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

共 12675 条记录，以下是4721-4730 订阅

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Concatenated image completion via tensor augmentation and completion

Concatenated image completion via tensor augmentation and co...

引用

International conference on Signal processing and Communication systems, ICSPCS

作者： Johann A. Bengua Hoang D. Tuan Ho N. Phien Minh N. Do Faculty of Engineering and Information Technology University of Technology Sydney Ultimo Australia Department of Electrical and Computer Engineering and the Coordinated Science Laboratory University of Illinois at Urbana-Champaign Illinois USA

ISBN: (纸本)9781509009428

This paper proposes a novel framework called concatenated image completion via tensor augmentation and completion (ICTAC), which recovers missing entries of color images with high accuracy. Typical images are second-or third-order tensors (2D/3D) depending if they are grayscale or color, hence tensor completion algorithms are ideal for their recovery. The proposed framework performs image completion by concatenating copies of a single image that has missing entries into a third-order tensor, applying a dimensionality augmentation technique to the tensor, utilizing a tensor completion algorithm for recovering its missing entries, and finally extracting the recovered image from the tensor. The solution relies on two key components that have been recently proposed to take advantage of the tensor train (TT) rank: A tensor augmentation tool called ket augmentation (KA) that represents a low-order tensor by a higher-order tensor, and the algorithm tensor completion by parallel matrix factorization via tensor train (TMac-TT), which has been demonstrated to outperform state-of-the-art tensor completion algorithms. Simulation results for color image recovery show the clear advantage of our framework against current state-of-the-art tensor completion algorithms.

关键词： Tensile stress Color image color analysis Indexes Arrays Correlation Magnetic resonance imaging

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Parallel image dehazing algorithm based on GPU using fuzzy system and hybird evolution algorithm

Parallel image dehazing algorithm based on GPU using fuzzy s...

引用

ACIS International conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD)

作者： Che-Lun Hung Ren-You Yan Hsiao-Hsi Wang Department of Computer Science and Communication Engineering Providence University Taichung Taiwan Department of Computer Science and Information Management Providence University Taichung Taiwan

Haze is an atmospheric phenomenon that fogs the visibility of the scenes. Removing the haze has been an important issue in image processing technologies. Many image dehazing technologies with evolution algorithms have been proposed to remove the fog in the image. However, these algorithms usually are compute-intensive. In this paper, we propose a parallel hybrid evolution algorithm based on GPU to enhance the computational performance. In traditional evolution algorithms, the calculation of fitness function occupies the most of the computation time. In the proposed method, we implement this part on GPU by using CUDA framework to reduce the computational load. The experiment results show that the proposed method can remove the haze efficiently and successfully.

关键词： Graphics processing units Fuzzy systems Evolutionary computation Signal processing algorithms Algorithm design and analysis Genetic algorithms Entropy

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Adaptive multispectral GPU accelerated architecture for Earth Observation satellites

Adaptive multispectral GPU accelerated architecture for Eart...

引用

IEEE International Workshop on Imaging systems and Techniques (IST)

作者： R.L. Davidson C.P. Bridges Surrey Space Centre University of Surrey Guildford UK

ISBN: (纸本)9781509018185

In recent years the growth in quantity, diversity and capability of Earth Observation (EO) satellites, has enabled increase's in the achievable payload data dimensionality and volume. However, the lack of equivalent advancement in downlink technology has resulted in the development of an onboard data bottleneck. This bottleneck must be alleviated in order for EO satellites to continue to efficiently provide high quality and increasing quantities of payload data. This research explores the selection and implementation of state-of-the-art multidimensional image compression algorithms and proposes a new onboard data processing architecture, to help alleviate the bottleneck and increase the data throughput of the platform. The proposed new system is based upon a backplane architecture to provide scalability with different satellite platform sizes and varying mission's objectives. The heterogeneous nature of the architecture allows benefits of both Field Programmable Gate Array (FPGA) and Graphical processing Unit (GPU) hardware to be leveraged for maximised data processing throughput.

关键词： image coding Prediction algorithms Algorithm design and analysis Data processing Hardware Field programmable gate arrays Approximation algorithms

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Embedded Vision : Enhancing Embedded Platform For Face Detection System

Embedded Vision : Enhancing Embedded Platform For Face Detec...

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IEEE International Instrumentation and Measurement Technology conference (I2MTC)

作者： Kushsairy, A. K. Kamaruddin, Mohd Khairi Nasir, Haidawati Safie, Sairul I. Bakti, Zulkifli Abdul Kadir Isa, Mohd Ridzuan Khan, Sheroz Univ Kuala Lumpur British Malaysian Inst Kuala Lumpur Selangor Malaysia Univ Kuala Lumpur Malaysian Inst Informat Technol Kuala Lumpur Selangor Malaysia Univ Kuala Lumpur Malaysian Inst Ind Technol Johor Baharu Malaysia Int Islamic Univ Malaysia Kuala Lumpur Selangor Malaysia

ISBN: (纸本)9781467392204

Face detection is an important step in any face recognition systems, for the purpose of localizing and extracting face region from the rest of the images. The algorithms were built in C/C++ code and collaborated with OpenCV library. However, face detection system require high performance resources due to heavy real time measurement, in additional, it needs to be run on embedded platform. Therefore, platform system that host the face detection need to be tuned and enhanced to gain better performance from the standard settings and if possible, as good as desktop or laptop performance. In this paper, we propose two methods for enhancing the performance of the embedded platform. The two methods are OpenCV libraries multiprocessing and RAM tuning. The results shows that from one of the boards, Board 1 with quad core ARM Cortex-A7 processor capable to achieve almost as fast as laptop with Intel i3 processor. It can be concluded that embedded platform is capable to be a replacement for conventional computer system.

关键词： embedded vision image processing computer vision face detection

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Toolbox for 3D acoustic imaging of manufactured electronic circuits

Toolbox for 3D acoustic imaging of manufactured electronic c...

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Electronics System-Integration Technology conference, ESTC

作者： K. Baishya G.M Zhang D.M. Harvey D.R. Braden General Engineering Research Institute Liverpool John Moores University Liverpool United Kingdom Delphi Electronics & Safety Kirkby Liverpool United Kingdom

ISBN: (纸本)9781509014033

A signal processing toolbox has been realized to enhance the acoustic signal processing of manufactured electronic systems. The toolbox contains a range of signal processing algorithms to help better differentiate the 3D scanned acoustic signals acquired from manufactured parts. The processing has been used to assess the through-life reliability of systems by non-destructively sampling systems during extended reliability tests. The algorithms are based on a variety of novel signal processing methods such as wavelet, time frequency domain imaging, dictionaries and Fast Fourier Transform (FFT) for comparison. The paper will explore how the various algorithms can be tuned to test samples using the designed toolbox. The toolbox has a graphical user interface (GUI) designed in MATLAB. It can control the processing and display of 3D image data “cubes” acquired from an array of A-Scans of a sample obtained by an acoustic microscope. In this case a Sonoscan Gen6 C-SAM acoustic microscope has been used, but if the data format is known the toolbox can be applied to any 3D cube of data. The data sizes can be large, so processing times can be of the order of minutes for 1k × 1k × 1k array. Recently the execution times have been speeded up considerably by employing parallel algorithms and multicore processing. Some routines now only take seconds which is a very significant speed-up.

关键词： Acoustics Three-dimensional displays Matching pursuit algorithms Two dimensional displays MATLAB Flip-chip devices image processing

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High speed vedic multiplier for image processing using FPGA

High speed vedic multiplier for image processing using FPGA

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International conference on (ISCO) Intelligent systems and Control

作者： S. Jayakumar S. Sumathi Department of EIE Adhiyamaan College of Engineering Hosur

ISBN: (纸本)9781467378086

Vedic multiplier is based on the ancient algorithms (sutras) followed in INDIA for multiplication. This work is based on one of the sutras called “Nikhilam Sutra”. This sutra is meant for faster mental calculation. Though faster when implemented in hardware, it consumes more power than the conventional ones. This paper presents a technique to modify the architecture of the Vedic multiplier by using some existing methods in order to reduce power and improve image processing applicatio. The 32 × 32 Vedic multiplier is coded in Verilog HDL and Synthesized using Synopsys Design Compiler. The performance is compared in terms of area, data arrival time and power with earlier existing architecture of Vedic multiplier. Filtering involves lots of multiplications which consumes time. Time required increases with the increase in the number of pixels. This paper proposes an approach for image filtering using Vedic Mathematic which performs faster multiplication compared to the conventional algorithms namely Booth and Array Multiplication Algorithm thus reducing the time required for filtering of images. Time required by the algorithms for filtering are then compared using the experimental results.

关键词： DH-HEMTs

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Acceleration of image reconstruction in 3D Electrical Capacitance Tomography in heterogeneous, multi-GPU system using sparse matrix computations and Finite Element Method

Acceleration of image reconstruction in 3D Electrical Capaci...

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Federated conference on Computer Science and Information systems (FedCSIS)

作者： Paweł Kapusta Michał Majchrowicz Dominik Sankowski Lidia Jackowska-Strumiłło Lodz University of Technology Institute of Applied Computer Science Poland

3D Electrical Capacitance Tomography provides a lot of challenging computational issues that have been reported in the past by many researchers. image reconstruction using deterministic methods requires execution of many basic operations of linear algebra. Due to significant sizes of matrices used in ECT for image reconstruction and the fact that best image quality is achieved by using algorithms of which significant part is FEM and which are hard to parallelize or distribute. In order to solve these issues a new set of algorithms had to be developed.

关键词： image reconstruction Sparse matrices Finite element analysis Three-dimensional displays Algorithm design and analysis Graphics processing units Electrodes

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

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

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International conference on Power Electronics, Intelligent Control and Energy systems

作者： Santosh Kumar Henge B. Rama Department of Computer Science Kakatiya University Warangal Telangana State India

ISBN: (纸本)9781467385886

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 (FfNN) Feedback-neural Network (FbNN) Top-down-hierarchical-histogram (THH) Mirror image Learning (MIL)

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MeMoS - a software tool for extraction of anatomical structures data from 3D medical images

MeMoS - a software tool for extraction of anatomical structu...

引用

IEEE Signal processing algorithms, Architectures, Arrangements, and Applications conference

作者： Zbigniew Tyfa Michal Strzelecki Lodz University of Technology Institute of Electronics Lodz 90-924 Poland

ISBN: (纸本)9781509026616

MeMoS (Medical Model Sketcher), a software package that provides data required to reconstruct 3D medical models, basing on DICOM and RAW image sets, is presented. The uttermost objective of the software creation was to reduce a time needed to perform laborious data extraction process from medical images (necessary for the model reconstruction), without the need of purchasing expensive licenses for already existing programs. Obtained data can be used in any CAD software to recreate the spatial object. Generated 3D models of vascular systems can be used in numerical simulations so as to investigate the physical phenomena occurring in the circulatory system. Additionally, MeMoS is capable of creating datasets for texture analysis - that can be directly fed to the input of texture analysis software. Several results of the possible program output along with preliminary validation of implemented algorithms are outlined as well.

关键词： Biomedical image analysis software 3D model reconstruction image segmentation

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Single-image Depth Perception in the Wild 16

Single-Image Depth Perception in the Wild

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Annual conference on Neural Information processing systems

作者： Weifeng Chen Zhao Fu Dawei Yang Jia Deng University of Michigan Ann Arbor

ISBN: (纸本)9781510838819

This paper studies single-image depth perception in the wild, i.e., recovering depth from a single image taken in unconstrained settings. We introduce a new dataset "Depth in the Wild" consisting of images in the wild annotated with relative depth between pairs of random points. We also propose a new algorithm that learns to estimate metric depth using annotations of relative depth. Compared to the state of the art, our algorithm is simpler and performs better. Experiments show that our algorithm, combined with existing RGB-D data and our new relative depth annotations, significantly improves single-image depth perception in the wild.

关键词： Depth Perception ANNOTATIONS state of the art algorithms images Learning

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