoO)-Based Context Aware Emergency Fire Management Systems for the Internet of Things

    PubMed Central

    Shamszaman, Zia Ush; Ara, Safina Showkat; Chong, Ilyoung; Jeong, Youn Kwae

    2014-01-01

    Recent advancements in the Internet of Things (IoT) and the Web of Things (WoT) accompany a smart life where real world objects, including sensing devices, are interconnected with each other. The Web representation of smart objects empowers innovative applications and services for various domains. To accelerate this approach, Web of Objects (WoO) focuses on the implementation aspects of bringing the assorted real world objects to the Web applications. In this paper; we propose an emergency fire management system in the WoO infrastructure. Consequently, we integrate the formation and management of Virtual Objects (ViO) which are derived from real world physical objects and are virtually connected with each other into the semantic ontology model. The charm of using the semantic ontology is that it allows information reusability, extensibility and interoperability, which enable ViOs to uphold orchestration, federation, collaboration and harmonization. Our system is context aware, as it receives contextual environmental information from distributed sensors and detects emergency situations. To handle a fire emergency, we present a decision support tool for the emergency fire management team. The previous fire incident log is the basis of the decision support system. A log repository collects all the emergency fire incident logs from ViOs and stores them in a repository. PMID:24531299

  9. Web-of-Objects (WoO)-based context aware emergency fire management systems for the Internet of Things.

    PubMed

    Shamszaman, Zia Ush; Ara, Safina Showkat; Chong, Ilyoung; Jeong, Youn Kwae

    2014-02-13

    Recent advancements in the Internet of Things (IoT) and the Web of Things (WoT) accompany a smart life where real world objects, including sensing devices, are interconnected with each other. The Web representation of smart objects empowers innovative applications and services for various domains. To accelerate this approach, Web of Objects (WoO) focuses on the implementation aspects of bringing the assorted real world objects to the Web applications. In this paper; we propose an emergency fire management system in the WoO infrastructure. Consequently, we integrate the formation and management of Virtual Objects (ViO) which are derived from real world physical objects and are virtually connected with each other into the semantic ontology model. The charm of using the semantic ontology is that it allows information reusability, extensibility and interoperability, which enable ViOs to uphold orchestration, federation, collaboration and harmonization. Our system is context aware, as it receives contextual environmental information from distributed sensors and detects emergency situations. To handle a fire emergency, we present a decision support tool for the emergency fire management team. The previous fire incident log is the basis of the decision support system. A log repository collects all the emergency fire incident logs from ViOs and stores them in a repository.

  10. The use of far infra-red radiation for the detection of concealed metal objects.

    DOT National Transportation Integrated Search

    1971-11-01

    Abstract The use of infrared radiation for the detection : of concealed metal objects has been investigated both : theoretically and experimentally. The investigation was : divided into two phases, one which considered passive : techniques, and anoth...

  11. Life detection systems.

    NASA Technical Reports Server (NTRS)

    Mitz, M. A.

    1972-01-01

    Some promising newer approaches for detecting microorganisms are discussed, giving particular attention to the integration of different methods into a single instrument. Life detection methods may be divided into biological, chemical, and cytological methods. Biological methods are based on the biological properties of assimilation, metabolism, and growth. Devices for the detection of organic materials are considered, taking into account an instrument which volatilizes, separates, and analyzes a sample sequentially. Other instrumental systems described make use of a microscope and the cytochemical staining principle.

  12. 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

  13. Kyiv Small Rivers in Metropolis Water Objects System

    NASA Astrophysics Data System (ADS)

    Krelshteyn, P.; Dubnytska, M.

    2017-12-01

    The article answers the question, what really are the small underground rivers with artificial watercourses: water bodies or city engineering infrastructure objects? The place of such rivers in metropolis water objects system is identified. The ecological state and the degree of urbanization of small rivers, as well as the dynamics of change in these indicators are analysed on the Kiev city example with the help of water objects cadastre. It was found that the registration of small rivers in Kyiv city is not conducted, and the summary information on such water objects is absent and is not taken into account when making managerial decisions at the urban level. To solve this problem, we propose to create some water bodies accounting system (water cadastre).

  14. Asteroid-comet continuum objects in the solar system.

    PubMed

    Hsieh, Henry H

    2017-07-13

    In this review presented at the Royal Society meeting, 'Cometary science after Rosetta', I present an overview of studies of small solar system objects that exhibit properties of both asteroids and comets (with a focus on so-called active asteroids). Sometimes referred to as 'transition objects', these bodies are perhaps more appropriately described as 'continuum objects', to reflect the notion that rather than necessarily representing actual transitional evolutionary states between asteroids and comets, they simply belong to the general population of small solar system bodies that happen to exhibit a continuous range of observational, physical and dynamical properties. Continuum objects are intriguing because they possess many of the properties that make classical comets interesting to study (e.g. relatively primitive compositions, ejection of surface and subsurface material into space where it can be more easily studied, and orbital properties that allow us to sample material from distant parts of the solar system that would otherwise be inaccessible), while allowing us to study regions of the solar system that are not sampled by classical comets.This article is part of the themed issue 'Cometary science after Rosetta'. © 2017 The Author(s).

  15. Adapting astronomical source detection software to help detect animals in thermal images obtained by unmanned aerial systems

    NASA Astrophysics Data System (ADS)

    Longmore, S. N.; Collins, R. P.; Pfeifer, S.; Fox, S. E.; Mulero-Pazmany, M.; Bezombes, F.; Goodwind, A.; de Juan Ovelar, M.; Knapen, J. H.; Wich, S. A.

    2017-02-01

    In this paper we describe an unmanned aerial system equipped with a thermal-infrared camera and software pipeline that we have developed to monitor animal populations for conservation purposes. Taking a multi-disciplinary approach to tackle this problem, we use freely available astronomical source detection software and the associated expertise of astronomers, to efficiently and reliably detect humans and animals in aerial thermal-infrared footage. Combining this astronomical detection software with existing machine learning algorithms into a single, automated, end-to-end pipeline, we test the software using aerial video footage taken in a controlled, field-like environment. We demonstrate that the pipeline works reliably and describe how it can be used to estimate the completeness of different observational datasets to objects of a given type as a function of height, observing conditions etc. - a crucial step in converting video footage to scientifically useful information such as the spatial distribution and density of different animal species. Finally, having demonstrated the potential utility of the system, we describe the steps we are taking to adapt the system for work in the field, in particular systematic monitoring of endangered species at National Parks around the world.

  16. Mentat: An object-oriented macro data flow system

    NASA Technical Reports Server (NTRS)

    Grimshaw, Andrew S.; Liu, Jane W. S.

    1988-01-01

    Mentat, an object-oriented macro data flow system designed to facilitate parallelism in distributed systems, is presented. The macro data flow model is a model of computation similar to the data flow model with two principal differences: the computational complexity of the actors is much greater than in traditional data flow systems, and there are persistent actors that maintain state information between executions. Mentat is a system that combines the object-oriented programming paradigm and the macro data flow model of computation. Mentat programs use a dynamic structure called a future list to represent the future of computations.

  17. Field Tests of a Tractor Rollover Detection and Emergency Notification System.

    PubMed

    Liu, B; Koc, A B

    2015-04-01

    The objective of this research was to assess the feasibility of a rollover detection and emergency notification system for farm tractors using field tests. The emergency notification system was developed based on a tractor stability model and implemented on a mobile electronic device with the iOS operating system. A complementary filter was implemented to combine the data from the accelerometer and gyroscope sensors to improve their accuracies in calculating the roll and pitch angles and the roll and pitch rates. The system estimates a stability index value during tractor operation, displays feedback messages when the stability index is lower than a preset threshold value, and transmits emergency notification messages when an overturn happens. Ten tractor rollover tests were conducted on a field track. The developed system successfully monitored the stability of the tractor during all of the tests. The iOS application was able to detect rollover accidents and transmit emergency notifications in the form of a phone call and email when an accident was detected. The system can be a useful tool for training and education in safe tractor operation. The system also has potential for stability monitoring and emergency notification of other on-road and off-road motorized vehicles.

  18. The use of far infra-red radiation for the detection of concealed metal objects

    DOT National Transportation Integrated Search

    1971-11-01

    The use of infrared radiation for the detection of concealed metal objects has been investigated both theoretically and experimentally. The investigation was divided into two phases, one which considered passive techniques, and another which involved...

  19. 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.

  20. Salient object detection: manifold-based similarity adaptation approach

    NASA Astrophysics Data System (ADS)

    Zhou, Jingbo; Ren, Yongfeng; Yan, Yunyang; Gao, Shangbing

    2014-11-01

    A saliency detection algorithm based on manifold-based similarity adaptation is proposed. The proposed algorithm is divided into three steps. First, we segment an input image into superpixels, which are represented as the nodes in a graph. Second, a new similarity measurement is used in the proposed algorithm. The weight matrix of the graph, which indicates the similarities between the nodes, uses a similarity-based method. It also captures the manifold structure of the image patches, in which the graph edges are determined in a data adaptive manner in terms of both similarity and manifold structure. Then, we use local reconstruction method as a diffusion method to obtain the saliency maps. The objective function in the proposed method is based on local reconstruction, with which estimated weights capture the manifold structure. Experiments on four bench-mark databases demonstrate the accuracy and robustness of the proposed method.

  1. Water system virus detection

    NASA Technical Reports Server (NTRS)

    Fraser, A. S.; Wells, A. F.; Tenoso, H. J.

    1975-01-01

    A monitoring system developed to test the capability of a water recovery system to reject the passage of viruses into the recovered water is described. A nonpathogenic marker virus, bacteriophage F2, is fed into the process stream before the recovery unit and the reclaimed water is assayed for its presence. Detection of the marker virus consists of two major components, concentration and isolation of the marker virus, and detection of the marker virus. The concentration system involves adsorption of virus to cellulose acetate filters in the presence of trivalent cations and low pH with subsequent desorption of the virus using volumes of high pH buffer. The detection of the virus is performed by a passive immune agglutination test utilizing specially prepared polystyrene particles. An engineering preliminary design was performed as a parallel effort to the laboratory development of the marker virus test system. Engineering schematics and drawings of a fully functional laboratory prototype capable of zero-G operation are presented. The instrument consists of reagent pump/metering system, reagent storage containers, a filter concentrator, an incubation/detector system, and an electronic readout and control system.

  2. Mechanical Systems. Competency Statements/Objectives and Reference Guide.

    ERIC Educational Resources Information Center

    North Carolina State Dept. of Public Instruction, Raleigh. Div. of Vocational Education.

    This curriculum guide provides competency statements/objectives for an 11th- to 12th-grade trade and industrial education course in mechanical systems. The first half of the guide consists of competency statements for the 53 units of the curriculum. Each competency statement consists of a terminal objective and specific objectives for each unit,…

  3. 46 CFR 108.405 - Fire detection system.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 46 Shipping 4 2010-10-01 2010-10-01 false Fire detection system. 108.405 Section 108.405 Shipping... EQUIPMENT Fire Extinguishing Systems § 108.405 Fire detection system. (a) Each fire detection system and each smoke detection system on a unit must— (1) Be approved by the Commandant; and (2) Have a visual...

  4. Inside-the-wall detection of objects with low metal content using the GPR sensor: effects of different wall structures on the detection performance

    NASA Astrophysics Data System (ADS)

    Dogan, Mesut; Yesilyurt, Omer; Turhan-Sayan, Gonul

    2018-04-01

    Ground penetrating radar (GPR) is an ultra-wideband electromagnetic sensor used not only for subsurface sensing but also for the detection of objects which may be hidden behind a wall or inserted within the wall. Such applications of the GPR technology are used in both military and civilian operations such as mine or IED (improvised explosive device) detection, rescue missions after earthquakes and investigation of archeological sites. Detection of concealed objects with low metal content is known to be a challenging problem in general. Use of A-scan, B-scan and C-scan GPR data in combination provides valuable information for target recognition in such applications. In this paper, we study the problem of target detection for potentially explosive objects embedded inside a wall. GPR data is numerically simulated by using an FDTD-based numerical computation tool when dielectric targets and targets with low metal content are inserted into different types of walls. A small size plastic bottle filled with trinitrotoluene (TNT) is used as the target with and without a metal fuse in it. The targets are buried into two different types of wall; a homogeneous brick wall and an inhomogeneous wall constructed by bricks having periodically located air holes in it. Effects of using an inhomogeneous wall structure with internal boundaries are investigated as a challenging scenario, paying special attention to preprocessing.

  5. 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.

  6. Detecting and discriminating novel objects: The impact of perirhinal cortex disconnection on hippocampal activity patterns

    PubMed Central

    Amin, Eman; Olarte‐Sánchez, Cristian M.; Aggleton, John P.

    2016-01-01

    ABSTRACT Perirhinal cortex provides object‐based information and novelty/familiarity information for the hippocampus. The necessity of these inputs was tested by comparing hippocampal c‐fos expression in rats with or without perirhinal lesions. These rats either discriminated novel from familiar objects (Novel‐Familiar) or explored pairs of novel objects (Novel‐Novel). Despite impairing Novel‐Familiar discriminations, the perirhinal lesions did not affect novelty detection, as measured by overall object exploration levels (Novel‐Novel condition). The perirhinal lesions also largely spared a characteristic network of linked c‐fos expression associated with novel stimuli (entorhinal cortex→CA3→distal CA1→proximal subiculum). The findings show: I) that perirhinal lesions preserve behavioral sensitivity to novelty, whilst still impairing the spontaneous ability to discriminate novel from familiar objects, II) that the distinctive patterns of hippocampal c‐fos activity promoted by novel stimuli do not require perirhinal inputs, III) that entorhinal Fos counts (layers II and III) increase for novelty discriminations, IV) that hippocampal c‐fos networks reflect proximal‐distal connectivity differences, and V) that discriminating novelty creates different pathway interactions from merely detecting novelty, pointing to top‐down effects that help guide object selection. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc. PMID:27398938

  7. The use of far infra-red radiation for the detection of concealed metal objects.

    DOT National Transportation Integrated Search

    1971-11-01

    The use of infra-red radiation for the detection : of conceal ed metal objects has been investiga ted both : theoretically and experimentally. The investigation was : divided into two phases, one which considered passive : techniques, and another whi...

  8. Bridge Crack Detection Using Multi-Rotary Uav and Object-Base Image Analysis

    NASA Astrophysics Data System (ADS)

    Rau, J. Y.; Hsiao, K. W.; Jhan, J. P.; Wang, S. H.; Fang, W. C.; Wang, J. L.

    2017-08-01

    Bridge is an important infrastructure for human life. Thus, the bridge safety monitoring and maintaining is an important issue to the government. Conventionally, bridge inspection were conducted by human in-situ visual examination. This procedure sometimes require under bridge inspection vehicle or climbing under the bridge personally. Thus, its cost and risk is high as well as labor intensive and time consuming. Particularly, its documentation procedure is subjective without 3D spatial information. In order cope with these challenges, this paper propose the use of a multi-rotary UAV that equipped with a SONY A7r2 high resolution digital camera, 50 mm fixed focus length lens, 135 degrees up-down rotating gimbal. The target bridge contains three spans with a total of 60 meters long, 20 meters width and 8 meters height above the water level. In the end, we took about 10,000 images, but some of them were acquired by hand held method taken on the ground using a pole with 2-8 meters long. Those images were processed by Agisoft PhotoscanPro to obtain exterior and interior orientation parameters. A local coordinate system was defined by using 12 ground control points measured by a total station. After triangulation and camera self-calibration, the RMS of control points is less than 3 cm. A 3D CAD model that describe the bridge surface geometry was manually measured by PhotoscanPro. They were composed of planar polygons and will be used for searching related UAV images. Additionally, a photorealistic 3D model can be produced for 3D visualization. In order to detect cracks on the bridge surface, we utilize object-based image analysis (OBIA) technique to segment the image into objects. Later, we derive several object features, such as density, area/bounding box ratio, length/width ratio, length, etc. Then, we can setup a classification rule set to distinguish cracks. Further, we apply semi-global-matching (SGM) to obtain 3D crack information and based on image

  9. Integrating an object system into CLIPS: Language design and implementation issues

    NASA Technical Reports Server (NTRS)

    Auburn, Mark

    1990-01-01

    This paper describes the reasons why an object system with integrated pattern-matching and object-oriented programming facilities is desirable for CLIPS and how it is possible to integrate such a system into CLIPS while maintaining the run-time performance and the low memory usage for which CLIPS is known. The requirements for an object system in CLIPS that includes object-oriented programming and integrated pattern-matching are discussed and various techniques for optimizing the object system and its integration with the pattern-matcher are presented.

  10. Portable pathogen detection system

    DOEpatents

    Colston, Billy W.; Everett, Matthew; Milanovich, Fred P.; Brown, Steve B.; Vendateswaran, Kodumudi; Simon, Jonathan N.

    2005-06-14

    A portable pathogen detection system that accomplishes on-site multiplex detection of targets in biological samples. The system includes: microbead specific reagents, incubation/mixing chambers, a disposable microbead capture substrate, and an optical measurement and decoding arrangement. The basis of this system is a highly flexible Liquid Array that utilizes optically encoded microbeads as the templates for biological assays. Target biological samples are optically labeled and captured on the microbeads, which are in turn captured on an ordered array or disordered array disposable capture substrate and then optically read.

  11. New neural-networks-based 3D object recognition system

    NASA Astrophysics Data System (ADS)

    Abolmaesumi, Purang; Jahed, M.

    1997-09-01

    Three-dimensional object recognition has always been one of the challenging fields in computer vision. In recent years, Ulman and Basri (1991) have proposed that this task can be done by using a database of 2-D views of the objects. The main problem in their proposed system is that the correspondent points should be known to interpolate the views. On the other hand, their system should have a supervisor to decide which class does the represented view belong to. In this paper, we propose a new momentum-Fourier descriptor that is invariant to scale, translation, and rotation. This descriptor provides the input feature vectors to our proposed system. By using the Dystal network, we show that the objects can be classified with over 95% precision. We have used this system to classify the objects like cube, cone, sphere, torus, and cylinder. Because of the nature of the Dystal network, this system reaches to its stable point by a single representation of the view to the system. This system can also classify the similar views to a single class (e.g., for the cube, the system generated 9 different classes for 50 different input views), which can be used to select an optimum database of training views. The system is also very flexible to the noise and deformed views.

  12. 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.

  13. Fluorescence detection system for microfluidic droplets

    NASA Astrophysics Data System (ADS)

    Chen, Binyu; Han, Xiaoming; Su, Zhen; Liu, Quanjun

    2018-05-01

    In microfluidic detection technology, because of the universality of optical methods in laboratory, optical detection is an attractive solution for microfluidic chip laboratory equipment. In addition, the equipment with high stability and low cost can be realized by integrating appropriate optical detection technology on the chip. This paper reports a detection system for microfluidic droplets. Photomultiplier tubes (PMT) is used as a detection device to improve the sensitivity of detection. This system improves the signal to noise ratio by software filtering and spatial filter. The fluorescence intensity is proportional to the concentration of the fluorescence and intensity of the laser. The fluorescence micro droplets of different concentrations can be distinguished by this system.

  14. Statistical methods for convergence detection of multi-objective evolutionary algorithms.

    PubMed

    Trautmann, H; Wagner, T; Naujoks, B; Preuss, M; Mehnen, J

    2009-01-01

    In this paper, two approaches for estimating the generation in which a multi-objective evolutionary algorithm (MOEA) shows statistically significant signs of convergence are introduced. A set-based perspective is taken where convergence is measured by performance indicators. The proposed techniques fulfill the requirements of proper statistical assessment on the one hand and efficient optimisation for real-world problems on the other hand. The first approach accounts for the stochastic nature of the MOEA by repeating the optimisation runs for increasing generation numbers and analysing the performance indicators using statistical tools. This technique results in a very robust offline procedure. Moreover, an online convergence detection method is introduced as well. This method automatically stops the MOEA when either the variance of the performance indicators falls below a specified threshold or a stagnation of their overall trend is detected. Both methods are analysed and compared for two MOEA and on different classes of benchmark functions. It is shown that the methods successfully operate on all stated problems needing less function evaluations while preserving good approximation quality at the same time.

  15. An objective method for measuring face detection thresholds using the sweep steady-state visual evoked response

    PubMed Central

    Ales, Justin M.; Farzin, Faraz; Rossion, Bruno; Norcia, Anthony M.

    2012-01-01

    We introduce a sensitive method for measuring face detection thresholds rapidly, objectively, and independently of low-level visual cues. The method is based on the swept parameter steady-state visual evoked potential (ssVEP), in which a stimulus is presented at a specific temporal frequency while parametrically varying (“sweeping”) the detectability of the stimulus. Here, the visibility of a face image was increased by progressive derandomization of the phase spectra of the image in a series of equally spaced steps. Alternations between face and fully randomized images at a constant rate (3/s) elicit a robust first harmonic response at 3 Hz specific to the structure of the face. High-density EEG was recorded from 10 human adult participants, who were asked to respond with a button-press as soon as they detected a face. The majority of participants produced an evoked response at the first harmonic (3 Hz) that emerged abruptly between 30% and 35% phase-coherence of the face, which was most prominent on right occipito-temporal sites. Thresholds for face detection were estimated reliably in single participants from 15 trials, or on each of the 15 individual face trials. The ssVEP-derived thresholds correlated with the concurrently measured perceptual face detection thresholds. This first application of the sweep VEP approach to high-level vision provides a sensitive and objective method that could be used to measure and compare visual perception thresholds for various object shapes and levels of categorization in different human populations, including infants and individuals with developmental delay. PMID:23024355

  16. Support system, excavation arrangement, and process of supporting an object

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

    Arnold, Bill W.

    2017-08-01

    A support system, an excavation arrangement, and a process of supporting an object are disclosed. The support system includes a weight-bearing device and a camming mechanism positioned below the weight-bearing device. A downward force on the weight-bearing device at least partially secures the camming mechanism to opposing surfaces. The excavation arrangement includes a borehole, a support system positioned within and secured to the borehole, and an object positioned on and supported by the support system. The process includes positioning and securing the support system and positioning the object on the weight-bearing device.

  17. Detection and laser ranging of orbital objects using optical methods

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

    Laser ranging to satellites (SLR) in earth orbit is an established technology used for geodesy, fundamental science and precise orbit determination. A combined active and passive optical measurement system using a single telescope mount is presented which performs precise ranging measurements of retro reflector equipped objects in low earth orbit (LEO). The German Aerospace Center (DLR) runs an observatory in Stuttgart where a system has been assembled completely from commercial off-the-shelf (COTS) components. The visible light directed to the tracking camera is used to perform angular measurements of objects under investigation. This is done astrometrically by comparing the apparent target position with cataloged star positions. First successful satellite laser ranging was demonstrated recently using an optical fiber directing laser pulses onto the astronomical mount. The transmitter operates at a wavelength of 1064 nm with a repetition rate of 3 kHz and pulse energy of 25 μJ. A motorized tip/tilt mount allows beam steering of the collimated beam with μrad accuracy. The returning photons reflected from the object in space are captured with the tracking telescope. A special low aberration beam splitter unit was designed to separate the infrared from visible light. This allows passive optical closed loop tracking and operation of a single photon detector for time of flight measurements at a single telescope simultaneously. The presented innovative design yields to a compact and cost effective but very precise ranging system which allows orbit determination.

  18. Considerations of persistence and security in CHOICES, an object-oriented operating system

    NASA Technical Reports Server (NTRS)

    Campbell, Roy H.; Madany, Peter W.

    1990-01-01

    The current design of the CHOICES persistent object implementation is summarized, and research in progress is outlined. CHOICES is implemented as an object-oriented system, and persistent objects appear to simplify and unify many functions of the system. It is demonstrated that persistent data can be accessed through an object-oriented file system model as efficiently as by an existing optimized commercial file system. The object-oriented file system can be specialized to provide an object store for persistent objects. The problems that arise in building an efficient persistent object scheme in a 32-bit virtual address space that only uses paging are described. Despite its limitations, the solution presented allows quite large numbers of objects to be active simultaneously, and permits sharing and efficient method calls.

  19. Fusion of local and global detection systems to detect tuberculosis in chest radiographs.

    PubMed

    Hogeweg, Laurens; Mol, Christian; de Jong, Pim A; Dawson, Rodney; Ayles, Helen; van Ginneken, Bramin

    2010-01-01

    Automatic detection of tuberculosis (TB) on chest radiographs is a difficult problem because of the diverse presentation of the disease. A combination of detection systems for abnormalities and normal anatomy is used to improve detection performance. A textural abnormality detection system operating at the pixel level is combined with a clavicle detection system to suppress false positive responses. The output of a shape abnormality detection system operating at the image level is combined in a next step to further improve performance by reducing false negatives. Strategies for combining systems based on serial and parallel configurations were evaluated using the minimum, maximum, product, and mean probability combination rules. The performance of TB detection increased, as measured using the area under the ROC curve, from 0.67 for the textural abnormality detection system alone to 0.86 when the three systems were combined. The best result was achieved using the sum and product rule in a parallel combination of outputs.

  20. 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.

  1. l-DOPA and Freezing of Gait in Parkinson’s Disease: Objective Assessment through a Wearable Wireless System

    PubMed Central

    Suppa, Antonio; Kita, Ardian; Leodori, Giorgio; Zampogna, Alessandro; Nicolini, Ettore; Lorenzi, Paolo; Rao, Rosario; Irrera, Fernanda

    2017-01-01

    Freezing of gait (FOG) is a leading cause of falls and fractures in Parkinson’s disease (PD). The episodic and rather unpredictable occurrence of FOG, coupled with the variable response to l-DOPA of this gait disorder, makes the objective evaluation of FOG severity a major clinical challenge in the therapeutic management of patients with PD. The aim of this study was to examine and compare gait, clinically and objectively, in patients with PD, with and without FOG, by means of a new wearable system. We also assessed the effect of l-DOPA on FOG severity and specific spatiotemporal gait parameters in patients with and without FOG. To this purpose, we recruited 28 patients with FOG, 16 patients without FOG, and 16 healthy subjects. In all participants, gait was evaluated clinically by video recordings and objectively by means of the wearable wireless system, during a modified 3-m Timed Up and Go (TUG) test. All patients performed the modified TUG test under and not under dopaminergic therapy (ON and OFF therapy). By comparing instrumental data with the clinical identification of FOG based on offline video-recordings, we also assessed the performance of the wearable system to detect FOG automatically in terms of sensitivity, specificity, positive and negative predictive values, and finally accuracy. TUG duration was longer in patients than in controls, and the amount of gait abnormalities was prominent in patients with FOG compared with those without FOG. l-DOPA improved gait significantly in patients with PD and particularly in patients with FOG mainly by reducing FOG duration and increasing specific spatiotemporal gait parameters. Finally, the overall wireless system performance in automatic FOG detection was characterized by excellent sensitivity (93.41%), specificity (98.51%), positive predictive value (89.55%), negative predictive value (97.31%), and finally accuracy (98.51%). Our study overall provides new information on the beneficial effect of l-DOPA on FOG

  2. Detection of Buried Objects by Means of a SAP Technique: Comparing MUSIC- and SVR-Based Approaches

    NASA Astrophysics Data System (ADS)

    Meschino, S.; Pajewski, L.; Pastorino, M.; Randazzo, A.; Schettini, G.

    2012-04-01

    a suitable threshold from a desired false-alarm rate), to ascribe each window to the ground or to the sought objects. Numerical results are presented, for a test scenario with a circular-section cylinder in a dielectric half-space. Different values of the ground permittivity, target size, and its position with respect to the receiving array, are considered. Preliminary results on the application of MUSIC and SVR to multiple-object localization are reported. [1] H. Jol, Ground Penetrating Radar: Theory and Applications, Elsevier, Amsterdam, NL, 2009. [2] Gross F.B., Smart Antennas for Wireless Communications, McGraw-Hill, New York 2005. [3] S. Meschino, L. Pajewski, G. Schettini, "Use of a Sub-Array Statistical Approach for the Detection of a Buried Object", Near Surface Geophysics, vol. 8(5), pp. 365-375, 2010. [4] M. Pastorino, A. Randazzo, "A Smart Antenna System for Direction of Arrival Estimation based on a Support Vector Regression," IEEE Trans. Antennas Propagat., vol. 53(7), pp. 2161-2168, 2005. [5] M. Di Vico, F. Frezza, L. Pajewski, G. Schettini, "Scattering by a Finite Set of Perfectly Conducting Cylinders Buried in a Dielectric Half-Space: a Spectral-Domain Solution," IEEE Trans. Antennas Propagat., vol. 53(2), pp. 719-727, 2005.

  3. Hot Spot Detection System Using Landsat 8/OLI Data

    NASA Astrophysics Data System (ADS)

    Kato, S.; Nakamura, R.; Oda, A.; Iijima, A.; Kouyama, T.; Iwata, T.

    2015-12-01

    We developed a simple algorithm and a Web-based visualizing system to detect hot spots using Landsat 8 OLI multispectral data as one of the applications of the real-time processing of Landsat 8 data. An empirical equation and radiometric and reflective thresholds were derived to detect hot spots using the OLI data at band 5 (0.865 μm) and band 7 (2.200 μm) based on the increase in spectral radiance at shortwave infrared (SWIR) region due to the emission from objects with high surface temperature. We surveyed typical patterns of surface spectra using the ASTER spectral library to delineate a threshold to distinguish hot spots from background surfaces. To adjust the empirical coefficients of our detection algorithm, we visually inspected the detected hot spots using 6593 Landsat 8 scenes, which cover eastern part of East Asia, taken from January 1, 2014 to December 31, 2014, displayed on a dedicated Web GIS system. Eventually we determined threshold equations which can theoretically detect hot spots at temperatures above 230 °C over isothermal pixels and hot spots as small as 1 m2 at temperatures of 1000 °C as the lowest temperature and the smallest subpixel coverage, respectively, for daytime scenes. The algorithm detected hot spots including wildfires, volcanos, open burnings and factories. 30-m spatial resolution of Landsat 8 enabled to detect wild fires and open burnings accompanied by clearer shapes of fire front lines than MODIS and VIIRS fire products. Although the 16-day revisit cycle of Landsat 8 is too long to effectively find unexpected wildfire or outbreak of eruption, the revisit cycle is enough to monitor temporally stable heat sources, such as continually erupting volcanos and factories. False detection was found over building rooftops, which have relatively smooth surfaces at longer wavelengths, when specular reflection occurred at the satellite overpass.

  4. Automatic detection of Floating Ice at Antarctic Continental Margin from Remotely Sensed Image with Object-oriented Matching

    NASA Astrophysics Data System (ADS)

    Zhao, Z.

    2011-12-01

    Changes in ice sheet and floating ices around that have great significance for global change research. In the context of global warming, rapidly changing of Antarctic continental margin, caving of ice shelves, movement of iceberg are all closely related to climate change and ocean circulation. Using automatic change detection technology to rapid positioning the melting Region of Polar ice sheet and the location of ice drift would not only strong support for Global Change Research but also lay the foundation for establishing early warning mechanism for melting of the polar ice and Ice displacement. This paper proposed an automatic change detection method using object-based segmentation technology. The process includes three parts: ice extraction using image segmentation, object-baed ice tracking, change detection based on similarity matching. An approach based on similarity matching of eigenvector is proposed in this paper, which used area, perimeter, Hausdorff distance, contour, shape and other information of each ice-object. Different time of LANDSAT ETM+ data, Chinese environment disaster satellite HJ1B date, MODIS 1B date are used to detect changes of Floating ice at Antarctic continental margin respectively. We select different time of ETM+ data(January 7, 2003 and January 16, 2003) with the area around Antarctic continental margin near the Lazarev Bay, which is from 70.27454853 degrees south latitude, longitude 12.38573410 degrees to 71.44474167 degrees south latitude, longitude 10.39252222 degrees,included 11628 sq km of Antarctic continental margin area, as a sample. Then we can obtain the area of floating ices reduced 371km2, and the number of them reduced 402 during the time. In addition, the changes of all the floating ices around the margin region of Antarctic within 1200 km are detected using MODIS 1B data. During the time from January 1, 2008 to January 7, 2008, the floating ice area decreased by 21644732 km2, and the number of them reduced by 83080

  5. Detection and Purging of Specular Reflective and Transparent Object Influences in 3d Range Measurements

    NASA Astrophysics Data System (ADS)

    Koch, R.; May, S.; Nüchter, A.

    2017-02-01

    3D laser scanners are favoured sensors for mapping in mobile service robotics at indoor and outdoor applications, since they deliver precise measurements at a wide scanning range. The resulting maps are detailed since they have a high resolution. Based on these maps robots navigate through rough terrain, fulfil advanced manipulation, and inspection tasks. In case of specular reflective and transparent objects, e.g., mirrors, windows, shiny metals, the laser measurements get corrupted. Based on the type of object and the incident angle of the incoming laser beam there are three results possible: a measurement point on the object plane, a measurement behind the object plane, and a measurement of a reflected object. It is important to detect such situations to be able to handle these corrupted points. This paper describes why it is difficult to distinguish between specular reflective and transparent surfaces. It presents a 3DReflection- Pre-Filter Approach to identify specular reflective and transparent objects in point clouds of a multi-echo laser scanner. Furthermore, it filters point clouds from influences of such objects and extract the object properties for further investigations. Based on an Iterative-Closest-Point-algorithm reflective objects are identified. Object surfaces and points behind surfaces are masked according to their location. Finally, the processed point cloud is forwarded to a mapping module. Furthermore, the object surface corners and the type of the surface is broadcasted. Four experiments demonstrate the usability of the 3D-Reflection-Pre-Filter. The first experiment was made in a empty room containing a mirror, the second experiment was made in a stairway containing a glass door, the third experiment was made in a empty room containing two mirrors, the fourth experiment was made in an office room containing a mirror. This paper demonstrate that for single scans the detection of specular reflective and transparent objects in 3D is possible. It

  6. Comparative study of popular objective functions for damping power system oscillations in multimachine system.

    PubMed

    Islam, Naz Niamul; Hannan, M A; Shareef, Hussain; Mohamed, Azah; Salam, M A

    2014-01-01

    Power oscillation damping controller is designed in linearized model with heuristic optimization techniques. Selection of the objective function is very crucial for damping controller design by optimization algorithms. In this research, comparative analysis has been carried out to evaluate the effectiveness of popular objective functions used in power system oscillation damping. Two-stage lead-lag damping controller by means of power system stabilizers is optimized using differential search algorithm for different objective functions. Linearized model simulations are performed to compare the dominant mode's performance and then the nonlinear model is continued to evaluate the damping performance over power system oscillations. All the simulations are conducted in two-area four-machine power system to bring a detailed analysis. Investigated results proved that multiobjective D-shaped function is an effective objective function in terms of moving unstable and lightly damped electromechanical modes into stable region. Thus, D-shape function ultimately improves overall system damping and concurrently enhances power system reliability.

  7. 46 CFR 108.411 - Smoke detection system.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 46 Shipping 4 2010-10-01 2010-10-01 false Smoke detection system. 108.411 Section 108.411 Shipping... EQUIPMENT Fire Extinguishing Systems § 108.411 Smoke detection system. Each smoke accumulator in a smoke detection system must be located on the overhead of the compartment protected by the system in a location...

  8. Toward detecting deception in intelligent systems

    NASA Astrophysics Data System (ADS)

    Santos, Eugene, Jr.; Johnson, Gregory, Jr.

    2004-08-01

    Contemporary decision makers often must choose a course of action using knowledge from several sources. Knowledge may be provided from many diverse sources including electronic sources such as knowledge-based diagnostic or decision support systems or through data mining techniques. As the decision maker becomes more dependent on these electronic information sources, detecting deceptive information from these sources becomes vital to making a correct, or at least more informed, decision. This applies to unintentional disinformation as well as intentional misinformation. Our ongoing research focuses on employing models of deception and deception detection from the fields of psychology and cognitive science to these systems as well as implementing deception detection algorithms for probabilistic intelligent systems. The deception detection algorithms are used to detect, classify and correct attempts at deception. Algorithms for detecting unexpected information rely upon a prediction algorithm from the collaborative filtering domain to predict agent responses in a multi-agent system.

  9. Buried Object Detection Method Using Optimum Frequency Range in Extremely Shallow Underground

    NASA Astrophysics Data System (ADS)

    Sugimoto, Tsuneyoshi; Abe, Touma

    2011-07-01

    We propose a new detection method for buried objects using the optimum frequency response range of the corresponding vibration velocity. Flat speakers and a scanning laser Doppler vibrometer (SLDV) are used for noncontact acoustic imaging in the extremely shallow underground. The exploration depth depends on the sound pressure, but it is usually less than 10 cm. Styrofoam, wood (silver fir), and acrylic boards of the same size, different size styrofoam boards, a hollow toy duck, a hollow plastic container, a plastic container filled with sand, a hollow steel can and an unglazed pot are used as buried objects which are buried in sand to about 2 cm depth. The imaging procedure of buried objects using the optimum frequency range is given below. First, the standardized difference from the average vibration velocity is calculated for all scan points. Next, using this result, underground images are made using a constant frequency width to search for the frequency response range of the buried object. After choosing an approximate frequency response range, the difference between the average vibration velocity for all points and that for several points that showed a clear response is calculated for the final confirmation of the optimum frequency range. Using this optimum frequency range, we can obtain the clearest image of the buried object. From the experimental results, we confirmed the effectiveness of our proposed method. In particular, a clear image of the buried object was obtained when the SLDV image was unclear.

  10. System and method for inventorying multiple remote objects

    DOEpatents

    Carrender, Curtis L.; Gilbert, Ronald W.

    2007-10-23

    A system and method of inventorying multiple objects utilizing a multi-level or a chained radio frequency identification system. The system includes a master tag and a plurality of upper level tags and lower level tags associated with respective objects. The upper and lower level tags communicate with each other and the master tag so that reading of the master tag reveals the presence and absence of upper and lower level tags. In the chained RF system, the upper and lower level tags communicate locally with each other in a manner so that more remote tags that are out of range of some of the upper and lower level tags have their information relayed through adjacent tags to the master tag and thence to a controller.

  11. System and method for inventorying multiple remote objects

    DOEpatents

    Carrender, Curtis L [Morgan Hill, CA; Gilbert, Ronald W [Morgan Hill, CA

    2009-12-29

    A system and method of inventorying multiple objects utilizing a multi-level or a chained radio frequency identification system. The system includes a master tag and a plurality of upper level tags and lower level tags associated with respective objects. The upper and lower level tags communicate with each other and the master tag so that reading of the master tag reveals the presence and absence of upper and lower level tags. In the chained RF system, the upper and lower level tags communicate locally with each other in a manner so that more remote tags that are out of range of some of the upper and lower level tags have their information relayed through adjacent tags to the master tag and thence to a controller.

  12. Atmospheric Blocking and Intercomparison of Objective Detection Methods: Flow Field Characteristics

    NASA Astrophysics Data System (ADS)

    Pinheiro, M. C.; Ullrich, P. A.; Grotjahn, R.

    2017-12-01

    A number of objective methods for identifying and quantifying atmospheric blocking have been developed over the last couple of decades, but there is variable consensus on the resultant blocking climatology. This project examines blocking climatologies as produced by three different methods: two anomaly-based methods, and the geopotential height gradient method of Tibaldi and Molteni (1990). The results highlight the differences in blocking that arise from the choice of detection method, with emphasis on the physical characteristics of the flow field and the subsequent effects on the blocking patterns that emerge.

  13. Penalized likelihood and multi-objective spatial scans for the detection and inference of irregular clusters

    PubMed Central

    2010-01-01

    Background Irregularly shaped spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff's spatial scan statistics have been used to control the excessive freedom of the shape of clusters. Penalty functions based on cluster geometry and non-connectivity have been proposed recently. Another approach involves the use of a multi-objective algorithm to maximize two objectives: the spatial scan statistics and the geometric penalty function. Results & Discussion We present a novel scan statistic algorithm employing a function based on the graph topology to penalize the presence of under-populated disconnection nodes in candidate clusters, the disconnection nodes cohesion function. A disconnection node is defined as a region within a cluster, such that its removal disconnects the cluster. By applying this function, the most geographically meaningful clusters are sifted through the immense set of possible irregularly shaped candidate cluster solutions. To evaluate the statistical significance of solutions for multi-objective scans, a statistical approach based on the concept of attainment function is used. In this paper we compared different penalized likelihoods employing the geometric and non-connectivity regularity functions and the novel disconnection nodes cohesion function. We also build multi-objective scans using those three functions and compare them with the previous penalized likelihood scans. An application is presented using comprehensive state-wide data for Chagas' disease in puerperal women in Minas Gerais state, Brazil. Conclusions We show that, compared to the other single-objective algorithms, multi-objective scans present better performance, regarding power, sensitivity and positive predicted value. The multi-objective non-connectivity scan is faster and better suited for the detection of moderately irregularly

  14. Finding and recognizing objects in natural scenes: complementary computations in the dorsal and ventral visual systems

    PubMed Central

    Rolls, Edmund T.; Webb, Tristan J.

    2014-01-01

    Searching for and recognizing objects in complex natural scenes is implemented by multiple saccades until the eyes reach within the reduced receptive field sizes of inferior temporal cortex (IT) neurons. We analyze and model how the dorsal and ventral visual streams both contribute to this. Saliency detection in the dorsal visual system including area LIP is modeled by graph-based visual saliency, and allows the eyes to fixate potential objects within several degrees. Visual information at the fixated location subtending approximately 9° corresponding to the receptive fields of IT neurons is then passed through a four layer hierarchical model of the ventral cortical visual system, VisNet. We show that VisNet can be trained using a synaptic modification rule with a short-term memory trace of recent neuronal activity to capture both the required view and translation invariances to allow in the model approximately 90% correct object recognition for 4 objects shown in any view across a range of 135° anywhere in a scene. The model was able to generalize correctly within the four trained views and the 25 trained translations. This approach analyses the principles by which complementary computations in the dorsal and ventral visual cortical streams enable objects to be located and recognized in complex natural scenes. PMID:25161619

  15. An Evaluation of Pixel-Based Methods for the Detection of Floating Objects on the Sea Surface

    NASA Astrophysics Data System (ADS)

    Borghgraef, Alexander; Barnich, Olivier; Lapierre, Fabian; Van Droogenbroeck, Marc; Philips, Wilfried; Acheroy, Marc

    2010-12-01

    Ship-based automatic detection of small floating objects on an agitated sea surface remains a hard problem. Our main concern is the detection of floating mines, which proved a real threat to shipping in confined waterways during the first Gulf War, but applications include salvaging, search-and-rescue operation, perimeter, or harbour defense. Detection in infrared (IR) is challenging because a rough sea is seen as a dynamic background of moving objects with size order, shape, and temperature similar to those of the floating mine. In this paper we have applied a selection of background subtraction algorithms to the problem, and we show that the recent algorithms such as ViBe and behaviour subtraction, which take into account spatial and temporal correlations within the dynamic scene, significantly outperform the more conventional parametric techniques, with only little prior assumptions about the physical properties of the scene.

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

    PubMed Central

    Van Weyenberg, Stephanie; Van Nuffel, Annelies; Lauwers, Ludwig; Vangeyte, Jürgen

    2017-01-01

    Simple Summary Most prototypes of systems to automatically detect lameness in dairy cattle are still not available on the market. Estimating their potential adoption rate could support developers in defining development goals towards commercially viable and well-adopted systems. We simulated the potential market shares of such prototypes to assess the effect of altering the system cost and detection performance on the potential adoption rate. We found that system cost and lameness detection performance indeed substantially influence the potential adoption rate. In order for farmers to prefer automatic detection over current visual detection, the usefulness that farmers attach to a system with specific characteristics should be higher than that of visual detection. As such, we concluded that low system costs and high detection performances are required before automatic lameness detection systems become applicable in practice. Abstract 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

  17. After-effects of TFT-LCD display polarity and display colour on the detection of low-contrast objects.

    PubMed

    Mayr, Susanne; Buchner, Axel

    2010-07-01

    Participants performed a word-non-word discrimination task within a car control display emulated on a thin film transistor liquid-crystal display (TFT-LCD). The task simulated an information read-out from a TFT-LCD-based instrument panel. Subsequently, participants performed a low-contrast object detection task that simulated the detection of objects during night-time driving. In experiment 1, words/non-words were presented black-on-white (positive polarity) or white-on-black (negative polarity). In experiments 2 and 3, display colour was additionally manipulated. A positive polarity advantage in the discrimination task was consistently observed. In contrast, positive displays interfered more than negative displays with subsequent detection. The detrimental after-effect of positive polarity displays was strong with white and blue, reduced with amber and absent with red displays. Subjective measures showed a preference for blue over red, but a slight advantage for amber over blue. Implications for TFT-LCD design are derived from the results. STATEMENT OF RELEVANCE: When using TFT-LCDs as car instrument panels, positive polarity red TFT-LCDs are very likely to lead to good instrument readability while at the same time minimising - relative to other colours - the negative effects of an illuminated display on low-contrast object detection during night-time driving.

  18. Multi-transmitter multi-receiver null coupled systems for inductive detection and characterization of metallic objects

    NASA Astrophysics Data System (ADS)

    Smith, J. Torquil; Morrison, H. Frank; Doolittle, Lawrence R.; Tseng, Hung-Wen

    2007-03-01

    Equivalent dipole polarizabilities are a succinct way to summarize the inductive response of an isolated conductive body at distances greater than the scale of the body. Their estimation requires measurement of secondary magnetic fields due to currents induced in the body by time varying magnetic fields in at least three linearly independent (e.g., orthogonal) directions. Secondary fields due to an object are typically orders of magnitude smaller than the primary inducing fields near the primary field sources (transmitters). Receiver coils may be oriented orthogonal to primary fields from one or two transmitters, nulling their response to those fields, but simultaneously nulling to fields of additional transmitters is problematic. If transmitter coils are constructed symmetrically with respect to inversion in a point, their magnetic fields are symmetric with respect to that point. If receiver coils are operated in pairs symmetric with respect to inversion in the same point, then their differenced output is insensitive to the primary fields of any symmetrically constructed transmitters, allowing nulling to three (or more) transmitters. With a sufficient number of receivers pairs, object equivalent dipole polarizabilities can be estimated in situ from measurements at a single instrument sitting, eliminating effects of inaccurate instrument location on polarizability estimates. The method is illustrated with data from a multi-transmitter multi-receiver system with primary field nulling through differenced receiver pairs, interpreted in terms of principal equivalent dipole polarizabilities as a function of time.

  19. Space weathering on near-Earth objects investigated by neutral-particle detection

    NASA Astrophysics Data System (ADS)

    Plainaki, C.; Milillo, A.; Orsini, S.; Mura, A.; De Angelis, E.; Di Lellis, A. M.; Dotto, E.; Livi, S.; Mangano, V.; Massetti, S.; Palumbo, M. E.

    2009-03-01

    The ion-sputtering (IS) process is active in many planetary environments in the solar system where plasma precipitates directly on the surface (for instance, Mercury, Moon and Europa). In particular, solar wind sputtering is one of the most important agents for the surface erosion of a near-Earth object (NEO), acting together with other surface release processes, such as photon stimulated desorption (PSD), thermal desorption (TD) and micrometeoroid impact vaporization (MIV). The energy distribution of the IS-released neutrals peaks at a few eVs and extends up to hundreds of eVs. Since all other release processes produce particles of lower energies, the presence of neutral atoms in the energy range above 10 eV and below a few keVs (sputtered high-energy atoms (SHEA)) identifies the IS process. SHEA easily escape from the NEO, due to NEO's extremely weak gravity. Detection and analysis of SHEA will give important information on surface-loss processes as well as on surface elemental composition. The investigation of the active release processes, as a function of the external conditions and the NEO surface properties, is crucial for obtaining a clear view of the body's present loss rate as well as for getting clues on its evolution, which depends significantly on space weather. In this work, an attempt to analyze processes that take place on the surface of these small airless bodies, as a result of their exposure to the space environment, has been realized. For this reason, a new space weathering model (space weathering on NEO-SPAWN) is presented. Moreover, an instrument concept of a neutral-particle analyzer specifically designed for the measurement of neutral density and the detection of SHEA from a NEO is proposed.

  20. Space weathering on near-Earth objects investigated by neutral-particle detection

    NASA Astrophysics Data System (ADS)

    Plainaki, C.; Milillo, A.; Orsini, S.; Mura, A.; de Angelis, E.; di Lellis, A. M.; Dotto, E.; Livi, S.; Mangano, V.; Palumbo, M. E.

    2009-04-01

    The ion-sputtering (IS) process is active in many planetary environments in the solar system where plasma precipitates directly on the surface (for instance, Mercury, Moon and Europa). In particular, solar wind sputtering is one of the most important agents for the surface erosion of a near-Earth object (NEO), acting together with other surface release processes, such as photon stimulated desorption (PSD), thermal desorption (TD) and micrometeoroid impact vaporization (MIV). The energy distribution of the IS-released neutrals peaks at a few eVs and extends up to hundreds of eVs. Since all other release processes produce particles of lower energies, the presence of neutral atoms in the energy range above 10 eV and below a few keVs (sputtered high-energy atoms (SHEA)) identifies the IS process. SHEA easily escape from the NEO, due to NEO's extremely weak gravity. Detection and analysis of SHEA will give important information on surface-loss processes as well as on surface elemental composition. The investigation of the active release processes, as a function of the external conditions and the NEO surface properties, is crucial for obtaining a clear view of the body's present loss rate as well as for getting clues on its evolution, which depends significantly on space weather. In this work, an attempt to analyze processes that take place on the surface of these small airless bodies, as a result of their exposure to the space environment, has been realized. For this reason, a new space weathering model (space weathering on NEO-SPAWN) is presented. Moreover, an instrument concept of a neutral-particle analyzer specifically designed for the measurement of neutral density and the detection of SHEA from a NEO is proposed.

  1. Objective detection and forecasting of Clear-Air Turbulence (CAT): A status report

    NASA Technical Reports Server (NTRS)

    Keller, John L.

    1988-01-01

    Clear-air turbulence has become the largest single cause of weather-related injuries occurring in commercial carriers at cruising altitudes. A technique for objective operational CAT detection (the SCATR index) has been formulated. Its physical basis ties CAT to total energy dissipation as a response to meso- and synoptic-scale dynamical processes associated with upper-level jet stream/frontal zones. Early case studies using properly analyzed routine RAOB rawinsonde sounding data have shown promise.

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

    NASA Technical Reports Server (NTRS)

    McDowell, Mark; Gray, Elizabeth

    2009-01-01

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

  3. Integrated multisensor perimeter detection systems

    NASA Astrophysics Data System (ADS)

    Kent, P. J.; Fretwell, P.; Barrett, D. J.; Faulkner, D. A.

    2007-10-01

    The report describes the results of a multi-year programme of research aimed at the development of an integrated multi-sensor perimeter detection system capable of being deployed at an operational site. The research was driven by end user requirements in protective security, particularly in threat detection and assessment, where effective capability was either not available or prohibitively expensive. Novel video analytics have been designed to provide robust detection of pedestrians in clutter while new radar detection and tracking algorithms provide wide area day/night surveillance. A modular integrated architecture based on commercially available components has been developed. A graphical user interface allows intuitive interaction and visualisation with the sensors. The fusion of video, radar and other sensor data provides the basis of a threat detection capability for real life conditions. The system was designed to be modular and extendable in order to accommodate future and legacy surveillance sensors. The current sensor mix includes stereoscopic video cameras, mmWave ground movement radar, CCTV and a commercially available perimeter detection cable. The paper outlines the development of the system and describes the lessons learnt after deployment in a pilot trial.

  4. 46 CFR 108.405 - Fire detection system.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 46 Shipping 4 2013-10-01 2013-10-01 false Fire detection system. 108.405 Section 108.405 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.405 Fire detection system. (a) Each fire detection system and...

  5. 46 CFR 108.405 - Fire detection system.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 46 Shipping 4 2011-10-01 2011-10-01 false Fire detection system. 108.405 Section 108.405 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.405 Fire detection system. (a) Each fire detection system and...

  6. 46 CFR 108.405 - Fire detection system.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 46 Shipping 4 2014-10-01 2014-10-01 false Fire detection system. 108.405 Section 108.405 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.405 Fire detection system. (a) Each fire detection system and...

  7. 46 CFR 108.405 - Fire detection system.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 46 Shipping 4 2012-10-01 2012-10-01 false Fire detection system. 108.405 Section 108.405 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.405 Fire detection system. (a) Each fire detection system and...

  8. Using evolutionary computation to optimize an SVM used in detecting buried objects in FLIR imagery

    NASA Astrophysics Data System (ADS)

    Paino, Alex; Popescu, Mihail; Keller, James M.; Stone, Kevin

    2013-06-01

    In this paper we describe an approach for optimizing the parameters of a Support Vector Machine (SVM) as part of an algorithm used to detect buried objects in forward looking infrared (FLIR) imagery captured by a camera installed on a moving vehicle. The overall algorithm consists of a spot-finding procedure (to look for potential targets) followed by the extraction of several features from the neighborhood of each spot. The features include local binary pattern (LBP) and histogram of oriented gradients (HOG) as these are good at detecting texture classes. Finally, we project and sum each hit into UTM space along with its confidence value (obtained from the SVM), producing a confidence map for ROC analysis. In this work, we use an Evolutionary Computation Algorithm (ECA) to optimize various parameters involved in the system, such as the combination of features used, parameters on the Canny edge detector, the SVM kernel, and various HOG and LBP parameters. To validate our approach, we compare results obtained from an SVM using parameters obtained through our ECA technique with those previously selected by hand through several iterations of "guess and check".

  9. Computer systems for automatic earthquake detection

    USGS Publications Warehouse

    Stewart, S.W.

    1974-01-01

    U.S Geological Survey seismologists in Menlo park, California, are utilizing the speed, reliability, and efficiency of minicomputers to monitor seismograph stations and to automatically detect earthquakes. An earthquake detection computer system, believed to be the only one of its kind in operation, automatically reports about 90 percent of all local earthquakes recorded by a network of over 100 central California seismograph stations. The system also monitors the stations for signs of malfunction or abnormal operation. Before the automatic system was put in operation, all of the earthquakes recorded had to be detected by manually searching the records, a time-consuming process. With the automatic detection system, the stations are efficiently monitored continuously. 

  10. APDS: Autonomous Pathogen Detection System

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

    Langlois, R G; Brown, S; Burris, L

    An early warning system to counter bioterrorism, the Autonomous Pathogen Detection System (APDS) continuously monitors the environment for the presence of biological pathogens (e.g., anthrax) and once detected, it sounds an alarm much like a smoke detector warns of a fire. Long before September 11, 2001, this system was being developed to protect domestic venues and events including performing arts centers, mass transit systems, major sporting and entertainment events, and other high profile situations in which the public is at risk of becoming a target of bioterrorist attacks. Customizing off-the-shelf components and developing new components, a multidisciplinary team developed APDS,more » a stand-alone system for rapid, continuous monitoring of multiple airborne biological threat agents in the environment. The completely automated APDS samples the air, prepares fluid samples in-line, and performs two orthogonal tests: immunoassay and nucleic acid detection. When compared to competing technologies, APDS is unprecedented in terms of flexibility and system performance.« less

  11. Automated seizure detection systems and their effectiveness for each type of seizure.

    PubMed

    Ulate-Campos, A; Coughlin, F; Gaínza-Lein, M; Fernández, I Sánchez; Pearl, P L; Loddenkemper, T

    2016-08-01

    Epilepsy affects almost 1% of the population and most of the approximately 20-30% of patients with refractory epilepsy have one or more seizures per month. Seizure detection devices allow an objective assessment of seizure frequency and a treatment tailored to the individual patient. A rapid recognition and treatment of seizures through closed-loop systems could potentially decrease morbidity and mortality in epilepsy. However, no single detection device can detect all seizure types. Therefore, the choice of a seizure detection device should consider the patient-specific seizure semiologies. This review of the literature evaluates seizure detection devices and their effectiveness for different seizure types. Our aim is to summarize current evidence, offer suggestions on how to select the most suitable seizure detection device for each patient and provide guidance to physicians, families and researchers when choosing or designing seizure detection devices. Further, this review will guide future prospective validation studies. Copyright © 2016. Published by Elsevier Ltd.

  12. Simple Systems for Detecting Spacecraft Meteoroid Punctures

    NASA Technical Reports Server (NTRS)

    Hall, Stephen B.

    2004-01-01

    A report describes proposed systems to be installed in spacecraft to detect punctures by impinging meteoroids or debris. Relative to other systems that have been used for this purpose, the proposed systems would be simpler and more adaptable, and would demand less of astronauts attention and of spacecraft power and computing resources. The proposed systems would include a thin, hollow, hermetically sealed panel containing an inert fluid at a pressure above the spacecraft cabin pressure. A transducer would monitor the pressure in the panel. It is assumed that an impinging object that punctures the cabin at the location of the panel would also puncture the panel. Because the volume of the panel would be much smaller than that of the cabin, the panel would lose its elevated pressure much faster than the cabin would lose its lower pressure. The transducer would convert the rapid pressure drop to an electrical signal that could trigger an alarm. Hence, the system would provide an immediate indication of the approximate location of a small impact leak, possibly in time to take corrective action before a large loss of cabin pressure could occur.

  13. Con-Text: Text Detection for Fine-grained Object Classification.

    PubMed

    Karaoglu, Sezer; Tao, Ran; van Gemert, Jan C; Gevers, Theo

    2017-05-24

    This work focuses on fine-grained object classification using recognized scene text in natural images. While the state-of-the-art relies on visual cues only, this paper is the first work which proposes to combine textual and visual cues. Another novelty is the textual cue extraction. Unlike the state-of-the-art text detection methods, we focus more on the background instead of text regions. Once text regions are detected, they are further processed by two methods to perform text recognition i.e. ABBYY commercial OCR engine and a state-of-the-art character recognition algorithm. Then, to perform textual cue encoding, bi- and trigrams are formed between the recognized characters by considering the proposed spatial pairwise constraints. Finally, extracted visual and textual cues are combined for fine-grained classification. The proposed method is validated on four publicly available datasets: ICDAR03, ICDAR13, Con-Text and Flickr-logo. We improve the state-of-the-art end-to-end character recognition by a large margin of 15% on ICDAR03. We show that textual cues are useful in addition to visual cues for fine-grained classification. We show that textual cues are also useful for logo retrieval. Adding textual cues outperforms visual- and textual-only in fine-grained classification (70.7% to 60.3%) and logo retrieval (57.4% to 54.8%).

  14. 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.

  15. Investigation of small solar system objects with the space telescope

    NASA Technical Reports Server (NTRS)

    Morrison, D.

    1979-01-01

    The application of the space telescope (ST) to study small objects in the solar system in order to understand the birth and the early evolution of the solar system is discussed. The upper size limit of the small bodies is defined as approximately 5000 km and includes planetary satellites, planetary rings, asteroids, and comets.The use of the astronomical instruments aboard the ST, such as the faint object camera, ultraviolet and infrared spectrometers, and spectrophotometers, to study the small solar system objects is discussed.

  16. Intrusion Detection in Control Systems using Sequence Characteristics

    NASA Astrophysics Data System (ADS)

    Kiuchi, Mai; Onoda, Takashi

    Intrusion detection is considered effective in control systems. Sequences of the control application behavior observed in the communication, such as the order of the control device to be controlled, are important in control systems. However, most intrusion detection systems do not effectively reflect sequences in the application layer into the detection rules. In our previous work, we considered utilizing sequences for intrusion detection in control systems, and demonstrated the usefulness of sequences for intrusion detection. However, manually writing the detection rules for a large system can be difficult, so using machine learning methods becomes feasible. Also, in the case of control systems, there have been very few observed cyber attacks, so we have very little knowledge of the attack data that should be used to train the intrusion detection system. In this paper, we use an approach that combines CRF (Conditional Random Field) considering the sequence of the system, thus able to reflect the characteristics of control system sequences into the intrusion detection system, and also does not need the knowledge of attack data to construct the detection rules.

  17. Object-based detection of vehicles using combined optical and elevation data

    NASA Astrophysics Data System (ADS)

    Schilling, Hendrik; Bulatov, Dimitri; Middelmann, Wolfgang

    2018-02-01

    The detection of vehicles is an important and challenging topic that is relevant for many applications. In this work, we present a workflow that utilizes optical and elevation data to detect vehicles in remotely sensed urban data. This workflow consists of three consecutive stages: candidate identification, classification, and single vehicle extraction. Unlike in most previous approaches, fusion of both data sources is strongly pursued at all stages. While the first stage utilizes the fact that most man-made objects are rectangular in shape, the second and third stages employ machine learning techniques combined with specific features. The stages are designed to handle multiple sensor input, which results in a significant improvement. A detailed evaluation shows the benefits of our workflow, which includes hand-tailored features; even in comparison with classification approaches based on Convolutional Neural Networks, which are state of the art in computer vision, we could obtain a comparable or superior performance (F1 score of 0.96-0.94).

  18. Acoustic signature recognition technique for Human-Object Interactions (HOI) in persistent surveillance systems

    NASA Astrophysics Data System (ADS)

    Alkilani, Amjad; Shirkhodaie, Amir

    2013-05-01

    Handling, manipulation, and placement of objects, hereon called Human-Object Interaction (HOI), in the environment generate sounds. Such sounds are readily identifiable by the human hearing. However, in the presence of background environment noises, recognition of minute HOI sounds is challenging, though vital for improvement of multi-modality sensor data fusion in Persistent Surveillance Systems (PSS). Identification of HOI sound signatures can be used as precursors to detection of pertinent threats that otherwise other sensor modalities may miss to detect. In this paper, we present a robust method for detection and classification of HOI events via clustering of extracted features from training of HOI acoustic sound waves. In this approach, salient sound events are preliminary identified and segmented from background via a sound energy tracking method. Upon this segmentation, frequency spectral pattern of each sound event is modeled and its features are extracted to form a feature vector for training. To reduce dimensionality of training feature space, a Principal Component Analysis (PCA) technique is employed to expedite fast classification of test feature vectors, a kd-tree and Random Forest classifiers are trained for rapid classification of training sound waves. Each classifiers employs different similarity distance matching technique for classification. Performance evaluations of classifiers are compared for classification of a batch of training HOI acoustic signatures. Furthermore, to facilitate semantic annotation of acoustic sound events, a scheme based on Transducer Mockup Language (TML) is proposed. The results demonstrate the proposed approach is both reliable and effective, and can be extended to future PSS applications.

  19. 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...

  20. Object-oriented biomedical system modelling--the language.

    PubMed

    Hakman, M; Groth, T

    1999-11-01

    The paper describes a new object-oriented biomedical continuous system modelling language (OOBSML). It is fully object-oriented and supports model inheritance, encapsulation, and model component instantiation and behaviour polymorphism. Besides the traditional differential and algebraic equation expressions the language includes also formal expressions for documenting models and defining model quantity types and quantity units. It supports explicit definition of model input-, output- and state quantities, model components and component connections. The OOBSML model compiler produces self-contained, independent, executable model components that can be instantiated and used within other OOBSML models and/or stored within model and model component libraries. In this way complex models can be structured as multilevel, multi-component model hierarchies. Technically the model components produced by the OOBSML compiler are executable computer code objects based on distributed object and object request broker technology. This paper includes both the language tutorial and the formal language syntax and semantic description.