scholarly journals Рекуррентные соотношения для оценки параметров транспортных подсистем кодирования и передачи изображений

2020 ◽  
Author(s):  
Sh.S. Fahmi ◽  
S.N. Turusov ◽  
N.V. Shatalova ◽  
M.A. Asaul
Keyword(s):  
Transmission Rate ◽  
Recursive Partitioning ◽  
Video Encoding ◽  
Amount Of Information ◽  
Coding Efficiency ◽  
Video Information ◽  
Characteristic Points ◽  
Video Systems ◽  
Encoding Efficiency

Кодирование видеоинформации обычно относится к вычислительной технологии, которая сжимает изображение и преобразует его в двоичный код (т.е. биты), чтобы уменьшить объём информации с целью хранения и передачи. Часто на практике кодирование приводит к потере качества, поэтому оценка эффективности кодирования осуществляется в двух аспектах: во-первых, это скорость передачи, измеряемая в битах, чем меньше, тем лучше во-вторых, понесенные потери, измеряемые субъективным качеством восстановленной видеоинформации, чем выше качество, тем лучше. Современные решения в сфере многоуровневого кодирования видеоинформации представляют стандарты MPEGx, использующие предсказание движения, и относятся к классу, так называемых, трудно формализуемых задач. Эти стандарты исчерпали себя и необходимы новые подходы, позволяющие увеличить эффективность кодирования путем не только максимального приближения к эпсилон-энтропии источника, но и какими информационными средствами достигнуто данное приближение и, в первую очередь, с какими точностью, скоростью и сложностью видеосистем. В работе рассматриваются вопросы, связанные с оценкой количества информации, необходимой для передачи характерных точек объектов на изображениях путём рекурсивного разбиения на полигоны различной формы и размера. Разработаны рекуррентные соотношения для оценки зависимости количества информации для кодирования характерных точек изображений от таких параметров, как разрядности данных, числа полигонов после разбиения, размера и формата изображений.Video encoding typically refers to computing technology that compresses an image and converts it into binary code (i.e. bits) to reduce the amount of information for the purpose of storage and transmission. Often in practice, encoding leads to loss of quality, therefore, the evaluation of encoding efficiency is carried out in two aspects: first, it is the transmission rate measured in bits, the less the better second, the losses incurred, measured by the subjective quality of the restored video information, the higher the quality, the better. Modern solutions in the field of multilevel encoding of video information are MPEGx standards that use motion prediction belong to the class of so-called, difficult to formalize problems. These standards are exhausted and need new approaches to increase the coding efficiency by not only the closest approach to Epsilon-entropy source, but what the information means to achieve this approach and, primarily, the precision, speed and complexity of video systems. The paper deals with the issues related to the assessment of the amount of information required to transfer the characteristic points of objects in the images by recursive partitioning into polygons of different shapes and sizes. Recurrence relations are developed to estimate the dependence of the amount of information to encode the characteristic points of images on such parameters as the bit depth of data, the number of polygons after splitting, the size and format of images.

scholarly journals Cognitive transport video systems

2020 ◽  
pp. 142-154
Author(s):  
Ш.С. Фахми ◽  
И.Г. Малыгин ◽  
С.М. Егоршев ◽  
Ю.Е. Крылов
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Explicit Knowledge ◽  
Human Vision ◽  
Vision Systems ◽  
Bottom Up ◽  
Video Information ◽  
Chip Technology ◽  
Characteristic Points ◽  
Video Systems

Цель развития систем искусственного интеллекта заключается в создании человекоподобного робота со способностями мыслить и принимать решения. Исследования в области компьютерного зрения начались в 1960-х годах. Ограничения в вычислительных ресурсах, отсутствие элементной базы с программируемой логикой и высокая стоимость проектов, выраженная в единицах числа вентилей, не позволяли, на первых этапах, использовать искусственный интеллект при решении задач обработки видеоинформации с наличием шума и помех. В последние десятилетия развитие методов машинного обучения способствовало заметному прогрессу в создании систем технического зрения на основе технологии «система на кристалле». Однако, большинство прикладных программ опираются на чисто восходящие методы проектирования (снизу вверх), не подающиеся обобщению и требующие большие объёмы данных. В данной работе проведен анализ знаний, основанных на результатах тестирования новых методов и технологий, связанных с системами компьютерного зрения за последние десять лет. Показано, что для создания когнитивных систем необходимо использование явных знаний, способствующих улучшению эффективности систем распознавания образов. Интеграция точных знаний с видеоинформацией позволяет получить современные приложения для обучения с использованием визуальных данных, с применением методов «снизу вверх» и «сверху вниз» (аналогичного механизму человеческого зрения). Рассмотрены важные этапы построения когнитивных видеосистем, включающие: сегментацию изображений, алгоритмы нахождения и структуризации характерных точек, принцип доминанты и выделение контуров объектов изображений. The goal for developing artificial intelligence systems is to create a humanoid robot with the ability to think and make decisions. Research in computer vision has started in 1960s. Limitations in computing resources, the lack of an element base with programmable logic and the high cost of projects, expressed in units of the number of gates, did not allow, at the first stages, using artificial intelligence when solving problems of processing video information with the presence of noise and interference. In recent decades, the development of machine learning methods has contributed to significant progress in the creation of vision systems based on the system-on-chip technology. However, most software applications rely on purely bottom-up design methods (bottom-up) that cannot be generalized and require large amounts of data. This paper analyzes the knowledge based on the results of testing new methods and technologies associated with computer vision systems over the past ten years. It is shown that to create cognitive systems, it is necessary to use explicit knowledge that improves the efficiency of pattern recognition systems. Integration of accurate knowledge with video information allows getting modern applications for training using visual data, using the methods "bottom-up" and "top-down" (similar to the mechanism of human vision). The essential stages of building cognitive video systems are considered, including: image segmentation, algorithms for finding and structuring characteristic points, the principle of dominant and selection of contours of image objects.

Stain contamination and embedding in electron microscopy

1986 ◽  
Vol 44 ◽  
pp. 50-53
Author(s):  
Hilton H. Mollenhauer
Keyword(s):  
Electron Microscopy ◽  
Information Retrieval ◽  
Epoxy Resins ◽  
Image Contrast ◽  
Sample Preservation ◽  
Factors Associated ◽  
Amount Of Information ◽  
Electron Microscopical ◽  
Contrast Information

Many factors (e.g., resolution of microscope, type of tissue, and preparation of sample) affect electron microscopical images and alter the amount of information that can be retrieved from a specimen. Of interest in this report are those factors associated with the evaluation of epoxy embedded tissues. In this context, informational retrieval is dependant, in part, on the ability to “see” sample detail (e.g., contrast) and, in part, on tue quality of sample preservation. Two aspects of this problem will be discussed: 1) epoxy resins and their effect on image contrast, information retrieval, and sample preservation; and 2) the interaction between some stains commonly used for enhancing contrast and information retrieval.

scholarly journals Improving Perceived Quality of Live Adaptative Video Streaming

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 948
Author(s):  
Carlos Eduardo Maffini Santos ◽  
Carlos Alexandre Gouvea da Silva ◽  
Carlos Marcelo Pedroso
Keyword(s):  
Video Streaming ◽  
Short Term Memory ◽  
Transmission Rate ◽  
Video Quality ◽  
Video On Demand ◽  
Live Streaming ◽  
Network Congestion ◽  
Congested Networks ◽  
Over The Top

Quality of service (QoS) requirements for live streaming are most required for video-on-demand (VoD), where they are more sensitive to variations in delay, jitter, and packet loss. Dynamic Adaptive Streaming over HTTP (DASH) is the most popular technology for live streaming and VoD, where it has been massively deployed on the Internet. DASH is an over-the-top application using unmanaged networks to distribute content with the best possible quality. Widely, it uses large reception buffers in order to keep a seamless playback for VoD applications. However, the use of large buffers in live streaming services is not allowed because of the induced delay. Hence, network congestion caused by insufficient queues could decrease the user-perceived video quality. Active Queue Management (AQM) arises as an alternative to control the congestion in a router’s queue, pressing the TCP traffic sources to reduce their transmission rate when it detects incipient congestion. As a consequence, the DASH client tends to decrease the quality of the streamed video. In this article, we evaluate the performance of recent AQM strategies for real-time adaptive video streaming and propose a new AQM algorithm using Long Short-Term Memory (LSTM) neural networks to improve the user-perceived video quality. The LSTM forecast the trend of queue delay to allow earlier packet discard in order to avoid the network congestion. The results show that the proposed method outperforms the competing AQM algorithms, mainly in scenarios where there are congested networks.

scholarly journals WAS POSTPONING THE TOKYO 2020 OLYMPIC AND PARALYMPIC GAMES A CORRECT DECISION?

2020 ◽  
Vol 26 (3) ◽  
pp. 191-195 ◽  
Author(s):  
Renato de Carvalho Guerreiro ◽  
Andressa Silva ◽  
Henrique de Araújo Andrade ◽  
Isadora Grade Biasibetti ◽  
Roberto Vital ◽  
...  
Keyword(s):  
Immune System ◽  
Physical Exercise ◽  
Chronic Diseases ◽  
Transmission Rate ◽  
Jet Lag ◽  
Level Of Evidence ◽  
Competition Period ◽  
Regular Physical Exercise ◽  
Paralympic Games

ABSTRACT In December 2019, Wuhan, in China, attracted international attention due to a pneumonia outbreak caused by the new coronavirus (2019-nCoV). Infection by 2019-nCoV is more likely in elderly people with comorbidities or with associated chronic diseases. Due to the high transmission rate among humans, this disease is rapidly disseminated, which led to several events being canceled, including the Tokyo 2020 Olympic and Paralympic Games. The aim of this article is to discuss the risk factors for Olympic and Paralympic athletes, as well as for spectators, that justify the decision to postpone the Tokyo Games 2020. Regular physical exercise is associated with health and the prevention of chronic diseases. Although athletes generally appear to be healthy and physically fit, this may not be true. The immune system, which protects the organism from invasive microorganisms, can be affected by the duration and quality of sleep, as well as by physical exercise which influences the quality of the immune response. High volumes of high-intensity physical exercise, as well as changes in sleep patterns during the pre-competition period and the impacts of jet lag on athletes traveling for the Tokyo Games in 2020 may lead to immune system suppression, making these groups more vulnerable to infection by 2019-nCoV. Moreover, during the period planned for the games in 2020 the pandemic may be subsiding in some countries and increasing in others, and this was also taken into consideration as a risk factor. Hence, the decision taken to postpone the Tokyo 2020 Olympic and Paralympic Games until 2021 due to the 2019-nCoV was the correct one, and was extremely important to protect the health of Olympic and Paralympic athletes, as well as spectators. Level of evidence V; expert opinion .

scholarly journals A method for reducing information redundancy of digital images for cloud storage

Connectivity ◽  
2020 ◽  
Vol 148 (6) ◽  
Author(s):  
Yu. I. Katkov ◽  
◽  
O. S. Zvenigorodsky ◽  
O. V. Zinchenko ◽  
V. V. Onyshchenko ◽  
...  
Keyword(s):  
Image Compression ◽  
Video Compression ◽  
Cloud Storage ◽  
Video Data ◽  
Information Redundancy ◽  
High Quality ◽  
Video Information ◽  
Quality Video ◽  
High Quality Video

The article is devoted to the topical issue of finding new effective and improving existing widespread compression methods in order to reduce computational complexity and improve the quality of image-renewable image compression images, is important for the introduction of cloud technologies. The article presents a problem To increase the efficiency of cloud storage, it is necessary to determine methods for reducing the information redundancy of digital images by fractal compression of video content, to make recommendations on the possibilities of applying these methods to solve various practical problems. The necessity of storing high-quality video information in new HDTV formats 2k, 4k, 8k in cloud storage to meet the existing needs of users has been substantiated. It is shown that when processing and transmitting high quality video information there is a problem of reducing the redundancy of video data (image compression) provided that the desired image quality is preserved, restored by the user. It has been shown that in cloud storage the emergence of such a problem is historically due to the contradiction between consumer requirements for image quality and the necessary volumes and ways to reduce redundancy of video data, which are transmitted over communication channels and processed in data center servers. The solution to this problem is traditionally rooted in the search for effective technologies for compressing, archiving and compressing video information. An analysis of video compression methods and digital video compression technology has been performed, which reduces the amount of data used to represent the video stream. Approaches to image compression in cloud storage under conditions of preservation or a slight reduction in the amount of data that provide the user with the specified quality of the restored image are shown. Classification of special compression methods without loss and with information loss is provided. Based on the analysis, it is concluded that it is advisable to use special methods of compression with loss of information to store high quality video information in the new formats HDTV 2k, 4k, 8k in cloud storage. The application of video image processing and their encoding and compression on the basis of fractal image compression is substantiated. Recommendations for the implementation of these methods are given.

scholarly journals Content profiling and translation scenarios

2016 ◽  
Vol 3 (1) ◽  
pp. 18-37 ◽  
Author(s):  
Sheila Castilho ◽  
Sharon O'Brien
Keyword(s):  
Strategic Management ◽  
End Users ◽  
Huge Amount ◽  
Amount Of Information ◽  
Different Content

Today’s companies are overwhelmed with the need to create a huge amount of content, faster, customized, and for numerous media platforms, in order to support their products. Struggling with managing this amount of information, companies have now realised that the strategic management of multilingual enterprise content has become essential. Strategic management involves profiling content, its uses, its end readers and deciding what should be translated, into which languages, using which translation processes and technology. Profiling enterprise content is necessary in order to maximize the quality of the content and its translation at minimum effort and cost by reducing complexity. By targeting the audience, content could be categorized according to the expectation of the end-users, and so, different translation scenarios can be applied to different content types. This article will discuss the challenges of profiling content within the enterprise, as well as translation scenarios focusing on the decisions that push content in one or another direction.

Improving the tracking quality of the weld seam butt with V-form grooving by using Kalman filter and neural network

2021 ◽  
Author(s):  
Keyword(s):  
Neural Network ◽  
Kalman Filter ◽  
Colored Noise ◽  
Weld Seam ◽  
Vision Sensor ◽  
Laser Vision Sensor ◽  
Characteristic Points ◽  
Laser Vision ◽  
Weld Seams

An algorithm for tracking of the welded seams grooving by using a Kalman filter based on six characteristic points of the profile obtained using the RF627 laser vision sensor is proposed. In order to reduce the error in weld seams control, a multilayer neural network with a backpropagation algorithm is created to compensate for errors caused by colored noise when using the Kalman filter. Experimental results show that when the algorithm is applied, the error in tracking the trajectory of weld seams is reduced. Keywords tracking of weld seams; multilayer/multi-pass welding; Kalman filter; multilayer perceptron

scholarly journals Considerations for Continuing Semielective and Emergency Otolaryngological Procedures During the COVID-19 Pandemic

2020 ◽  
Vol 100 (1) ◽  
pp. 19-25
Author(s):  
Sarina K. Mueller ◽  
Maximilian Traxdorf ◽  
Konstantinos Mantsopoulos ◽  
Antoniu-Oreste Gostian ◽  
Matti Sievert ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Emergency Surgery ◽  
Transmission Rate ◽  
Medical Personnel ◽  
Human Beings ◽  
Threatening Condition ◽  
Long Time ◽  
Life Threatening

Introduction: During the COVID-19 pandemic, worldwide over 600,000 human beings died due to the cause of the disease. In order to deescalate the transmission rate and to avoid crush loading the countries medical health systems social distancing, face masks, and lockdowns have been considered essential by the majority of governments. Whereas some countries have highly reduced or completely stopped otorhinolaryngological procedures, other countries have continued selected surgeries. The objective of this study was to analyze procedures and outcomes of continuing semielective and emergency surgeries during the COVID-19 pandemic. Methods: Retrospective analysis of n = 750 patients who received semi-elective or emergency surgery between March 26 and June 16, 2020, in the Otolaryngology Department of the Friedrich-Alexander-University of Erlangen-Nürnberg. All patients were screened for COVID symptoms and swabbed for SARS-CoV-2 prior to surgery. Results: Of the n = 750 patients, n = 699 patients received semielective surgery and n = 51 emergency surgery. For 27 patients, the swab result could not be awaited due to a life-threatening condition. In these cases, surgery was performed in full protective equipment. No patient was tested positive during or after the surgery (follow-up 45 to 127 days). No member of the medical personnel showed symptoms or was tested positive after contact with patients. Due to the continuation of surgeries, patients’ lives were saved and improvement of long-term quality-of-life and outcomes is anticipated. Conclusions: Continuing selected otorhinolaryngological surgeries is crucial for patients’ health, survival, and long-time quality of life, yet, the protection of the medical personnel has to be granted.

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