scholarly journals Natural Image Enhancement Using a Biogeography Based Optimization Enhanced with Blended Migration Operator

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
J. Jasper ◽  
S. Berlin Shaheema ◽  
S. Berlin Shiny
Keyword(s):  
Image Processing ◽  
Image Enhancement ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Objective Evaluation ◽  
Natural Image ◽  
Edge Information ◽  
Migration Operator ◽  
Current State ◽  
Complex Optimization

This paper addresses a novel and efficient algorithm for solving optimization problem in image processing applications. Image enhancement (IE) is one of the complex optimization problems in image processing. The main goal of this paper is to enhance color images such that the eminence of the image is more suitable than the original image from the perceptual viewpoint of human. Traditional methods require prior knowledge of the image to be enhanced, whereas the aim of the proposed biogeography based optimization (BBO) enhanced with blended migration operator (BMO) algorithm is to maximize the objective function in order to enhance the image contrast by maximizing the parameters like edge intensity, edge information, and entropy. Experimental results are compared with the current state-of-the-art approaches and indicate the superiority of the proposed technique in terms of subjective and objective evaluation.

scholarly journals A new conjugate gradient method based on a modified secant condition with its applications in image processing

2020 ◽  
Author(s):  
Fahimeh Abdollahi ◽  
M. Fatemi
Keyword(s):  
Image Processing ◽  
Conjugate Gradient Method ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Secant Condition ◽  
Gradient Parameter ◽  
Function Information ◽  
Modified Secant Condition

We propose an effective conjugate gradient method belonging to the class of Dai-Liao methods for solving unconstrained optimization problems. We employ a variant of the modified secant condition, and introduce a new conjugate gradient parameter by solving an optimization problem. Optimization problem combines the well-known features of the linear conjugate gradient method using some penalty functions. This new parameter takes advantage of function information as well as the gradient information to provide the iterations. Our proposed method is globally convergent under mild assumptions. We examine the ability of the method for solving some real world problems from image processing field. Numerical results show that the proposed method is efficient in the sense of PSNR test. We also compare our proposed method with some well-known existing algorithms using a collection of CUTEr problems to show it's efficiency.

An Embedded Multi-Phase Tactic of Scheduling Autoimmunization for Complex Correlated Production System

2010 ◽  
Vol 439-440 ◽  
pp. 505-509 ◽  
Author(s):  
Ya Bo Luo ◽  
Ming Chun Tang
Keyword(s):  
Optimization Problem ◽  
Job Shop ◽  
Optimization Problems ◽  
Scheduling System ◽  
Design Variables ◽  
Complex Optimization ◽  
Feasible Solutions ◽  
Optimum Solution ◽  
Multi Phase ◽  
Machine Allocation

The schedule for job shop system involving the complex correlated constraints is a complex combinatorial optimization problem, for which currently there is no a methodology claiming to have capability to find the optimum solution. Current research concentrate on the search of acceptable feasible solutions. This research proposes an embedded multi-phase methodology to find the acceptable feasible solutions in a higher efficiency. The thinking of the methodology is to decompose the complex optimization problem into two sub problems of the operation sequence and the machine allocation to lower the complexity of the scheduling system and improve the searching efficiency. The two sub problems are solved orderly respectively, and the results of the first sub problem are embedded into the second sub problem as the original values of design variables. Thus these two sub optimization problems are integrated into a searching loop to ensure the feasibility of solution and improve the searching efficiency in the complex correlated system.

scholarly journals Application of Genetic Algorithm in Common Optimization Problems

2019 ◽  
Vol 8 (1) ◽  
pp. 17-21
Author(s):  
Nika Topuria ◽  
Omar Kikvidze
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Local Optima ◽  
Deterministic Algorithms ◽  
Complex Optimization ◽  
Short Time ◽  
Fitness Parameter

Use of non-deterministic algorithms for solving multi-variable optimization problems is widely used nowadays. Genetic Algorithm belongs to a group of stochastic biomimicry algorithms, it allows us to achieve optimal or near-optimal results in large optimization problems in exceptionally short time (compared to standard optimization methods). Major advantage of Genetic Algorithm is the ability to fuse genes, to mutate and do selection based on fitness parameter. These methods protect us from being trapped in local optima (Most of deterministic algorithms are prone to getting stuck on local optima). In this paper we experimentally show the upper hand of Genetic Algorithms compared to other traditional optimization methods by solving complex optimization problem.

scholarly journals Physics-Inspired Optimization Algorithms: A Survey

2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
Anupam Biswas ◽  
K. K. Mishra ◽  
Shailesh Tiwari ◽  
A. K. Misra
Keyword(s):  
Comparative Studies ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Optimization Algorithms ◽  
Natural Phenomenon ◽  
Complex Optimization ◽  
Evolution With Time

Natural phenomenon can be used to solve complex optimization problems with its excellent facts, functions, and phenomenon. In this paper, a survey on physics-based algorithm is done to show how these inspirations led to the solution of well-known optimization problem. The survey is focused on inspirations that are originated from physics, their formulation into solutions, and their evolution with time. Comparative studies of these noble algorithms along with their variety of applications have been done throughout this paper.

scholarly journals A Comparative Study of Swarm Intelligence Algorithms for UCAV Path-Planning Problems

Mathematics ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 171
Author(s):  
Haoran Zhu ◽  
Yunhe Wang ◽  
Zhiqiang Ma ◽  
Xiangtao Li
Keyword(s):  
Path Planning ◽  
Swarm Intelligence ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Planning Problem ◽  
Complex Optimization ◽  
Battlefield Environment ◽  
Planning Problems ◽  
Path Planning Problem ◽  
Open Issues

Path-planning for uninhabited combat air vehicles (UCAV) is a typically complicated global optimization problem. It seeks a superior flight path in a complex battlefield environment, taking into various constraints. Many swarm intelligence (SI) algorithms have recently gained remarkable attention due to their capability to address complex optimization problems. However, different SI algorithms present various performances for UCAV path-planning since each algorithm has its own strengths and weaknesses. Therefore, this study provides an overview of different SI algorithms for UCAV path-planning research. In the experiment, twelve algorithms that published in major journals and conference proceedings are surveyed and then applied to UCAV path-planning. Moreover, to demonstrate the performance of different algorithms in further, we design different scales of problem cases for those comparative algorithms. The experimental results show that UCAV can find the safe path to avoid the threats efficiently based on most SI algorithms. In particular, the Spider Monkey Optimization is more effective and robust than other algorithms in handling the UCAV path-planning problem. The analysis from different perspectives contributes to highlight trends and open issues in the field of UCAVs.

A Methodology for Missile Countermeasures Optimization under Uncertainty

2002 ◽  
Vol 10 (2) ◽  
pp. 129-149 ◽  
Author(s):  
Frank W. Moore
Keyword(s):  
Genetic Programming ◽  
Optimization Problem ◽  
Autonomous Agents ◽  
Optimization Problems ◽  
Optimization Under Uncertainty ◽  
Programming System ◽  
Current State ◽  
Aircraft Survivability ◽  
Specific Sequences

The missile countermeasures optimization problem is a complex strategy optimization problem that combines aircraft maneuvers with additional countermeasures in an attempt to survive attack from a single surface-launched, anti-aircraft missile. Classic solutions require the evading aircraft to execute specific sequences of maneuvers at precise distances from the pursuing missile and do not effectively account for uncertainty about the type and/or current state of the missile. This paper defines a new methodology for solving the missile countermeasures optimization problem under conditions of uncertainty. The resulting genetic programming system evolves programs that combine maneuvers with such countermeasures as chaff, flares, and jamming to optimize aircraft survivability. This methodology may be generalized to solve strategy optimization problems for intelligent, autonomous agents operating under conditions of uncertainty.

Implications of Digital Image Processing in the Paraclinical Assessment of the Partially Edentated Patient

2018 ◽  
Vol 69 (2) ◽  
pp. 521-524
Author(s):  
Magda Ecaterina Antohe ◽  
Doriana Agop Forna ◽  
Cristina Gena Dascalu ◽  
Norina Consuela Forna
Keyword(s):  
Image Processing ◽  
Image Enhancement ◽  
Treatment Plan ◽  
Digital Processing ◽  
Contour Detection ◽  
Anatomical Structures ◽  
Imaging Processing ◽  
Point To Point ◽  
Radiological Image ◽  
Processing Techniques

The application of certain digital processing techniques offers the possibility of extra accuracy in the interpretation of paraclinical examinations of this type, with profound implications in the diagnosis as well as in the hierarchy of the treatment plan. The purpose of this study is to identify the type of imaging processing for the identification of pathological elements from orthopantomographies and articular tomographies. A number of 20 orthopantomographies and 15 temporo-mandibular joint tomography have undergone through various image enhancement techniques. Various methods of image enhancement (enhancement) have been used for those procedures whereby it becomes more useful in the following aspects: specific details are highlighted; noise is eliminated; the image becomes more visually attractive. The workings were done in Corel PhotoPaint 7.0, using the automatic procedures available.The choice of a particular type of image enhancement technique has been selected for each type of pathology found in orthopantomographies or articular tomography, providing the best accuracy for an optimal imaging interpretation that underpins a precision diagnosis.Of the most useful imaging processing in the optimization of the orthopantomographic image accuracy the point-to-point transformations are to be noted. The image processing proposed in this article focused primarily on improving the radiological image attributes to highlight specific anatomical structures, and secondly, the contour detection, where it was necessary for the diagnostic purposes as well.

Software suite for determining the tilts of tower-type structures according to terrestrial laser scanning

2020 ◽  
Vol 961 (7) ◽  
pp. 2-7
Author(s):  
A.V. Zubov ◽  
N.N. Eliseeva
Keyword(s):  
Laser Scanning ◽  
Optimization Problems ◽  
Optimization Methods ◽  
User Participation ◽  
Software Suite ◽  
Current State ◽  
Visual Basic For Applications ◽  
Operational Data ◽  
Theoretical Developments

The authors describe a software suite for determining tilt degrees of tower-type structures according to ground laser scanning indication. Defining the tilt of the pipe is carried out with a set of measured data through approximating the sections by circumferences. They are constructed using one of the simplest search engine optimization methods (evolutionary algorithm). Automatic filtering the scan of the current section from distorting data is performed by the method of assessing the quality of models constructed with that of least squares. The software was designed using Visual Basic for Applications. It contains several blocks (subprograms), with each of them performing a specific task. The developed complex enables obtaining operational data on the current state of the object with minimal user participation in the calculation process. The software suite is the result of practical implementing theoretical developments on the possibilities of using search methods at solving optimization problems in geodetic practice.

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