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

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Black-and-White Drawing support for Adobe Illustrator using Onomatopoeia

Black-and-White Drawing support for Adobe Illustrator using ...

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IEEE International conference on Fuzzy systems (FUZZ-IEEE)

作者： Yamada, Yuri Kayama, Gou Nakamura, Tsuyoshi Endo, Kazuya Kanoh, Masayoshi Yamada, Koji Nagoya Inst Technol Nagoya Aichi Japan Chukyo Univ Nagoya Aichi Japan Inst Adv Media Arts & Sci Ogaki Japan

ISBN: (纸本)9781509060344

Adobe Illustrator provides many tools for a user to create art works. The tools also provide many parameters or options that the user can tune up or select. This study focuses on black-and-white drawings ("Sumi-e" or "Suiboku-ga" in Japanese) on Adobe Illustrator. In order to create black-and-white drawings, the user usually has to select a proper brush from preset brushes Adobe Illustrator provides. But the selection is difficult for the user, especially beginners. This paper proposes a supporting plug-in tool for the user to decide and apply the proper brush. The plug-in can accept an onomatopoeic utterance input which expresses the user's own imagination or impression of the brush. Onomatopoeia is well known as a useful figurative expression for Japanese people to describe their own imagination or impression for something. This paper reports the configuration of the plug-in and illustrated some examples of black-and-white drawings created by using the plug-in. The architecture of the plug-in consists of CNN(convolution neural network), database of brush samples, brush image interpolation, fuzzy-based image expansion and contraction, and so on. CNN allows input of arbitrary onomatopoeias. The brush image interpolation generates a new brush from brush samples in the database. The fuzzy-based image expansion and contraction transforms the new brush into a natural-looked brush form with less jaggy.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Contemporary Stegnalysis Schemes for Reliable Detection of Steganography 2

Contemporary Stegnalysis Schemes for Reliable Detection of S...

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2nd IEEE International conference on Wireless Communications, Signal processing and Networking (WiSPNET)

作者： Babu, G. John Sridevi, R. Sreekavitha Engn Coll Khammam Telangana India JNTUH Coll Engn Hyderabad Telangana India

ISBN: (纸本)9781509044429

Steganalysis is the process of detecting the hidden information in the carrier. Most used carriers for steganography are images due to the redundant information present in the images and frequency of their use on the Internet. Steganalysis methods are classified into two categories, Targeted steganalysis and universal steganalysis. Targeted steganalysis is based on analysis of individual and known steganographic scheme. Blind steganalysis methods detect steganographic schemes created by unknown random stego-systems. The objective of steganalysis algorithms is to distinguish stego images from pure images. A classifier is built based on stego and pure images. When the knowledge of steganographic scheme is not available, a general steganalyzer is built, which is trained with a set of pure images and a set of stego images generated by various steganographic algorithms. The performance of steganalysis algorithm depends on three important aspects, preprocessing technique, feature selection & extraction and classification. This paper presents the contemporary steganalysis schemes discussing the details and comparing various aspects of these methods.

关键词： image steganalysis Feature Selection Feature Extraction Machine learning

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Transferring Microscopy image Modalities with Conditional Generative Adversarial Networks 30

Transferring Microscopy Image Modalities with Conditional Ge...

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30th IEEE/CVF conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Han, Liang Yin, Zhaozheng Missouri Univ Sci & Technol Dept Comp Sci Rolla MO 65409 USA

ISBN: (纸本)9781538607336

Phase Contrast (PC) and Differential Interference Contrast (DIC) microscopy are two popular non-invasive techniques for monitoring live cells. Each of these two image modalities has its own advantages and disadvantages to visualize specimens, so biologists need these two complementary modalities together to analyze specimens. In this paper, we investigate a conditional Generative Adversarial Network (conditional GAN), which contains one generator and two discriminators, to transfer microscopy image modalities. Given a training dataset consisting of pairs of images (source and destination) captured on the same set of specimens by DIC and Phase Contrast microscopes, we can train a conditional GAN, and with this well-trained GAN, we can generate the corresponding Phase Contrast image given a new DIC image, vice versa. The preliminary experiments demonstrate that our approach outperforms one state-of-the-arts method, and can provide biologists a computational way to switch between microscopy image modalities, so biologists can combine the advantages of different image modalities to better visualize and analyze specimens over time, without purchasing all types of microscopy image modalities or switching between imaging systems back-and-forth during time-lapse experiments.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Intelligent Computing, Networked Control, and Their Engineering Applications 1st ed. 2017

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丛书名： Communications in Computer and Information Science

2017年

作者： Dong Yue Chen Peng Dajun Du Tengfei Zhang Min Zheng Qinglong Han

ISBN: (数字)9789811063732

ISBN: (纸本)9789811063725

The three-volume set CCIS 761, CCIS 762, and CCIS 763 constitutes the thoroughly refereed proceedings of the International conference on Life System Modeling and Simulation, LSMS 2017, and of the International conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2017, held in Nanjing, China, in September 2017. The 208 revised full papers presented were carefully reviewed and selected from over 625 submissions. The papers of this volume are organized in topical sections on: Biomedical Signal processing; Computational Methods in Organism Modeling; Medical Apparatus and Clinical Applications; Bionics Control Methods, algorithms and Apparatus; Modeling and Simulation of Life systems; Data Driven Analysis; image and Video processing; Advanced Fuzzy and Neural Network Theory and algorithms; Advanced Evolutionary Methods and Applications; Advanced Machine Learning Methods and Applications; Intelligent Modeling, Monitoring, and Control of Complex Nonlinear systems; Advanced Methods for Networked systems; Control and Analysis of Transportation systems; Advanced Sliding Mode Control and Applications; Advanced Analysis of New Materials and Devices; Computational Intelligence in Utilization of Clean and Renewable Energy Resources; Intelligent Methods for Energy Saving and Pollution Reduction; Intelligent Methods in Developing Electric Vehicles, Engines and Equipment; Intelligent Computing and Control in Power systems; Modeling, Simulation and Control in Smart Grid and Microgrid; Optimization Methods; Computational Methods for Sustainable Environment.

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Advanced Computational Methods in Life System Modeling and Simulation 1st ed. 2017

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丛书名： Communications in Computer and Information Science

2017年

作者： Minrui Fei Shiwei Ma Xin Li Xin Sun Li Jia Zhou Su

ISBN: (数字)9789811063701

ISBN: (纸本)9789811063695

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PAC-Bayes bounds for stable algorithms with instance-dependent priors 18

PAC-Bayes bounds for stable algorithms with instance-depende...

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Proceedings of the 32nd International conference on Neural Information processing systems

作者： Omar Rivasplata Emilio Parrado-Hernández John Shawe-Taylor Shiliang Sun Csaba Szepesvári UCL University Carlos III of Madrid East China Normal University DeepMind

PAC-Bayes bounds have been proposed to get risk estimates based on a training sample. In this paper the PAC-Bayes approach is combined with stability of the hypothesis learned by a Hilbert space valued algorithm. The PAC-Bayes setting is used with a Gaussian prior centered at the expected output. Thus a novelty of our paper is using priors defined in terms of the data-generating distribution. Our main result estimates the risk of the randomized algorithm in terms of the hypothesis stability coefficients. We also provide a new bound for the SVM classifier, which is compared to other known bounds experimentally. Ours appears to be the first uniform hypothesis stability-based bound that evaluates to non-trivial values.

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The reliability and accuracy of estimating heart-rates from RGB video recorded on a consumer grade camera 3

The reliability and accuracy of estimating heart-rates from ...

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conference on Optics and Biophotonics in Low-Resource Settings iii

作者： Eaton, Adam Vincely, Vinoin Kurt, Paige Lloyd Hugenberg Vishwanath, Karthik Miami Univ Dept Phys Oxford OH 45056 USA Miami Univ Dept Psychol Oxford OH 45056 USA

ISBN: (数字)9781510605527

ISBN: (纸本)9781510605510;9781510605527

Video Photoplethysmography (VPPG) is a numerical technique to process standard RGB video data of exposed human skin and extracting the heart-rate (HR) from the skin areas. Being a non-contact technique, VPPG has the potential to provide estimates of subject's heart-rate, respiratory rate, and even the heart rate variability of human subjects with potential applications ranging from infant monitors, remote healthcare and psychological experiments, particularly given the non-contact and sensor-free nature of the technique. Though several previous studies have reported successful correlations in HR obtained using VPPG algorithms to HR measured using the gold-standard electrocardiograph, others have reported that these correlations are dependent on controlling for duration of the video-data analyzed, subject motion, and ambient lighting. Here, we investigate the ability of two commonly used VPPG-algorithms in extraction of human heart-rates under three different laboratory conditions. We compare the VPPG HR values extracted across these three sets of experiments to the gold-standard values acquired by using an electrocardiogram or a commercially available pulse-oximeter. The two VPPG-algorithms were applied with and without KLT-facial feature tracking and detection algorithms from the Computer Vision MATLAB (R) toolbox. Results indicate that VPPG based numerical approaches have the ability to provide robust estimates of subject HR values and are relatively insensitive to the devices used to record the video data. However, they are highly sensitive to conditions of video acquisition including subject motion, the location, size and averaging techniques applied to regions-of-interest as well as to the number of video frames used for data processing.

关键词： video photoplethysmography cardiovascular biomedical imaging image and signal processing

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Performance Analysis of Video Segmentation 4

Performance Analysis of Video Segmentation

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4th International conference on Advanced Computing and Communication systems (ICACCS)

作者： Aditya, H. Gayatri, T. Santosh, T. Ankalaki, Shilpa Majumdar, Jharna Nitte Meenakshi Inst Technol Dept Comp Sci & Engn Bangalore 560064 Karnataka India Nitte Meenakshi Inst Technol Dept Elect & Commun Engn Bangalore 560064 Karnataka India Nitte Meenakshi Inst Technol Dept MTech Comp Sci & Engn Bangalore 560064 Karnataka India Nitte Meenakshi Inst Technol Ctr Robot Res Bangalore 560064 Karnataka India

ISBN: (纸本)9781509045594

Segmentation plays a vital role in digital media processing, pattern recognition and computer vision. In the last four decades, extensive research has been done and a number of algorithms have been published in the literature. Each one has its own merits and demerits. This paper aims to make a comparative analysis of the most popularly known segmentation methods, namely K-Means, Region Growing, Mean shift and Watershed segmentation for video from different category. The contribution of the paper is twofold: Conventionally, the value of K in K-Means segmentation is not known a prior and given as input. In order to avoid manual input by the user, Region growing segmentation is used. The prominent regions come as output of the region growing method, is used as input for K-Means segmentation. The performance of the segmentation algorithms is determined using a set of Quality Metric (QM) parameters. Segmentation is done on RGB Color Video from Entertainment, Sports and Natural Scenery category. The results show the most suitable algorithm for segmentation for each category of video. UBUNTU C Version 16.04 LTS is used to implement the algorithms.

关键词： image Segmentation Region-growing K-mean Clustering Mean shift segmentation Watershed segmentation QM parameters UBUNTU C Version 16.04 LTS

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Enhanced Gray Scale Skeletonization of Fingerprint Ridges Using Parallel Algorithm 1st

Enhanced Gray Scale Skeletonization of Fingerprint Ridges Us...

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1st International conference on Recent Trends in image processing and Pattern Recognition (RTIP2R)

作者： Dyre, Shoba Sumathi, C. P. SDNB Vaishnav Coll Women Dept Comp Sci Chennai Tamil Nadu India

ISBN: (纸本)9789811048593;9789811048586

Thinning of fingerprint ridges plays a vital role in fingerprint identification systems as it simplifies the subsequent processing steps like fingerprint classification and feature extraction. In this paper, we analyze some of the parallel thinning algorithms and have proposed a methodology for skeletonization of fingerprint ridges directly on gray scale images as significant amount of information and features are lost during the binarization process. This algorithm is based on conditionally eroding the gray level ridges iteratively until a one pixel thick ridge is obtained. Refinement procedures have also been proposed to improve the quality of ridge skeleton. Experiments conducted on sample fingerprint images collected using an optical fingerprint Reader exhibit desirable features of the proposed approach.

关键词： Gray scale image Fingerprint Skeletonization Parallel algorithm Iterative

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A Novel Three-dimensional Indoor Localization Algorithm Based on Visual Visible Light Communication Using Single LED

A Novel Three-dimensional Indoor Localization Algorithm Base...

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IEEE International conference on Automation, Electronics and Electrical Engineering (AUTEEE)

作者： Weipeng Guan Shangsheng Wen Hanlin Zhang Lizhao Liu School of Automation Science and Engineering South China University of Technology Guangzhou Guangdong China School of Materials Science and Engineering South China University of Technology Guangzhou Guangdong China School of Computer Science and Engineering South China University of Technology Guangzhou Guangdong China School of Software Engineering South China University of Technology Guangzhou Guangdong China

ISBN: (纸本)9781538678626;9781538678619

Visible light positioning (VLP) is widely believed to be a cost-effective answer to the growing demand for Indoor positioning. However, because of the nonlinear and highly complicated relationship between 3D world coordinate and 2D image coordinate, there is a need to develop effective VLP location algorithm to locate the positioning terminal using image sensor. Besides, due to the high computational cost of image processing, most existing VLP systems fail to deliver satisfactory performance in terms of real-time ability and positioning accuracy, both of which are crucial for the performance of indoor positioning system. The field of view (FOV) of image sensor affects the number of LEDs. Therefore, this paper proposes an image-sensor-based single-light positioning system and sets up relevant experiments to test the proposed system. What's more, the real-time ability is taken into consideration, which greatly improves the robustness and practicality of the system. As for the ID information of each LED, it utilizes the rolling shutter mechanism of the Complementary Metal Oxide Semiconductor (CMOS) image sensor and combines machine learning algorithm to identify. Different from the traditional LED-ID modulation and demodulation methods, the LED-ID detection and recognition problem was treated as a classification problem in machine learning filed. In this paper, two typical linear classifiers in the case of binary classification problem are introduced. As the features of different LED-ID is linear separable in the feature space, linear classifiers are used to identify the LED-ID. The scheme proposed could improve the speed of LED-ID identification and the robustness of the system by off-line training for the classifiers and online recognition of LED-ID. When there's only one LED in the camera image, it means the distance between the terminal and LED is so close that the diameter of the LED can be measured. Therefore, it is able to use the proposed single-light positioni

关键词： Light emitting diodes image sensors Cameras Robustness Real-time systems Machine learning algorithms Machine learning

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