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1st IEEE International conference on Power Electronics, Intelligent Control, and Energy systems (ICPEICES)

作者： Henge, Santosh Kumar Rama, B. Kakatiya Univ Dept Comp Sci Warangal Telangana State India

ISBN: (纸本)9781467385879

OCR is the most active, interesting evaluation invention of text cum character processing recognition and pattern based image recognition. In present life OCR has been successfully using in finance, legal, banking, health care and home need appliances. The OCR consists the different levels of processing methods like as image Pre Acquisition, Classification, Post-Acquisition, Pre-Level processing, Segmented processing, Post-Level processing, Feature Extraction. The many researchers are proposed various levels of different methodologies and approaches in different versions of languages with help of modern and traditional technologies. This paper expressed the detail study and analysis of various character recognition methods and approaches: in details like as flow and type of approached methodology was used, type of algorithm has built with support of technology has implemented background of the proposed methodology and invention best outcomes flow for the each methodology. This paper and also expressed the main objectives and ideology of various OCR algorithms, like as neural networks algorithm, structural algorithm, support vector algorithm, statistical algorithm, template matching algorithm along with how they classified, identified, rule formed, inferred for recognition of characters and symbols.

关键词： Support Vector Machine (SVM) Optical Character Recognition (OCR) Artificial Neural Network (ANN) Pattern Matching algorithms (PMA) Stastical Algorithm (SstA) Strctural Algorithm (SA) Freeman Chain Code (FCC) Digitized-Retrievable Rorm (DRF) Feedforwardneural Network (FINN) Feedback-neural Network (FbNN) Top-down-hierarchical-histogram (THH) Mirror image Learning (MIL)

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The PUT Surveillance Database

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8th International conference on image processing and Communications (IP and C)

作者： Fularz, Michal Kraft, Marek Schmidt, Adam Niechcial, Jakub Univ Technol Inst Control & Informat Engn Piotrowo 3A PL-60965 Poznan Poland

In this paper we present a new, publicly available database of color, high resolution images useful in evaluation of various algorithms in the field of video surveillance. The additional data provided with the images ... 详细信息

ISBN: (纸本)9783319238142;9783319238135

关键词： Video surveillance image dataset Object recognition Object tracking Reidentification

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Towards printing as an electronics manufacturing method: micro-scale chiplet position control

Towards printing as an electronics manufacturing method: mic...

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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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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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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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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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Large Scale Retrieval and Generation of image Descriptions

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INTERNATIONAL JOURNAL OF COMPUTER VISION 2016年第1期119卷 46-59页

作者： Ordonez, Vicente Han, Xufeng Kuznetsova, Polina Kulkarni, Girish Mitchell, Margaret Yamaguchi, Kota Stratos, Karl Goyal, Amit Dodge, Jesse Mensch, Alyssa Daume, Hal, iii Berg, Alexander C. Choi, Yejin Berg, Tamara L. Univ N Carolina Chapel Hill NC 27599 USA SUNY Stony Brook Stony Brook NY 11794 USA Microsoft Res Redmond WA USA Tohoku Univ Sendai Miyagi Japan Columbia Univ New York NY USA Yahoo Labs Sunnyvale CA USA Carnegie Mellon Univ Pittsburgh PA 15213 USA Univ Penn Philadelphia PA 19104 USA Univ Maryland College Pk MD 20742 USA Univ Washington Seattle WA 98195 USA

What is the story of an image? What is the relationship between pictures, language, and information we can extract using state of the art computational recognition systems? In an attempt to address both of these questions, we explore methods for retrieving and generating natural language descriptions for images. Ideally, we would like our generated textual descriptions (captions) to both sound like a person wrote them, and also remain true to the image content. To do this we develop data-driven approaches for image description generation, using retrieval-based techniques to gather either: (a) whole captions associated with a visually similar image, or (b) relevant bits of text (phrases) from a large collection of image + description pairs. In the case of (b), we develop optimization algorithms to merge the retrieved phrases into valid natural language sentences. The end result is two simple, but effective, methods for harnessing the power of big data to produce image captions that are altogether more general, relevant, and human-like than previous attempts.

关键词： Retrieval image description Data driven Big data Natural language processing

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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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