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Iberian conference on Information systems and Technologies (CISTI)

作者： Luis Barba-Guamán Pablo Alejandro Quezada-Sarmiento Carlos Calderon-Cordova Liliana Enciso Daniel Guamán Departament of Electronics and Computer Science Universidad Técnica Particular de Loja Loja Ecuador

ISBN: (纸本)9781509050475

The artificial vision is a part of the artificial intelligence that pretends to simulate the human vision, is to say, from the acquisition, processing, analysis and interpretation of images through an intelligent system. This work presents the creation of prototypes under the game jam model as a software product. In this context, the objective of the present work was to apply basic artificial vision algorithms such as linear discriminant analysis (LDA), principal component analysis (PCA), Fisherface, Otsu, CamShift and color spaces such as RGB and HSV in order to be able to motion detection of objects, face recognition and pedestrian detection. As a result of applying this model in rapid prototyping, we found significant factors (such as: participatory design, light construction, product value approach, aesthetics and technology) in the implementation of innovative strategies in creating of prototypes focused on Software development.

关键词： Games Software Principal component analysis Prototypes Computational modeling image color analysis Color

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CAS-CNN: A Deep Convolutional Neural Network for image Compression Artifact Suppression

CAS-CNN: A Deep Convolutional Neural Network for Image Compr...

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International Joint conference on Neural Networks

作者： Lukas Cavigelli Pascal Hager Luca Benini Integrated Systems Laboratory ETH Zurich Zurich Switzerland

ISBN: (纸本)9781509061839

Lossy image compression algorithms are pervasively used to reduce the size of images transmitted over the web and recorded on data storage media. However, we pay for their high compression rate with visual artifacts degrading the user experience. Deep convolutional neural networks have become a widespread tool to address high-level computer vision tasks very successfully. Recently, they have found their way into the areas of low-level computer vision and image processing to solve regression problems mostly with relatively shallow networks. We present a novel 12-layer deep convolutional network for image compression artifact suppression with hierarchical skip connections and a multi-scale loss function. We achieve a boost of up to 1.79 dB in PSNR over ordinary JPEG and an improvement of up to 0.36 dB over the best previous ConvNet result. We show that a network trained for a specific quality factor (QF) is resilient to the QF used to compress the input image - a single network trained for QF 60 provides a PSNR gain of more than 1.5 dB over the wide QF range from 40 to 76.

关键词： image coding Training Neural networks Transform coding image resolution Convolution Visualization

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MULTI-image SUPER-RESOLUTION USING A DUAL WEIGHTING SCHEME BASED ON VORONOI TESSELLATION 23

MULTI-IMAGE SUPER-RESOLUTION USING A DUAL WEIGHTING SCHEME B...

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23rd IEEE International conference on image processing (ICIP)

作者： Baetz, Michel Eichenseer, Andrea Kaup, Andre Friedrich Alexander Univ Erlangen Nurnberg Multimedia Commun & Signal Proc Cauerstr 7 D-91058 Erlangen Germany

ISBN: (纸本)9781467399616

Increasing spatial resolution is often required in many applications such as entertainment systems or video surveillance. Apart from using higher resolution sensors, it is also possible to apply super resolution algorithms to realize an increased resolution. Those methods can be divided into approaches that rely on only a single low resolution image or on multiple low resolution video frames. While incorporating more frames into the super-resolution is beneficial for the resolution enhancement in principle, it is also likely to introduce more artifacts from inaccurate motion estimation. To alleviate this problem, various weightings have been proposed in the literature. In this paper, we propose an extended dual weighting scheme for an interpolation-based super-resolution method based on Voronoi tessellation that relies on both a motion confidence weight and a distance weight. Compared to non-weighted super-resolution, the proposed method yields an average gain in luminance PSNR of up to 1.29 dB and 0.61 dB for upscaling factors of 2 and 4, respectively. Visual comparisons substantiate the objective results.

关键词： Resolution Enhancement image processing Multi-image Super-Resolution Voronoi Tessellation

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Comprative Study with Analysis of OCR algorithms and Invention Analysis of Character Recognition Approched Methodologies 1

Comprative Study with Analysis of OCR Algorithms and Inventi...

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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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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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