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

共 14690 条记录，以下是4621-4630 订阅

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An efficient image watermarking scheme using the Laplacian Pyramid based on projection

An efficient image watermarking scheme using the Laplacian P...

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2017 International conference on Recent Advances in Signal processing, Telecommunications and Computing, SigTelCom 2016

作者： Nguyen, Sy C. Kha, Ha Hoang Nguyen, Hoang M. Faculty of Electrical and Electronics Engineering Ho Chi Minh City University of Technology VNU-HCM Viet Nam Faculty of Management Information Systems Banking University of HCM City Viet Nam

ISBN: (纸本)9781509022915

The digital image watermarking technology is widely used to protect intellectual property and to authenticate digital contents in the network environment. The aim of the paper is to invoke the improved Laplacian Pyramid transform to develop a new image watermarking scheme. Specifically, the host image is decomposed and reconstructed by using the improved Laplacian Pyramid transform. Then, the mid frequency subband data with the appropriate level and strength factor are chosen to embed the watermark. Finally, we conduct experiments to investigate the invisibility and robustness of the proposed algorithm. To measure the invisibility and the robustness of the algorithms, we use the peak signal-to-noise ratio (PSNR) and normalized correlation (NC) as performance metrics. Experimental results demonstrate that invisibility and robustness are guaranteed. The proposed algorithm outperforms one based on curvelets for the lossy JPEG compression attack in terms of invisibility and robustness. © 2017 IEEE.

关键词： image watermarking

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Cyber-physical magnetic field sensors 11

Cyber-physical magnetic field sensors

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11th Annual TechConnect World Innovation conference and Expo, Held Jointly with the 20th Annual Nanotech conference and Expo, and the 2017 National SBIR/STTR conference

作者： Kravljaca, Vladimir Lyshevski, Sergey Edward Department of Electrical and Microelectronic Engineering Rochester Institute of Technology RochesterNY14623 United States

ISBN: (纸本)9780998878201

This paper studies integrated solid-state Hall effect sensors with processing microelectronics. Many commercialized triaxial magnetometers have iii-V semiconductor sensing elements, application-specific integrated circuits (ASICs) and microcontrollers. processing algorithms are supported by device- and hardware specific architectures, middleware and software. Integrated Hall effect sensors with InSb sensing elements may ensure sufficient accuracy, measurement range, adequate spatiotemporal resolution, linearity, high bandwidth, and fast response time. Nonlinearities, cross-axis coupling, temperature sensitivity and other performance-degrading phenomena are minimized using ASICs which implement filters, compensators, etc. We examine and solve noise attenuation and error reduction problems by processing the ASICs outputs of integrated Hall effect sensors. Noise and error are minimized by using adaptive filters and information analysis. A dynamic mode estimator supports system reconfiguration. The experimentally substantiated laboratory-proven schemes enhance the existing solutions toward CPS-compliant sensing solutions for complex systems.

关键词： iii-V semiconductors

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NASA Technical Reports Server (Ntrs) 19880014804: Third conference on Artificial Intelligence for Space Applications, Part 2

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2017年

NASA Technical Reports Server (Ntrs) 19880014804: Third conference on Artificial Intelligence for Space Applications, Part 2 by NASA Technical Reports Server (Ntrs); published by

关键词： (ntrs) 19880014804: adaptive control algorithms applications, architecture (computers) artificial computer programs conference conferences denton, judith s. [compiler] distributed processing expert systems freeman, michael s. [compiler] hubble space telescope image processing monitors nasa technical reports server (ntrs) neural nets real time operation space stations vereen, mary [compiler]

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Blind image Quality Assessment designed by learning-based attributes selection 25

Blind Image Quality Assessment designed by learning-based at...

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25th Color and Imaging conference: Color Science and Engineering systems, Technologies, and Applications, CIC 2017

作者： Charrier, Christophe Saadane, Abdelhakim Fernandez-Maloigne, Christine Normandie Univ. UNICAEN ENSICAEN CNRS GREYC Caen14000 France Université de Nantes XLIM UMR CNRS 7252 France Université de Poitiers XLIM UMR CNRS 7252 France

ISBN: (纸本)9780892083282

With the rapid growth of image processing technologies, objective image Quality Assessment (IQA) is a topic where considerable research effort has been made over the last two decades. IQA algorithms based on image structure have been shown to correlate well with Mean Opinion Scores (MOS). No-Reference (NR) image quality metrics are of fundamental interest as they can be embedded in practical applications This paper deals with a new NR-IQA metric based on natural scenes statistics. It proposes to model the best correlated statistics of seven well known no-reference image quality algorithms by a MultiVariate Gaussian Distribution (MVGD). A part of LIVE database is used with the associated DMOS to fit the MVGD model, namely Model image Quality Index (MIQI). Hence, the quality of a distorted image is given by the DMOS that maximizes the multivariate Gaussian probability density function. Experimental results demonstrate the method effectiveness for a wide variety of distortions. © 2017 Society for Imaging Science and Technology.

关键词： image quality

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BEST: Benchmark and Evaluation of Surveillance Task 13th

BEST: Benchmark and Evaluation of Surveillance Task

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13th Asian conference on Computer Vision (ACCV)

作者： Zhang, Chongyang Ni, Bingbing Song, Li Zhai, Guangtao Yang, Xiaokang Zhang, Wenjun Shanghai Jiao Tong Univ Inst Image Commun & Network Engn Shanghai 200240 Peoples R China

ISBN: (纸本)9783319545264;9783319545257

Smart/Intelligent video surveillance technology plays the central role in the emerging smart city systems. Most intelligent visual algorithms require large-scale image/video datasets to train classifiers or acquire discriminative features using machine learning. However, most existing datasets are collected from non-surveillance conditions, which have significant differences as compared to the practical surveillance data. As a consequence, many existing intelligent visual algorithms trained on traditional datasets perform not so well in the real world surveillance applications. We believe the lack of high quality surveillance datasets has greatly limited the application of the computer vision algorithms in practical surveillance scenarios. To solve this problem, one large-scale and comprehensive surveillance image and video database and test platform, called Benchmark and Evaluation of Surveillance Task (abbreviated as BEST), is developed in this work. The original images and videos in BEST were all collected from on-using surveillance cameras, and have been carefully selected to cover a wide and balanced range of outdoor surveillance scenarios. Compared with the existing surveillance/non-surveillance datasets, the proposed BEST dataset provides a realistic, extensive and diversified testbed for a more comprehensive performance evaluation. Our experimental results show that, performance of seven pedestrian detection algorithms on BEST is worse than that on the existing datasets. This highlights the difference between non-surveillance data and real surveillance data, which is the major cause of the performance decreases. The dataset is open to the public and can be downloaded at: http://***/best/Data/List/Datasets.

关键词： Security systems

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SPID: Surveillance Pedestrian image Dataset and Performance Evaluation for Pedestrian Detection 13th

SPID: Surveillance Pedestrian Image Dataset and Performance ...

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13th Asian conference on Computer Vision (ACCV)

作者： Wang, Dan Zhang, Chongyang Cheng, Hao Shang, Yanfeng Mei, Lin Shanghai Jiao Tong Univ Inst Image Commun & Network Engn Shanghai Peoples R China Minist Publ Secur Res Inst 3 Shanghai Peoples R China

ISBN: (纸本)9783319545264;9783319545257

nedestrian detection is highly valued in intelligent surveillance systems. Most existing pedestrian datasets are autonomously collected from non-surveillance videos, which result in significant data differences between the self-collected data and practical surveillance data. The data differences include: resolution, illumination, view point, and occlusion. Due to the data differences, most existing pedestrian detection algorithms based on traditional datasets can hardly be adopted to surveillance applications directly. To fill the gap, one surveillance pedestrian image dtaset (SPID), in which all the images were collected from the on-using surveillance systems, was constructed and used to evaluate the existing pedestrian detection (PD) methods. The dataset covers various surveillance scenes and pedestrian scales, view points, and illuminations. Four traditional PD algorithms using hand-crafted features and one deep-learning-model based deep PD methods are adopted to evaluate their performance on the SPID and some well-known existing pedestrian datasets, such as INRIA and Caltech. The experimental ROC curves show that: The performance of all these algorithms tested on SPID is worse than that on INRIA dataset and Caltech dataset, which also proves that the data differences between non-surveillance data and real surveillance data will induce the decreasing of PD performance. The main factors include scale, view point, illumination and occlusion. Thus the specific surveillance pedestrian dataset is very necessary. We believe that the release of SPID can stimulate innovative research on the challenging and important surveillance pedestrian detection problem. SPID is available online at: http://***/best/Data/List/Datasets.

关键词： Security systems

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An Effective Enhancement and Segmentation of Coronary Arteries in 2D Angiograms

An Effective Enhancement and Segmentation of Coronary Arteri...

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International conference on Smart Computing and Electronic Enterprise (ICSCEE)

作者： Sammer Zai Asad Abbas Mehran University of Engineering and Technology Dept. of Computer Systems Engineering Jamshoro Pakistan Dept. of Software Engineering Hanyang University Ansan South Korea

ISBN: (纸本)9781538648391

Vessel enhancement in two-dimensional angiogram images is an essential pre-requisite step towards the isolation of coronary arteries. Hessian-based filters are the most commonly used vessel enhancement filters; however, these filters are more sensitive to noise and suppress the bifurcation regions. Suppression of bifurcation regions results in disconnected vessels. In this study, we present a technique that enhances the arteries of the heart in 2D angiograms and also refines the noisy vesselness obtained through Frangi's method by using guided filter which produces more enhanced image that can be used as an effective pre-processing step for binarization of the Frangi vessel response having less discontinuities and joint suppression. The proposed approach makes use of the guided filter which smooths the edges, and at the same time preserves the edges as well for the enhancement of vessels. Following this filter, an Adaptive thresholding is applied to segment the coronary arteries from the angiogram. The proposed method has been tested on real angiography images and the efficiency of the method has been shown qualitatively as well as quantitatively.

关键词： Arteries image segmentation Maximum likelihood detection Nonlinear filters Two dimensional displays Filtering algorithms Bifurcation

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Sub-pixel X-marker detection by Hough transform

Sub-pixel X-marker detection by Hough transform

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Iranian conference of Biomedical Engineering (ICBME)

作者： Ali Yazdani Hojjat Aalizadeh Farshid Karimi Saeed Solouki Hamid Soltanian-Zadeh School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Control and Intelligent Processing Center of Excellence(CIPCE) School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781538679531;9781538679524

High precision center detection of X-markers is required in many applications such as navigation surgery systems and camera calibration. Hough transform is a preferable tool for extracting intersecting lines in an image, which leads to center detection. In this paper, we detect X-marker centers by the sub-pixel precision, using Hough transform. Switching to Hough space helps us to apply processes like thresholding, filtering and weighted averaging on coordinates. The algorithm involves two parameters `Hough Size' and `Filter Size' required to be adjusted for best performance of the algorithm. A dataset of 900 images is used and best performance is achieved by values of 180 and 23 for the above parameters, respectively. Using this setting, 90.8% of the centers are detected successfully by the sub-pixel precision. The average distance between detected centers and reference centers is 0.51 pixels. This suggests that the proposed algorithm has the potential to be utilized for sub-pixel marker detection.

关键词： image edge detection Transforms Feature extraction Cameras Biomedical engineering Calibration Filtering algorithms

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algorithms for People Recognition in Digital images: A Systematic Review and Testing 5th

Algorithms for People Recognition in Digital Images: A Syste...

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5th World conference on Information systems and Technologies (WorldCIST)

作者： Intriago-Pazmino, Monserrate Vargas-Sandoval, Vanessa Moreno-Diaz, Jorge Salazar-Jacome, Elizabeth Salazar-Grandes, Mayra Escuela Politec Nacl Dept Informat & Ciencias Comp Quito Ecuador Escuela Politec Nacl Fac Ingn Sistemas Quito Ecuador Univ Fuerzas Armadas ESPE Dept Ciencias Exactas Latacunga Ecuador Univ Fuerzas Armadas ESPE Dept Elect & Elect Latacunga Ecuador

ISBN: (纸本)9783319565385;9783319565378

People recognition in digital images has wide applications and challenges. In this article, we present a systematic review of works published in the last decade;based on which, we have identified, implemented and tested the frequently used and best-assessed algorithms. We have found Histograms of Oriented Gradients (HOG) like feature extraction algorithm;and two classification algorithms, AdaBoost and Support Vector Machine (SVM). The tests were performed on 50 images chosen randomly from Penn-Fudan public database. The accuracy in SVM-HOG combination was 0.96, it is a similar value to a related work;and the detection rate was 0.66 in SVM-HOG combination and 0.72 in Adaboost-HOG combination, they are inferior to related works. We shall discuss possible reasons.

关键词： People recognition Human recognition Pedestrian recognition Systematic review Computer vision Digital image processing

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20 Years of Progress in Video Compression - from MPEG-1 to MPEG-H HEVC. General View on the Path of Video Coding Development 8th

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

作者： Karwowski, Damian Grajek, Tomasz Klimaszewski, Krzysztof Stankiewicz, Olgierd Stankowski, Jakub Wegner, Krzysztof Poznan Univ Tech Chair Multimedia Telecommun & Microelect Polanka 3 St PL-60965 Poznan Poland

ISBN: (纸本)9783319472744;9783319472737

Compression of moving images has opened unprecedented opportunities of transmission and storage of digital video. Extraordinary performance of today's video codecs is a result of tens of years of work on the development of methods of data encoding. This paper is an attempt to show this history of development. It highlights the history of individual algorithms of data encoding as well as the evolution of video compression technologies as a whole. With the development of successive technologies also functionalities of codecs were evolving, which make also the topic of the paper. The paper ends the attempt of authors' forecasting about the future evolution of video compression technologies.

关键词： image compression

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