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American Control conference

作者： Ion Matei Saigopal Nelaturi Jeng Ping Lu Julie A. Bert Lara S. Crawford Eugene Chow System Sciences Laboratory at Palo Alto Research Center (PARC) Electronic Materials and Devices Laboratory at Palo Alto Research Center (PARC)

ISBN: (纸本)9781509045839

We address the problem of position control of micro-chips (chiplets) immersed in dielectric fluid. An electric field, shaped by controlling the voltages of spiral shaped electrodes, is used to reliably and accurately transport and position chiplets using dielectrophoretic forces. A lumped, capacitive based (nonlinear) motion model is used to generate an open loop control policy. The open loop policy is generated using a one step model predictive control approach. By exploiting the spatial symmetry and periodicity of the open loop control solution, a real-time control scheme is designed by applying simple algebraic operations to a base function defined on a finite domain. The chiplet position is tracked using image processing algorithms. We demonstrate the validity of our approach by describing an experimental result, where real-time control is used to move a chiplet for 1000μm in a controlled manner.

关键词： problem position control Position control Printing Electronics Real time control Open loop systems Standing Orders image processing algorithm manufacturing method time monitoring Periodicity

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Graph Colouring as a Challenge Problem for Dynamic Graph processing on Distributed systems 16

Graph Colouring as a Challenge Problem for Dynamic Graph Pro...

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International conference on High Performance Computing, Networking, Storage and Analysis (SC)

作者： Sallinen, Scott Iwabuchi, Keita Poudel, Suraj Gokhale, Maya Ripeanu, Matei Pearce, Roger Lawrence Livermore Natl Lab Livermore CA 94550 USA Univ British Columbia Vancouver BC Canada Tokyo Inst Technol Tokyo Japan Univ Alabama Birmingham Birmingham AL USA

ISBN: (纸本)9781467388153

An unprecedented growth in data generation is taking place. Data about larger dynamic systems is being accumulated, capturing finer granularity events, and thus processing requirements are increasingly approaching real-time. To keep up, data-analytics pipelines need to be viable at massive scale, and switch away from static, offline scenarios to support fully online analysis of dynamic systems. This paper uses a challenge problem, graph colouring, to explore massive-scale analytics for dynamic graph processing. We present an event-based infrastructure, and a novel, online, distributed graph colouring algorithm. Our implementation for colouring static graphs, used as a performance baseline, is up to an order of magnitude faster than previous results and handles massive graphs with over 257 billion edges. Our framework supports dynamic graph colouring with performance at large scale better than GraphLab's static analysis. Our experience indicates that online solutions are feasible, and can be more efficient than those based on snapshotting.

关键词： Heuristic algorithms Color image color analysis Algorithm design and analysis Runtime image edge detection Training Algorithm design and analysis Edge detection colored graph image colour analysis Runtime Heuristic algorithms Distributed systems Functional training Color data generation

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Lip Shape Based Emotion Identification 24

Lip Shape Based Emotion Identification

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24th Signal processing and Communication Application conference (SIU)

作者： Gul, Nuray Tora, Hakan Atilim Univ Elekt Elekt Muhendisligi Bolumu Ankara Turkey

ISBN: (纸本)9781509016792

Emotion recognition systems have an important role to play in the human-computer interactive applications (HCI). These systems are using facial features of face images and they are verifying or identifying the emotions. In this study, emotion identification algorithms are improved by using just mouth region features of a face. Region of interest (mouth region) is detected by Viola-Jones algorithms from video frames which are including different emotional face expressions. Outer boundaries of lip shapes are extracted by manually and calculated the scalar Fourier Descriptors (FDs) of the boundaries. Classification and recognition of the emotions is presented according to scalar FDs of lip contours. Test results are obtained as 93.9 % accuracy rate for scalar FDs.

关键词： Fourier Descriptors image processing object recognition Emotion identification Lip Contour

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A Formal Algebra Implementation for Distributed image and Video Stream processing 16

A Formal Algebra Implementation for Distributed Image and Vi...

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10th International conference on Distributed Smart Cameras (ICDSC)

作者： Helala, Mohamed A. Pu, Ken Q. Qureshi, Faisal Z. Univ Ontario Inst Technol Fac Sci Oshawa ON Canada

ISBN: (纸本)9781450347860

We are interested in building scalable computer vision systems for distributed processing of big visual data. We apply data streaming concepts, namely stream algebra operators, which have been proven effective in the database literature. The operators collectively form an algebra over data streams. The algebra has well defined semantics. It naturally describes online computer vision algorithms and their feedback control and tuning algorithms. In this work, we present the first implementation of such algebra at large scale. Our implementation provides a high level programming interface for constructing and executing vision workflow graphs while hiding the data transfer and concurrency details. It also allows feedback control and dynamic reconfiguration of vision algorithms. A case study is discussed showing a streaming workflow for online lane and road boundary detection and describing the flexibility and effectiveness of the algebra for building complex distributed applications.

关键词： stream algebra workflow graphs programming frameworks distributed vision processing

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Neuroimage-based clinical prediction using machine learning tools

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INTERNATIONAL JOURNAL OF IMAGING systems AND TECHNOLOGY 2017年第1期27卷 89-97页

作者： Demirhan, Ayse Gazi Univ Elect & Elect Engn Fac Technol Ankara Turkey

Classification of structural brain magnetic resonance (MR) images is a crucial task for many neurological phenotypes that machine learning tools are increasingly developed and applied to solve this problem in recent years. In this study binary classification of T1-weighted structural brain MR images are performed using state-of-the-art machine learning algorithms when there is no information about the clinical context or specifics of neuroimaging. image derived features and clinical labels that are provided by the International conference on Medical image Computing and Computer-Assisted Intervention 2014 machine learning challenge are used. These morphological summary features are obtained from four different datasets (each N > 70) with clinically relevant phenotypes and automatically extracted from the MR imaging scans using FreeSurfer, a freely distributed brain MR image processing software package. Widely used machine learning tools, namely;back-propagation neural network, self-organizing maps, support vector machines and k-nearest neighbors are used as classifiers. Clinical prediction accuracy is obtained via cross-validation on the training data (N = 150) and predictions are made on the test data (N = 100). Classification accuracy, the fraction of cases where prediction is accurate and area under the ROC curve are used as the performance metrics. Accuracy and area under curve metrics are used for tuning the training hyperparameters and the evaluation of the performance of the classifiers. Performed experiments revealed that support vector machines show a better success compared to the other methods on clinical predictions using summary morphological features in the absence of any information about the phenotype. Prediction accuracy would increase greatly if contextual information is integrated into the system. (C) 2017 Wiley Periodicals, Inc.

关键词： structural brain MR images image classification morphological features clinical prediction machine learning

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Design of Simulation Platform for Missile-borne SAR Imaging 8

Design of Simulation Platform for Missile-borne SAR Imaging

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8th International conference on Intelligent Human-Machine systems and Cybernetics (IHMSC)

作者： Chen, Qi Zhu, Mingbo Li, Xiangping Guo, Tao Zou, Xiaohai Naval Aeronaut & Astronaut Univ Dept Elect & Informat Engn Yantai Peoples R China CEMEE State Key Lab Luoyang Peoples R China

ISBN: (纸本)9781509007684

Missile-borne synthetic aperture radar (SAR) imaging system is built up according to actual working principle, it uses the input data and embedded algorithms to simulate echo, then generate SAR image. Relevant algorithms is analyzed, a SAR echo simulation method based on graphic processing unit (GPU) acceleration is presented to satisfy the request of real-time. Simulation platform realized by MATLAB GUI turns out to be reliable and interactive, it can meet the demand for missile-borne SAR system test and development, and has some practical value.

关键词： Synthetic aperture radar (SAR) Graphic processing unit (GPU) Simulation platform Interactive

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Target Detection in Hyperspectral images 24

Target Detection in Hyperspectral Images

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24th Signal processing and Communication Application conference (SIU)

作者： Karakaya, Ahmet Yuksel, Seniha Esen Aselsan Ankara Turkey Hacettepe Univ Elekt & Elekt Muhendisligi Bolumu Ankara Turkey

ISBN: (纸本)9781509016792

Target detection in hyperspectral images is important in many applications including search and rescue operations, defense systems, mineral exploration, mine detection and border security. In this study, the goal is to detect the nine sub-pixel targets, from seven different materials, that are placed around the town. For this purpose, eight hyperspectral target detection algorithms are compared and the three most successful algorithms are fused together. The results are compared with ROC curves, and it is found that the fusion of signed ACE, CEM and AMSD algorithms can achieve very successfull results in comparison to the other algorithms.

关键词： hyperspectral image target detection

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Zero Resource Anti-Spoofing Detection for Unit Selection Based Synthetic Speech using image Spectrogram Artifacts

Zero Resource Anti-Spoofing Detection for Unit Selection Bas...

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Asia-Pacific Signal and Information processing Association Annual Summit and conference (APSIPA)

作者： Leow, Su Jun Chng, Eng Siong Lee, Chin-hui Nanyang Technol Univ Singapore Singapore Georgia Inst Technol Atlanta GA 30332 USA

ISBN: (纸本)9789881476821

Synthesized speech poses a serious threat to speaker verification systems, which is aggravated by speech synthesis systems becoming more freely available and easily adaptable to a target speaker. This motivated research into synthetic speech detection to circumvent the threat. Although current algorithms are effective in the detection of HMM-based speech synthesizers, unit selection based speech synthesizers remain a serious threat due to its ability to generate spoofing speech which easily overcame existing detectors. Current error rates for their detection is a lot higher than that obtained for other spoofing methods. This paper proposes a detection algorithm to counter unit selection based synthesis speech. It is free of training and exploits presence of artifacts in image spectrogram to perform detection. To the best of our knowledge, this is the first attempt targeted for unit selection based synthesis speech. Experimental results show the effectiveness of the proposed approach.

关键词： Speech synthesis

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Road Sign Recognition System on Raspberry Pi

Road Sign Recognition System on Raspberry Pi

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IEEE Long Island systems, Applications and Technology conference (LISAT)

作者： Bilgin, Enis Robila, Stefan Montclair State Univ Dept Comp Sci Montclair NJ 07043 USA

ISBN: (纸本)9781467384902

Digital image processing, i.e. the use of computer systems to process pictures, has applications in many fields, including of medicine, space exploration, geology and oceanography and continues to increase in its applicability. The main objective of this paper is to demonstrate the ability of image processing algorithms on a small computing platform. Specifically we created a road sign recognition system based on an embedded system that reads and recognizes speed signs. The paper describes the characteristics of speed signs, requirements and difficulties behind implementing a real-time base system with embedded system, and how to deal with numbers using image processing techniques based on shape and dimension analysis. The paper also shows the techniques used for classification and recognition. Color analysis also plays a specifically important role in many other different applications for road sign detection, this paper points to many problems regarding stability of color detection due to daylight conditions, so absence of color model can led a better solution. In this project lightweight techniques were mainly used due to limitation of real-time based application and Raspberry Pi capabilities. Raspberry Pi is the main target for the implementation, as it provides an interface between sensors, database, and image processing results, while also performing functions to manipulate peripheral units (usb dongle, keyboard etc.).

关键词： component Digital image processing Raspberry Pi Embedded System Road Sign Recognition

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Identifying and classifying cancerous cells based on the Ki67 detector 2

Identifying and classifying cancerous cells based on the Ki6...

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2nd International conference on image processing, Applications and systems (IPAS)

作者： Seddik, Hassen Saidani, Bechir Univ Tunis ENSIT Tunis Tunisia

ISBN: (纸本)9781509016457

The image processing arose from the idea of the necessity to replace the human observer by a machine. The interest of this paper is to replace the medical image by information interpretable. Usually, experts have manually performed to count the cell nuclei biopsy samples, one by one. This method ensures that accuracy is achieved in the final diagnosis delivered by pathologists, but the time until the patient is notified can vary from weeks to months depending on the laboratory resources. Cancer developing speed is also a limiting factor, so the sooner the disease is discovered the better and quicker the patient can start with the treatment or preparations for surgery can be arranged. Promptness in cancer recognition increases the chances to overcome this illness that affects every year more and more men as the world population's life expectancy increases. So, for this reason, it has proposed an automatic method. To return the more reliable and fast diagnosis, we applied a method based on tools and algorithms. The chain of this processing is begun with the segmentation to separate the various constituent zones the image. Secondly, we have the step of detecting the edges of the prostatic cells as well their center. Finally, we have the step of counting where we are going to find a score for the diagnosis.

关键词： image processing segmentation detection of cells cancer counting of cells

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