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Conference on Adaptive Optics systems vii

作者： Lukin, V. P. Botygina, N. N. Antoshkin, L., V Borzilov, A. G. Emaleev, O. N. Konyaev, P. A. Kovadlo, P. G. Kolobov, D. Yu Shikhovtsev, A. Yu Chuprakov, S. A. Russian Acad Sci VE Zuev Inst Atmospher Opt Siberian Branch Tomsk 634055 Russia Russian Acad Sci Inst Solar Terr Phys Siberian Branch Irkutsk 664033 Russia

ISBN: (纸本)9781510636842

A multi-cascade adaptive optical system for imaging and image stabilization for the Large Solar Vacuum Telescope is described. This system was created in 2017 by specialists of the V.E. Zuev Institute of Atmospheric Optics SB RAS, Tomsk, with the technical support of the Institute of Solar-Terrestrial Physics SB RAS, Irkutsk. The system has been tested at the Large Solar Vacuum Telescope (Baikal Astrophysical Observatory) and demonstrated its efficiency. Along with the first cascade of adaptive image stabilization by a tip-tilt corrected mirror, this system employs the second imaging cascade based on correction with a flexible mirror controlled by a specialized wavefront sensor, as well as the third cascade for real-time post-detector processing of video camera frames. Reliable experimental data confirming the efficiency of the multi-cascade adaptive system for image formation and stabilization have been obtained. Three high-rate digital video cameras recording simultaneously digital images with rates from 300 to 980 frames per second were used to test the system. The mirror correcting wavefront tilts and operating in a closed optical feedback loop was controlled by the specially developed software including the fast correlation tracking algorithm. The post-detector digital imaging was performed with a special software for processing of video camera frames in real time with the use of modern high-speed parallel algorithms based on the Intel MKL and IPP libraries.

关键词： astronomy solar telescope astroclimate turbulence adaptive optics tilt corrector correction cascade

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Airborne Intelligence, Surveillance, Reconnaissance (ISR) systems and Applications vii

Airborne Intelligence, Surveillance, Reconnaissance (ISR) Sy...

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Airborne Intelligence, Surveillance, Reconnaissance (ISR) systems and Applications vii

ISBN: (纸本)9780819481320

The proceedings contain 33 papers. The topics discussed include: 3D imaging without range information;lock-in imaging with synchronous digital mirror demodulation;chromotomographic imager field demonstration results;multisensor airborne imagery collection and processing onboard small unmanned systems;use of compact synthetic aperture radar systems to assist with device detection and discrimination;compact survey and inspection day/night image sensor suite for small unmanned aircraft systems (EyePod);a simulation of wide area surveillance (WAS) systems and algorithm for digital elevation model (DEM) extraction;opto-mechanical review of a light weight compact visible zoom camera;robust component-based car detection and counting in aerial imagery based on the mean-shift color space clustering;advanced vehicle tracking in persistent aerial surveillance video;and directed area search using socio-biological vision algorithms and cognitive Bayesian reasoning.

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A real-time person tracking system based on SiamMask network for intelligent video surveillance

A real-time person tracking system based on SiamMask network...

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作者： Ahmed, Imran Jeon, Gwanggil Centre for Excellence in Information Technology IMSciences Peshawar 1-A Sector E-5 Phase VII Hayatabad Peshawar Pakistan Department of Embedded Systems Engineering Incheon National University Incheon Korea Republic of

Real-time video surveillance systems are widely deployed in various environments, including public areas, commercial buildings, and public infrastructures. Person detection is a key and crucial task in different video surveillance applications, such as person detection, segmentation, and tracking. Researchers presented different image processing and artificial intelligence-based approaches (including machine and deep learning) for person detection and tracking, but mainly comprised of frontal view camera perspective. A real-time person tracking and segmentation system is introduced in this work, using an overhead camera perspective. The system applied a deep learning-based algorithm, i.e., SiamMask, a simple, versatile, fast, and surpassing other real-time tracking algorithms. The algorithm also performs segmentation of the target person by combining a mask branch to the fully convolutional twin neural network for target or person tracking. First, the person video sequences are obtained from an overhead perspective, and then additional training is performed with the help of transfer learning. Finally, a comparison is performed with other tracking algorithms. The SiamMask algorithm delivers good results, with a tracking accuracy of 95%. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Monitoring

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Evaluation of active appearance models for cardiac MRI

Evaluation of active appearance models for cardiac MRI

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Workshops Bildverarbeitung fur die Medizin: Algorithmen Systeme Anwendungen, BVM 2006 - Workshop on image processing for Medicine: algorithms - systems - Applications, BVM 2006

作者： Böhler, Tobias Boskamp, Tobias Müller, Heinrich Hennemuth, Anja Peitgen, Heinz-Otto MeVis - Center for Medical Diagnostic Systems and Visualization Universitätsallee 29 28359 Bremen Germany LS VII Computer Graphics University of Dortmund Otto-Hahn-Strasse 16 44221 Dortmund Germany

ISBN: (纸本)9783540321361

Robust delineation of short-axis cardiac magnetic resonance images (MRI) is a fundamental precondition for functional heart diagnostics. Segmentation of the myocardium and the left ventricular blood pool allows for the analysis of important quantitative parameters. Modelbased segmentation methods based on representative image data provide an inherently stable tool for this *** present an implementation and evaluation of 3-D Active Appearance Models for the segmentation of the left ventricle using actual clinical case images. Models created from varying random data sets have been evaluated and compared with manual segmentations.

关键词： Magnetic resonance imaging

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Photorealistic generation of histological and histopathological slides

Photorealistic generation of histological and histopathologi...

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Workshops Bildverarbeitung fur die Medizin: Algorithmen Systeme Anwendungen, BVM 2006 - Workshop on image processing for Medicine: algorithms - systems - Applications, BVM 2006

作者： Weichert, Frank Linder, Roland Landes, Constantin A. Groh, Andreas Ẅunderlich, Robin Wagner, Mathias Lehrstuhl Informatik VII Universität Dortmund Germany Institut Für Medizinische Informatik Universität zu Lübeck Germany Klinik und Poliklinik Für Kiefer- und Plastische Chirurgie Germany Institut Für Angewandte Mathematik Universität des Saarlandes Germany Institut Für Allgemeine und Spezielle Pathologie Universität des Saarlandes Germany

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Multiple Transform Selection in Versatile Video Coding: a Review 8

Multiple Transform Selection in Versatile Video Coding: a Re...

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8th International Conference on Advanced Computing and Communication systems, ICACCS 2022

作者： Chowdary, T. Anil Nalluri, Purnachand VIT-AP University School of Electronics Engineering Inavolu Andhra Pradesh 522237 India

ISBN: (纸本)9781665408165

Tools for Transform Coding in coding of video relied on DCT-II traditionally for mapping residuals of image/video signals. Residual mapping can be done to a domain where quantizing and encoding tools give better efficiency in coding than domain of spatial. Nonetheless, DCT-II cannot model available types of residual image/video signals effectively. DCT-II modeling all types of residuals is not possible because of non-stationary behaviour of contents of video. So, to improve performance in compression of 4 X 4 blocks, DST-vii was instigated into VVC. In this paper This Paper presents survey of different algorithms for selection of optimal transform for each block (4X4, 8X8, 16X16, 32X32 and 64X64) of residual image/video for VVC. © 2022 IEEE.

关键词： Video signal processing

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Multiresolution target discrimination during image formation

Multiresolution target discrimination during image formation

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algorithms for Synthetic Aperture Radar imagery vii

作者： Kaplan, Lance M. Oh, Seung-Mok McClellan, James H. Clark Atlanta Univ Atlanta United States

This paper presents a novel scheme to detect and discriminate landmines from other clutter objects during the image formation process for ultra-wideband (UWB) synthetic aperture radar (SAR) systems. By identifying likely regions containing the targets of interest, i.e., landmines, it is possible to speed up the overall formation time by pruning the processing to resolve regions that do not contain targets. The image formation algorithm is a multiscale approximation to standard backprojection known as the quadtree that uses a 'divide-and-conquer' strategy. The intermediate quadtree data admits multiresolution representations of the scene, and we develop a contrast statistic to discriminate structured/diffuse regions and an aperture diversity statistic to discriminate between regions containing mines and desert scrub. The potential advantages of this technique are illustrated using data collected at Yuma, AZ by the ARL BoomSAR system.

关键词： Radar imaging

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Encyclopedia of MATLAB: Science and Engineering - Volume vii

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2015年

作者： Louis Young

ISBN: (纸本)9781632401953

Proportional-integral-derivative (PID) controllers are widely regarded as the most important tool for a control engineer. However, in today's era of computer science, MATLAB has acquired the position of an essential tool for the modern system engineering. This book has been written in a manner to serve as a practical guide for both practicing engineers and engineering students. Numerous applications use MATLAB as the working framework which shows that it is an effective, comprehensive and handy technique for performing technical computations. This book discusses various prominent applications in which MATLAB is used: in image processing algorithms, and from Graphic User Interface (GUI) design for educational purposes to Simulink embedded systems.

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Long Term Safety Area Tracking (LT-SAT) with online failure detection and recovery for robotic minimally invasive surgery

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MEDICAL image ANALYSIS 2018年 45卷 13-23页

作者： Penza, Veronica Du, Xiaofei Stoyanov, Danail Forgione, Antonello Mattos, Leonardo S. De Momi, Elena Politecn Milan Dept Elect Informat & Bioengn Pzza L Da Vinci 32 I-20133 Milan Italy Ist Italiano Tecnol Dept Adv Robot Via Morego 30 I-16163 Genoa Italy UCL Ctr Med Image Comp Dept Comp Sci London England Osped Niguarda Ca Granda Pzza Osped Maggiore 3 I-20162 Milan Italy

Despite the benefits introduced by robotic systems in abdominal Minimally Invasive Surgery (MIS), major complications can still affect the outcome of the procedure, such as intra-operative bleeding. One of the causes is attributed to accidental damages to arteries or veins by the surgical tools, and some of the possible risk factors are related to the lack of sub-surface visibilty. Assistive tools guiding the surgical gestures to prevent these kind of injuries would represent a relevant step towards safer clinical procedures. However, it is still challenging to develop computer vision systems able to fulfill the main requirements: (i) long term robustness, (ii) adaptation to environment/object variation and (iii) real time processing. The purpose of this paper is to develop computer vision algorithms to robustly track soft tissue areas (Safety Area, SA), defined intra-operatively by the surgeon based on the real-time endoscopic images, or registered from a pre-operative surgical plan. We propose a framework to combine an optical flow algorithm with a tracking-by-detection approach in order to be robust against failures caused by: (i) partial occlusion, (ii) total occlusion, (iii) SA out of the field of view, (iv) deformation, (v) illumination changes, (vi) abrupt camera motion, (vii), blur and (viii) smoke. A Bayesian inference-based approach is used to detect the failure of the tracker, based on online context information. A Model Update Strategy (MUpS) is also proposed to improve the SA re-detection after failures, taking into account the changes of appearance of the SA model due to contact with instruments or image noise. The performance of the algorithm was assessed on two datasets, representing ex-vivo organs and in-vivo surgical scenarios. Results show that the proposed framework, enhanced with MUpS, is capable of maintain high tracking performance for extended periods of time (similar or equal to 4 min - containing the aforementioned events) with high precisi

关键词： Long-term tissue tracking Tracking failure detection Model Update Strategy Robotic minimally invasive surgery

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Natural image classification in non linear network model

Natural image classification in non linear network model

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SPIE - The International Society for Optical Engineering

作者： Azhar, Hanif Iftekharuddin, Khan Kozma, Robert Admala, Abhinav Intelligent Systems and Image Processing Lab. Electrical and Computer Engineering Department University of Memphis TN 38152 United States Computer Science Department University of Memphis TN 38152 United States

We study the non-linear behavior of the KIII model for natural image classification. The KIII model is designed to be a dynamic computational model that simulates the sensory cortex. The KIII model has been explored for rudimentary pattern recognition and classification in noisy environment [1-3]. We extend the study of KIII models in understanding whether self-organized neural populations can be exploited into perceptual and memory producing systems such as in natural image classification. Our goal is to obtain a quantitative index on how well the KIII model behaves when it is assigned the task to identify and distinguish one class of natural image from the other based on color and texture features. For twenty training data, twenty validation data and eighty test data set for four image classes, we obtain 80% correct classification using the KIII. We compare a standard non linear neural network tools such as back propagation for the classification of the same set of natural images and obtain 65% correct classification. We conclude that dynamic neural computational models such as KIII may be suitable candidates for natural image classification.

关键词： image segmentation

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