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

共 12980 条记录，以下是4801-4810 订阅

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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...

引用

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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A Survey of Blob Detection algorithms for Biomedical images

A Survey of Blob Detection Algorithms for Biomedical Images

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International conference of Information and Communication Technology for Embedded systems

作者： Kay Thwe Min Han Bunyarit Uyyanonvara School of Information Computer and Communication TechnologySirindhorn International Institute of Technology Thammasat University 131 Moo 5 Tiwanont Road Bangkadi Muang Pathumthani 12000 Thailand School of Information Computer and Communication Technology Sirindhorn International Institute of Technology Thammasat University 131 Moo 5 Tiwanont Road Bangkadi Muang Pathumthani 12000 Thailand

ISBN: (纸本)9781509022502

This paper presents a survey of blob detection methods which has been applied on image processing with relation of medical images proposed by literature. "The blob detection is a mathematical method which detects regions or points in digital images". [1] The regions or points which have noticeable difference with their surroundings is called blob. Given the increased interest in biomedical image processing system, many algorithms and methods have been reported to apply but there is no systematic survey and classification of the blob detection for medical images and how they have been assessed and applied. The findings, which is the most usable methods of blob detectors in biomedical image processing has been presented. It was also investigated how these studies have been surveyed, how they evolved in the main digital libraries over the last decade, and what points deserves further attention, through new research. From this survey, practitioners and researchers can adopt the blob detection methods and analyze to use these methods in their research for further development.

关键词： Blob Detection Survey Medical image processing Blob Detection Methods

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Euclidean Proximity Function in image processing

Euclidean Proximity Function in Image Processing

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

作者： Pawel M. Stasik Poznan University of Technology Faculty of Computing Science Chair of Control and Systems Engineering

ISBN: (纸本)9781509026616

In image processing measuring and valuing a distance between two points is important. The obtained values can be used for determining whether two points are close to each other or to define weights for a filter concentrated around a central element. While there are measures of proximity, neither of them was defined with a such use in mind, mostly concentrating on problem of an optimization. The idea is to turn the Euclidean distance between two points into a measure of how close (or far) two points are from each other, basing on two given ranges. The function was mostly obtained by a theoretical analysis supported with a mathematical calculation and examples of use. As it was proven in the work, the obtained function can be implemented not only to measure proximity, but also as a flexible kernel for image filters, allowing for blurring or edge-detection.

关键词： image edge detection Euclidean distance Fuzzy logic Limiting Hypercubes Optimization Edge detection Euclidean distance Hypercube Limiting Fuzzy logic image processing image filtering Proximity central element Function BLURRING

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Pulse rate variability and blood oxidation content identification using miniature wearable wrist device

Pulse rate variability and blood oxidation content identific...

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International conference on systems, Signals and image processing, IWSSIP

作者： Jernej Ženko Marko Kos Iztok Kramberger Faculty of Electrical Engineering and Computer Science University of Maribor Maribor Slovenia

This paper presents the work related to the identification of PRV (pulse rate variability) and SpO2 (blood oxidation content) using miniature wearable wrist device. The extension of currently widely used PPT (photo plethysmography) measuring technique is proposed. Most PPT devices only measure PR (pulse rate), but with minimum adaptations to the sensor, a wider range of parameters can be measured. Two of such parameters are PRV and SpO2. This set of parameters gives a better insight into ones physical and mental state than only PR parameter. In order to develop a device that does not obstruct the user in any way, we propose a miniature non-invasive wearable device, and algorithms that do not need any significant processing power in order to identify the biometric parameters. The device is a lightweight battery powered embedded system, that measures and analyses biometric data for later analysis in correlation with one's activity.

关键词： Decision support systems Data processing

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Novel approach to enhance face recognition using depth maps

Novel approach to enhance face recognition using depth maps

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International conference on systems, Signals and image processing, IWSSIP

作者： Yaser Saleh Eran Edirisinghe Department Computer Science Loughborough University Loughborough UK

ISBN: (纸本)9781467395564

Face recognition, although being a popular area of research and study, still has many challenges, and with the appearance of the Microsoft Kinect device, new possibilities of research were uncovered, one of which is face recognition using the Kinect. With the goal of enhancing face recognition, this paper is aiming to prove how depth maps, since not effected by illumination, can improve face recognition with a benchmark algorithm based on the Eigenface. This required some experiments to be carried out, mainly in order to check if algorithms created to recognize faces using normal images can be as effective if not more effective with depth map images. The OpenCV Eigenface algorithm implementation was used for the purpose of training and testing both normal and depth-map images. Finally, results of the experiments are presented to prove the ability of the tested algorithm to function with depth maps, also, proving the capability of depth maps face recognition's task in poor illumination.

关键词： Face recognition Lighting Face Training image recognition Benchmark testing

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International conference on Modern Engineering: Science and Education, MESE 2011

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International conference on Modern Engineering: Science and Education, MESE 2011

ISBN: (纸本)9783319295787

The proceedings contain 19 papers. The special focus in this conference is on Advances in Mechanical Engineering. The topics include: Frameworks not restorable from self stresses;structural modifications synthesis of bennett mechanism;kinematic research of bricard linkage modifications;drive selection of multidirectional mechanism with excess inputs;engineering calculations of bolt connections;modern methods of contact forces between wheelset and rails determining;a novel design of an electrical transmission line inspection machine;one stable scheme of centrifugal forces dynamic balance;new effective data structure for multidimensional optimization orthogonal packing problems;one-dimensional models in turbine blades dynamics;stationary oscillation in two-mass machine aggregate with universal-joint drive;the vibrations of reservoirs and cylindrical supports of hydro technical constructions partially submerged into the liquid;mathematical modelling of interaction of the biped dinamic walking robot with the ground;programmable movement synthesis for the mobile robot with the orthogonal walking drivers;processing of data from the camera of structured light for algorithms of image analysis in control systems of mobile robots;structural and phase transformation in material of steam turbines blades after high-speed mechanical effect;stress corrosion cracking and electrochemical potential of titanium alloys;metal flow control at processes of cold axial rotary forging and use of the capabilities of acoustic-emission technique for diagnostics of separate heat exchanger elements.

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algorithms for image processing in graph-based volumetric segmentation

Algorithms for image processing in graph-based volumetric se...

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International conference on Information, Intelligence, systems and Applications (IISA)

作者： Dumitru Dan Burdescu Liana Stanescu Marius Brezovan Cosmin Stoica Spahiu Florin Slabu Computers and information Technology Department University of Craiova Universitatea din Craiova Craiova RO Departament of Computer Science University of Craiova Craiova Dolj Romania

ISBN: (纸本)9781509034307

The aim of this article is to present a method to detect visual objects from color digital images by volumetric segmentation. We will discuss algorithms for visual and multimedia computing. The problem of partitioning images into homogenous regions or semantic entities is a basic problem for identifying relevant objects. The presented method is a general-purpose volumetric segmentation method and it produces results from two different perspectives: (a) from the perspective of perceptual grouping of regions from the images, and also (b) from the perspective of determining regions if the input spatial images contain visual objects. We present a unified framework for volumetric image segmentation and prism cells used is the first run into volumetric segmentation algorithms. The major concept used in graph-based volumetric segmentation method is the concept of homogeneity of volumes and thus the edge weights are based on color distance. The complexity of our original algorithm for volumetric segmentation is linear.

关键词： image segmentation image color analysis Visualization Partitioning algorithms Syntactics Vegetation Joining processes

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Efficient GPU Computing Framework of Cloud Filtering in Remotely Sensed image processing

Efficient GPU Computing Framework of Cloud Filtering in Remo...

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Proceedings of the Digital image Computing: Technqiues and Applications (DICTA)

作者： Jing Ke Arcot Sowmya Yi Guo Tomasz Bednarz Michael Buckley School of Computer Science and Engineering UNSW / DATA61 CSIRO Sydney Australia School of Computer Science and Engineering UNSW Sydney Australia Mathematics Western Sydney University Sydney Australia DATA61 CSIRO Brisbane Australia DATA61 CSIRO Sydney Australia

For optical remote sensing images, an effective method to reduce or eliminate the impact of clouds is important. With big data input and real-time processing demands, efficient parallelization strategies are essential for high performance computing on multi-core systems. This paper proposes an efficient high performance parallel computing framework for cloud filtering and smoothing. A comparison and benchmarking of two parallel algorithms for cloud filtering that incorporates spatial smoothing solved by two-dimensional dynamic programming is implemented. The experiments were carried out on an NVIDIA GPU accelerator with evaluations of approximation, parallelism and performance. The test results show significant performance improvements with high accuracy compared with sequential CPU implementation, and can be applied to other multi-core systems.

关键词： Graphics processing units Smoothing methods Dynamic programming Indexes Instruction sets Heuristic algorithms Parallel processing

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