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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems VII"

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ProxImaL: Efficient image Optimization using Proximal algorithms

ProxImaL: Efficient Image Optimization using Proximal Algori...

引用

ACM SIGGRAPH conference

作者： Heide, Felix Diamond, Steven Niessner, Matthias Ragan-Kelley, Jonathan Heidrich, Wolfgang Wetzstein, Gordon Stanford Univ Stanford CA 94305 USA Univ British Columbia Vancouver BC V5Z 1M9 Canada KAUST Thuwal Saudi Arabia

ISBN: (纸本)9781450342797

Computational photography systems are becoming increasingly diverse, while computational resources-for example on mobile platforms-are rapidly increasing. As diverse as these camera systems may be, slightly different variants of the underlying image processing tasks, such as demosaicking, deconvolution, denoising, inpainting, image fusion, and alignment, are shared between all of these systems. Formal optimization methods have recently been demonstrated to achieve state-of-the-art quality for many of these applications. Unfortunately, different combinations of natural image priors and optimization algorithms may be optimal for different problems, and implementing and testing each combination is currently a time-consuming and error-prone process. ProxImaL is a domain-specific language and compiler for image optimization problems that makes it easy to experiment with different problem formulations and algorithm choices. The language uses proximal operators as the fundamental building blocks of a variety of linear and nonlinear image formation models and cost functions, advanced image priors, and noise models. The compiler intelligently chooses the best way to translate a problem formulation and choice of optimization algorithm into an efficient solver implementation. In applications to the image processing pipeline, deconvolution in the presence of Poisson-distributed shot noise, and burst denoising, we show that a few lines of ProxImaL code can generate highly efficient solvers that achieve state-of-the-art results. We also show applications to the nonlinear and nonconvex problem of phase retrieval.

关键词： computational photography digital image processing optimization

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Research of the Defects in PET Preform 21

Research of the Defects in PET Preform

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21st International conference on Methods and Models in Automation and Robotics (MMAR)

作者： Laucka, Andrius Andriukaitis, Darius Markevicius, Vytautas Zilys, Mindaugas Kaunas Univ Technol Dept Elect Engn LT-51368 Kaunas Lithuania

ISBN: (纸本)9781509018666

image technologies nowadays are used not only for keeping personal events safe, but also are widely applied in conjunction with automated electronic systems. Computer vision is widely used for inspection of the production quality in industries. Food industry is not an exception. Containers for food industry are made in very large quantities. This article contains of defect analysis of both external and side area of the bottleneck. Defects were divided into groups according to which the filters are created. For the control of PET preparation quality an automated computer vision algorithms were developed. The algorithms and methods were used for the detection of defective products mainly based on the image segmentation, digital production, erosion, smoothing. The most effective filters for the defect detection of the workpieces have been determined. It was carried out that efficiency of algorithms are close to 100 %.

关键词： PET digital image processing image segmentation computer vision smoothing methods

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A SYSTEM FOR HIGH PRECISION GLASS-TO-GLASS DELAY MEASUREMENTS IN VIDEO COMMUNICATION 23

A SYSTEM FOR HIGH PRECISION GLASS-TO-GLASS DELAY MEASUREMENT...

引用

23rd IEEE International conference on image processing (ICIP)

作者： Bachhuber, Christoph Steinbach, Eckehard Tech Univ Munich Chair Media Technol Munich Germany

ISBN: (纸本)9781467399616

Ultra low delay video transmission is becoming increasingly important. Video-based applications with ultra low delay requirements range from teleoperation scenarios such as controlling drones or telesurgery to autonomous control of dynamic processes using computer vision algorithms applied on real-time video. To evaluate the performance of the video transmission chain in such systems, it is important to be able to precisely measure the glass-to-glass (G2G) delay of the transmitted video. In this paper, we present a low-complexity system that takes a series of pairwise independent measurements of G2G delay and derives performance metrics such as mean delay or minimum delay etc. from the data. The precision is in the sub-millisecond range, mainly limited by the sampling rate of the measurement system. In our implementation, we achieve a G2G measurement precision of 0.5 milliseconds with a sampling rate of 2kHz.

关键词： Video signal processing Glass-to-glass delay measurement video delay distribution

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A nonconvex splitting method for symmetric nonnegative matrix factorization: Convergence analysis and optimality

A nonconvex splitting method for symmetric nonnegative matri...

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IEEE International conference on Acoustics, Speech and Signal processing

作者： Songtao Lu Mingyi Hong Zhengdao Wang Department of Electrical and Computer Engineering Iowa State University Ames 50011 USA Industrial and Manufacturing Systems Engineering Iowa State University Ames 50011 USA

ISBN: (纸本)9781509041183

Symmetric non-negative matrix factorization (SymNMF) has important applications in data analytics problems such as document clustering, community detection and image segmentation. In this paper, we propose a novel nonconvex variable splitting method for solving SymNMF. Different from the existing works, we prove that the algorithm converges to the set of Karush-Kuhn-Tucker (KKT) points of the nonconvex SymNMF problem with a global sublinear convergence rate. We also show that the algorithm can be efficiently implemented in a distributed manner. Further, we provide sufficient conditions that guarantee the global and local optimality of the obtained solutions. Extensive numerical results performed on both synthetic and real data sets suggest that the proposed algorithm yields high quality of the solutions and converges quickly to the set of local minimum solutions compared with other algorithms.

关键词： Symmetric Nonnegative Matrix Factorization Karush-Kuhn-Tucker points variable splitting global and local optimality clustering optimality matrix decomposition Cluster Analysis Nonnegative CENTROSYMMETRIC Solutions image segmentation Converge Dataset Sufficient conditions

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A novel artificial fish swarm algorithm for pattern recognition with convex optimization

A novel artificial fish swarm algorithm for pattern recognit...

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International conference on Communication and Electronics systems (ICCES)

作者： Shi, Lei Guo, Rui Ma, Yuchen Peking Univ Beijing Peoples R China Macquarie Univ N Ryde NSW Australia Hong Kong Baptist Univ Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781509010660

image pattern recognition is an important area in digital image processing. An efficient pattern recognition algorithm should be able to provide correct recognition at a reduced computational time. Off late amongst the machine learning pattern recognition algorithms, Artificial fish swarm algorithm is one of the swarm intelligence optimization algorithms that works based on population and stochastic search. In order to achieve acceptable result, there are many parameters needs to be adjusted in AFSA. Among these parameters, visual and step are very significant in view of the fact that artificial fish basically move based on these parameters. In standard AFSA, these two parameters remain constant until the algorithm termination. Large values of these parameters increase the capability of algorithm in global search, while small values improve the local search ability of the algorithm. In this paper, we empirically study the performance of the AFSA and different approaches to balance between local and global exploration have been tested based on the adaptive modification of visual and step during algorithm execution. The proposed approaches have been evaluated based on the four well-known benchmark functions. Experimental results show considerable positive impact on the performance of AFSA. A Convex optimization has been integrated into the proposed work to have an ideal segmentation of the input image which is a MR brain image.

关键词： image segmentation fish school algorithms convex optimization recognition rates

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Development of software prototypes through model game jam and basic vision artificial techniques

Development of software prototypes through model game jam an...

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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...

引用

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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