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conference on Applications of Digital image processing XL

作者： Ushenko, Yu. O. Vanchuliak, O. Bodnar, G. B. Ushenko, V. O. Grytsyuk, M. Pavlyukovich, N. Pavlyukovich, O. V. Antonyuk, O. Chernivtsi Natl Univ 2 Kotsyubinsky Str UA-58012 Chernovtsy Ukraine Bukovinian State Med Univ UA-58000 Chernovtsy Ukraine

ISBN: (数字)9781510612501

ISBN: (纸本)9781510612501;9781510612495

A new technique of Mueller-matrix mapping of polycrystalline structure of histological sections of biological tissues is suggested. The algorithms of reconstruction of distribution of parameters of linear and circular dichroism of histological sections liver tissue of mice with different degrees of severity of diabetes are found. The interconnections between such distributions and parameters of linear and circular dichroism of liver of mice tissue histological sections are defined. The comparative investigations of coordinate distributions of parameters of amplitude anisotropy formed by Liver tissue with varying severity of diabetes (10 days and 24 days) are performed. The values and ranges of change of the statistical (moments of the 1st - 4th order) parameters of coordinate distributions of the value of linear and circular dichroism are defined. The objective criteria of cause of the degree of severity of the diabetes differentiation are determined.

关键词： polarization Fourier optics and signal processing imaging systems medical and biological imaging

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Cartooning for Enhanced Privacy in Lifelogging and Streaming Videos 30

Cartooning for Enhanced Privacy in Lifelogging and Streaming...

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

作者： Hassan, Eman T. Hasan, Rakibul Shaffer, Patrick Crandall, David Kapadia, Apu Indiana Univ Bloomington Sch Informat & Comp Bloomington IN 47405 USA

ISBN: (纸本)9781538607336

We describe an object replacement approach whereby privacy-sensitive objects in videos are replaced by abstract cartoons taken from clip art. Our approach uses a combination of computer vision, deep learning, and image processing techniques to detect objects, abstract details, and replace them with cartoon clip art. We conducted a user study (N=85) to discern the utility and effectiveness of our cartoon replacement technique. The results suggest that our object replacement approach preserves a video's semantic content while improving its privacy by obscuring details of objects.

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

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Multi-functional informational - instrumental technology for the hydrochemical monitoring 21

Multi-functional informational - instrumental technology for...

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21st International conference on Control systems and Computer Science (CSCS)

作者： Nitu, Costica Dobrescu, Anda Sabena Krapivin, Vladimir F. Mkrtchyan, Ferdenant A. Soldatov, Vladimir Yu Univ Politehn Bucuresti Bucharest Romania Russian Acad Sci Kotelnikov Inst Radioengn & Elect Moscow Russia

ISBN: (纸本)9781538618394

Water quality operative control is considered when chemical analysis is possible. In this paper, new information-instrumental technology is proposed. This technology is based on combined use of optical instrumental means and recognition algorithms of spectral images. Adaptive multi-functional system is proposed to be as tool for operative diagnosis of hydrochemical processes. This system has two levels of items that realize specific functions of monitoring data analysis and processing. The system measuring functions are based on spectroellipsometric technology. Examples of the system use are given.

关键词： water quality monitoring diagnostics algorithm spectroellipsometer image recognition

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Playback detection using machine learning with spectrogram features approach 10

Playback detection using machine learning with spectrogram f...

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10th International conference on Human System Interactions (HSI)

作者： Dembski, Jerzy Ruminski, Jacek Gdansk Univ Technol Fac Elect Telecommun & Informat Ul Narutowicza 11-12 PL-80952 Gdansk Poland

ISBN: (纸本)9781509046881

This paper presents 2D image processing approach to playback detection in automatic speaker verification ( ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients ( HOG) with support vector machines ( SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks ( CNN) were compared on different data partitions in respect of speakers or playback devices: for instance with different speakers in training and test subsets. The playback detection systems were trained and tested on two speech datasets S-1 and S-2 manufactured independently by two different institutions. The test error for both datasets oscillates about the level of 1% for HOG+SVM and even below it for CNN in bigger S-1 base. In cross validation scenario in which one base was used for training and second base for the test the results were very poor what suggests that the information relevant for playback detection appeared in each base in different way.

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

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Leveraging Deep Preference Learning for Indexing and Retrieval of Biomedical images 8

Leveraging Deep Preference Learning for Indexing and Retriev...

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8th International IEEE/EMBS conference on Neural Engineering (NER)

作者： Pang, Shuchao Orgun, Mehmet A. Du, Anan Yu, Zhezhou Jilin Univ Coll Comp Sci & Technol Qianjin St 2699 Changchun Jilin Peoples R China Macquarie Univ Dept Comp Sydney NSW 2109 Australia China Mobile HangZhou Informat Technol Co Ltd Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781509046034

This paper presents an original framework based on deep learning and preference learning to retrieve and characterize biomedical images for assisting physicians in diagnosing complex diseases with potentially only small differences between them. In particular, we use deep learning to extract the high-level and compact features for biomedical images. In contrast to the traditional biomedical algorithms or general image retrieval systems that only consider the use of pixel and/or hand-crafted features to represent images, we utilize deep neural networks for feature discovery of biomedical images. Moreover, in order to be able to index the similarly referenced images, we introduce preference learning in a novel way to learn what kinds of images we need so that we can obtain the similarity ranking list of biomedical images. We evaluate the performance of our system in detailed experiments over the well-known available OASIS-MRI database for whole brain neuroimaging as a benchmark and compare it with those of the traditional biomedical and general image retrieval approaches. Our proposed system exhibits an outstanding retrieval ability and efficiency for biomedical image applications.

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

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Predictor-Based controllers for UAVs with input delay

Predictor-Based controllers for UAVs with input delay

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IEEE International conference on Advanced Intelligent Mechatronics (AIM)

作者： Cao, Ning Lynch, Alan F. Univ Alberta Dept Elect & Comp Engn Edmonton AB Canada

ISBN: (纸本)9781509060009

This paper proposes predictor-based controllers for a class of systems with input delay and which relate to the control of Unmanned Aerial Vehicles (UAVs). The first control problem considered is motion control where position of the vehicle is regulated to a constant. The second problem arises from visual servoing where camera measurements are used to control the vehicle's relative pose to a visual target. The UAV control is assumed to have an inner-outer loop structure with the delay appearing only in the outer loop variables. In the visual servoing case, a projection-based adaptive law is developed since depth information cannot be determined from the image of a single camera. Sufficient conditions in form of linear matrix inequalities (LMIs) are given for global asymptotic stability of the outer-loop.

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

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Development and future trends in the application of visualization toolkit (VTK): The case for medical image 3D reconstruction

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AIP conference Proceedings 2019年第1期2092卷

作者： Welsey Daniel C. Advincula Jose Antonio G. Choco Kryzz Amiel G. Magpantay Leonard Angelo N. Sabellina, III Jolo Gerard Miel F. Tolentino Renann G. Baldovino Nilo T. Bugtai Aaron Raymond See Yi-Chun Du 1Manufacturing Engineering and Management (MEM) Department De La Salle University 2401 Taft Avenue 0922 Manila Philippines 2Department of Electrical Engineering Southern Taiwan University of Science and Technology No. 1 Nantai Street Yongkang District Tainan City Taiwan 710

Three-dimensional reconstruction of medical images plays a vital role in clinical medicine and medical research. It serves as a powerful tool to help doctors analyze multiple 2D medical images in a 3D perspective. The developed 3D model offers a faster and accurate approach in clinical diagnosis and therapy. Before, the development of 3D reconstruction programs it has always been a challenge to visualize in a 3D perspective but with the advent of powerful computing and graphics processing, medical imaging equipment development is on the rise. The advancement of 3D image reconstruction is not only due to the innovative hardware, but also because of the increase in open-source platforms or libraries, such as visualization toolkit (VTK), that assist on its development to provide an information visualization framework and advanced 3D modeling techniques. VTK is an object-oriented 3D graphics software program that is free to obtain and used both for open- and closed-source applications such as 3D computer graphics, image processing, and visualization. In medical imaging, data from ultrasound systems, magnetic resonance imaging (MRI), and computed tomography (CT) scans can be managed in VTK. Different algorithms of image processing such as color mapping, image re-slicing or resampling, iso-contouring, thresholding, and other algorithms can be utilized to make volume images from the data. Subsequently, data presentation is simplified with the data reconstruction through the use of supplemental software for analysis. VTK library contains a large number of filters, which are multi-threaded to facilitate parallel processing and interpretation. In this paper, recent technologies on the application of VTK for 3D reconstruction of biomedical images will be presented. Moreover, current methodologies will be discussed to clearly understand the different integral steps needed in image data conversion.

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A Novel Algorithm for Laser Spot Detection Based on Quaternion Discrete Cosine Transform

A Novel Algorithm for Laser Spot Detection Based on Quaterni...

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International conference on Intelligent and Interactive systems and Applications (IISA)

作者： Miao, Xiaodong Shi, Xiang Xu, Zhixing Wang, Aiqing Wang, Wei Kangni Mech & Elect Co Ltd Nanjing 210009 Jiangsu Peoples R China Nanjing Univ Technol Sch Mech & Power Engn Nanjing 211800 Jiangsu Peoples R China

ISBN: (纸本)9783319495682;9783319495675

Laser spot detection is an important problem in optical measurement. The precision and speed of the detection algorithm influence the optical measurement system directly. The traditional algorithms such as Hough Transform and Gravity model are unsatisfactory in complex conditions. The laser spot detection algorithm referred in this paper is based on the quaternion discrete cosine transform and moment and a method is adopted to approximate the edge of the laser spot. Not only the center and edge can be detected simultaneously but also the robustness of noise is better than others. The algorithm is suitable for the real-time optical measurement.

关键词： Laser spot image processing Quaternion discrete cosine transform

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Development of an Embedded Atmospheric Turbulence Mitigation Engine 2

Development of an Embedded Atmospheric Turbulence Mitigation...

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conference on Long-Range Imaging II

作者： Paolini, Aaron Bonnett, James Kozacik, Stephen Kelmelis, Eric EM Photon Inc 51 East Main StSuite 203 Newark DE 19711 USA Univ Delaware Dept Elect & Comp Engn 140 Evans Hall Newark DE 19716 USA

ISBN: (数字)9781510609105

ISBN: (纸本)9781510609099;9781510609105

Methods to reconstruct pictures from imagery degraded by atmospheric turbulence have been under development for decades. The techniques were initially developed for observing astronomical phenomena from the Earth's surface, but have more recently been modified for ground and air surveillance scenarios. Such applications can impose significant constraints on deployment options because they both increase the computational complexity of the algorithms themselves and often dictate a requirement for low size, weight, and power (SWaP) form factors. Consequently, embedded implementations must be developed that can perform the necessary computations on low-SWaP platforms. Fortunately, there is an emerging class of embedded processors driven by the mobile and ubiquitous computing industries. We have leveraged these processors to develop embedded versions of the core atmospheric correction engine found in our ATCOM software. In this paper, we will present our experience adapting our algorithms for embedded systems on a chip (SoCs), namely the NVIDIA Tegra that couples general-purpose ARM cores with their graphics processing unit (GPU) technology and the Xilinx Zynq which pairs similar ARM cores with their field-programmable gate array (FPGA) fabric.

关键词： Atmospheric Turbulence Turbulence Mitigation Atmospheric Compensation image processing LongRange imagery image Enhancement Real-Time Embedded

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Machine-learning algorithms for helicopter hydraulic faults detection: model based research

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Journal of Physics: conference Series 2019年第5期1368卷

作者： A M Gareev E Yu Minaev D M Stadnik N S Davydov V I Protsenko I A Popelniuk A V Nikonorov A G Gimadiev Samara National Research University Moskovskoe Shosse 34A Samara Russia 443086 Image Processing Systems Institute of RAS - Branch of the FSRC 'Crystallography and Photonics' RAS Molodogvardejskaya street 151 Samara Russia 443001

The problem of automatic reliability monitoring and reliability-centered maintenance is increasingly important today. In this paper, we compare the accuracy of four machine learning approaches for fault detection in a hydraulic system. The first three approaches are based on SVM classifiers with linear, polynomial and RBF kernels and the last one is a gradient boosting on oblivious decision trees. We evaluate algorithms on the synthetic dataset generated by our simulation model of the helicopter hydraulic system and show that high accuracy fault detection can be achieved.

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