scholarly journals Method for Improving an Image Segment in a Video Stream Using Median Filtering and Blind Deconvolution Based on Evolutionary Algorithms

2020 ◽  
pp. paper80-1-paper80-11
Author(s):  
Andrey Trubakov ◽  
Anna Trubakova
Keyword(s):  
Evolutionary Algorithms ◽  
Blind Deconvolution ◽  
Main Idea ◽  
Video Stream ◽  
Poor Quality ◽  
Surveillance Systems ◽  
Focal Distance ◽  
Noise Component ◽  
Image Segment ◽  
Software Product

Video surveillance systems, dash cameras and security systems have become an inescapable part of the most institutions ground environment. Their main purpose is to prevent incidents and to analyze the situation in case of extemporaneous events. Though as often as not it is necessary to increase an image segment many times over to investigate some incidents. Sometimes it is dozens of times. However, the obtained material is mostly of poor quality. This is connected either with noise or resolution characteristics, including focal distance. The paper considers an approach for improving image segments, which were obtained after multiple zooming. The main idea of the proposed solution is to use methods of blind deconvolution. In this case, the selection of restoration parameters is carried out using evolutionary algorithms with automatic evaluation of the result. That seems like the most important detail here is pre-processing besides noise minimization within the image, because when the image is repeatedly enlarged the effect of the noise component also increases. To avoid this thing, we suggest using ordinal statistics and average convolution for a series of images. The proposed solution was implemented as a software product, and its operation was tested on a number of video segments made under different shooting conditions. The results are presented at the end of this article.

scholarly journals Quality Assessment of Some Essential Children’s Medicines Sold in Licensed Outlets in Ashanti Region, Ghana

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Grace Frimpong ◽  
Kwabena Ofori-Kwakye ◽  
Noble Kuntworbe ◽  
Kwame Ohene Buabeng ◽  
Yaa Asantewaa Osei ◽  
...  
Keyword(s):  
Quality Evaluation ◽  
Active Pharmaceutical Ingredient ◽  
Poor Quality ◽  
Surveillance Systems ◽  
Ashanti Region ◽  
The United Kingdom ◽  
The Poor ◽  
Medicine Outlets ◽  
Children’S Medicines

The quality of 68 samples of 15 different essential children’s medicines sold in licensed medicine outlets in the Ashanti Region, Ghana, was evaluated. Thirty-two (47.1%) of the medicines were imported, mainly from India (65.6%) and the United Kingdom (28.1%), while 36 (52.9%) were locally manufactured. The quality of the medicines was assessed using content of active pharmaceutical ingredient (API), pH, and microbial limit tests, and the results were compared with pharmacopoeial standards. Twenty-six (38.2%) of the samples studied passed the official content of API test while 42 (61.8%) failed. Forty-nine (72.1%) of the samples were compliant with official specifications for pH while 19 (27.9%) were noncompliant. Sixty-six (97.1%) samples passed the microbial load and content test while 2 (2.9%) failed. Eighteen (26.5%) samples passed all the three quality evaluation tests, while one (1.5%) sample (CFX1) failed all the tests. All the amoxicillin suspensions tested passed the three evaluation tests. All the ciprofloxacin, cotrimoxazole, flucloxacillin, artemether-lumefantrine, multivitamin, and folic acid samples failed the content of API test and are substandard. The overall API failure rate for imported products (59.4%) was comparable to locally manufactured (63.9%) samples. The results highlight the poor quality of the children’s medicines studied and underscore the need for regular pharmacovigilance and surveillance systems to fight this menace.

scholarly journals Nonlinear Nonconvex Optimization by Evolutionary Algorithms Applied to Robust Control

2009 ◽  
Vol 2009 ◽  
pp. 1-21 ◽  
Author(s):  
Joaquín Cervera ◽  
Alfonso Baños
Keyword(s):  
Robust Control ◽  
Evolutionary Algorithms ◽  
Optimization Problem ◽  
Main Idea ◽  
Evolutionary Process ◽  
Open Loop ◽  
Gain Function ◽  
Local Optima ◽  
Suboptimal Solution ◽  
Fixed Structure

This work focuses on the problem of automatic loop shaping in the context of robust control. More specifically in the framework given by Quantitative Feedback Theory (QFT), traditionally the search of an optimum design, a non convex and nonlinear optimization problem, is simplified by linearizing and/or convexifying the problem. In this work, the authors propose a suboptimal solution using a fixed structure in the compensator and evolutionary optimization. The main idea in relation to previous work consists of the study of the use of fractional compensators, which give singular properties to automatically shape the open loop gain function with a minimum set of parameters, which is crucial for the success of evolutionary algorithms. Additional heuristics are proposed in order to guide evolutionary process towards close to optimum solutions, focusing on local optima avoidance.

scholarly journals METHOD OF IMAGE PROCESSING IN THE PROBLEM OF DETECTING MOVING OBJECTS IN OPTICAL-ELECTRONIC SURVEILLANCE SYSTEMS OF THERMAL IMAGING TYPE

Doklady BGUIR ◽  
2020 ◽  
Vol 18 (2) ◽  
pp. 96-104
Author(s):  
E. I. Mikhnionok
Keyword(s):  
Image Processing ◽  
False Alarm ◽  
Background Subtraction ◽  
Thermal Imaging ◽  
Surveillance System ◽  
Moving Objects ◽  
Field Of View ◽  
Surveillance Systems ◽  
Electronic Surveillance ◽  
Noise Component

The article considers the method of image processing proposed by the author in relation to the problem of automatic detection of moving objects in optoelectronic thermal imaging systems. Moving objects on the observed scene are subject to investigation, so it is advisable to use algorithms based on background subtraction methods to solve the detection problem. However, the observed objects may include objects of interest (a person, a vehicle), as well as other objects and background elements that increase the noise component of the observed situation. Also, the increase in the noise component is greatly influenced by false segmentation in the foreground of the areas of processed images when transferring the field of view of the sensor of the optical-electronic surveillance system. The purpose of this article is to prove the reduction of the probability of false alarm of an automatic detector due to the author's proposed approaches to image processing. The research uses the mathematical apparatus of probability theory and simulation with subsequent statistical processing of data. The article shows that the probability of a false alarm of an automatic detector based on the background subtraction method increases significantly after the transfer of the field of view of the sensor of the optical-electronic surveillance system and decreases after the movement stops as the areas of the processed image that are falsely highlighted in the foreground are automatically segmented. The simulation showed that the approaches proposed by the author can increase the peak signal-to-noise ratio of processed images and reduce the probability of a false alarm of the automatic detector of objects of interest. The results obtained show the feasibility of adapting detection algorithms based on background subtraction methods to work in scanning optoelectronic surveillance systems.

Using a 2D Laser Range Finder for Environment Monitoring by an Autonomous Mobile Robot

2007 ◽  
Author(s):  
Claudio Marotta ◽  
Annalisa Milella ◽  
Grazia Cicirelli ◽  
Arcangelo Distante
Keyword(s):  
Mobile Robot ◽  
Main Idea ◽  
Range Data ◽  
Surveillance Systems ◽  
Local Data ◽  
Inference System ◽  
Novel Approach ◽  
Automated Surveillance ◽  
Local Range ◽  
Logic Inference

In this paper, a novel approach to automated inspection is presented, which uses a mobile robot equipped with a 2D laser rangefinder. The main idea underlying the proposed method is that of comparing current laser readings with local range data of the environment stored in a database, to look for new or removed objects. First, the robot is guided to reach goals, fixed in critical areas where inspection is required. Range data of the region surrounding each goal are automatically acquired and stored in a database. Afterwards, the robot can begin its surveillance task. Each time it reaches a goal, comparison between the current readings and the stored local data is performed using an Iterative Closest Point (ICP)-based scan-matching algorithm. Then, a fuzzy logic inference system establishes whether a significant variation of the scene has occurred and an alarm signal must be produced. Experimental results show that the proposed approach is reliable in detecting either new or missing objects and can be effectively used in automated surveillance systems in dynamic environments.

Applying multiobjective evolutionary algorithms to dynamic software product lines for reconfiguring mobile applications

2015 ◽  
Vol 103 ◽  
pp. 392-411 ◽  
Author(s):  
Gustavo G. Pascual ◽  
Roberto E. Lopez-Herrejon ◽  
Mónica Pinto ◽  
Lidia Fuentes ◽  
Alexander Egyed
Keyword(s):  
Evolutionary Algorithms ◽  
Mobile Applications ◽  
Software Product Lines ◽  
Multiobjective Evolutionary Algorithms ◽  
Product Lines ◽  
Software Product ◽  
Dynamic Software

Optimization of Anti-Spam Systems with Multiobjective Evolutionary Algorithms

2013 ◽  
Vol 26 (1) ◽  
pp. 54-67 ◽  
Author(s):  
Vitor Basto-Fernandes ◽  
Iryna Yevseyeva ◽  
José R. Méndez
Keyword(s):  
Evolutionary Algorithms ◽  
Open Source Software ◽  
Research Area ◽  
Multiobjective Evolutionary Algorithms ◽  
Spam Filtering ◽  
Nsga Ii ◽  
Software Product ◽  
Spam Filters ◽  
Problem Description ◽  
Human Effort

In this paper anti-spam filtering is presented as a cumbersome service, as opposed to a software product perspective. The huge human effort for setting up, adaptation, maintenance, and tuning of filters for spam detection in anti-spam systems is explained. Choosing the best importance scores for the spam filters is essential for the accuracy of any rules based anti-spam system, and is also one of the biggest challenges in this research area. Optimal filters score settings for Apache SpamAssassin project (the most widely adopted anti-spam open-source software) is addressed. In addition to a survey done on single/multi-objective optimization research in this area, we also present a study for filters score setting using multiobjective optimization based on two most representative evolutionary algorithms, NSGA II and SPEA2. Problem description, simulation and results analysis is done for SpamAssassin public mail corpus which is widely used for benchmarking purposes.

scholarly journals High-speed algorithm for transmitting video information about emergency situations on transport objects

2021 ◽  
pp. 64-70
Author(s):  
И.Г. Малыгин ◽  
О.А. Королев
Keyword(s):  
Real Time ◽  
High Speed ◽  
High Performance ◽  
Low Complexity ◽  
Transformation Method ◽  
Video Stream ◽  
Surveillance Systems ◽  
Video Information ◽  
Emergency Situations ◽  
Multiplication Operation

Современные интеллектуальные видеосистемы наблюдения стали все больше акцентироваться на передачу в реальном времени высококачественного видео различных важных событий, в том числе чрезвычайных ситуаций. Для высокопроизводительных систем передачи видеоинформации нового поколения необходимы эффективные структурные решения, способные как к высокой скорости передачи, так и к высокой точности вычисления. Такие структуры должны обрабатывать огромные последовательности изображений, при этом каждый видеопоток должен характеризоваться высоким разрешением с минимальным шумом и искажениями, потребляя при этом как можно меньше мощности. Спектральные алгоритмы обработки видеоинформации являются наиболее распространенным способом передачи в реальном времени, в частности дискретное косинусное преобразование. При этом исходное изображение подвергается преобразованию из пространственной в частотную область с целью сжатия путём уменьшения или устранения избыточности визуальных данных. Неявное вычисление преобразования последовательности 8-точечного массива приводит к эффективному сжатию, требующему не более пятикратного выполнения операции умножения. В статье предложены архитектура с низкой структурой сложности и метод преобразования изображений на основе алгебры целых чисел. Modern intelligent video surveillance systems have become increasingly focused on real-time transmission of high-quality video of various important events, including emergencies. For high-performance video information transmission systems of the new generation, efficient structural solutions are needed that are capable of both high transmission speed and high calculation accuracy. Such structures must process huge sequences of images, and each video stream must be characterized by high resolution and with minimal noise and distortion, while consuming as little power as possible. Spectral algorithms for processing video information are the most common method of transmission in real time, in particular the discrete cosine transform. In this case, the original image is transformed from the spatial to the frequency domain in order to compress by reducing or eliminating the redundancy of visual data. Implicitly calculating the sequence transformation of an 8-point array results in efficient compression, requiring no more than five times the multiplication operation. In this paper, we propose an architecture with a low complexity structure and image transformation method based on the algebra of integers

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