scholarly journals A new approach to robust fundamental matrix estimation using an analytic objective function and adjusted gradient projection

2019 ◽  
Author(s):  
Cuibing Du ◽  
Zongqing Lu ◽  
Jing-Hao Xue ◽  
Qingmin Liao
Keyword(s):  
Objective Function ◽  
Fundamental Matrix ◽  
Gradient Projection ◽  
New Approach ◽  
Matrix Estimation

Image Enhancement with Improved Global and Local Visual Effects

2021 ◽  
Vol 01 ◽  
Author(s):  
Muhammad Adeel ◽  
Yinglei Song
Keyword(s):  
Objective Function ◽  
Image Enhancement ◽  
Optimization Technique ◽  
Optimization Method ◽  
Original Image ◽  
Visual Effects ◽  
Swarm Optimization ◽  
New Approach ◽  
Visual Contrast ◽  
Global And Local

Background: In many applications of image processing, the enhancement of images is often a step necessary for their preprocessing. In general, for an enhanced image, the visual contrast as a whole and its refined local details are both crucial for achieving accurate results for subsequent classification or analysis. Objective: This paper proposes a new approach for image enhancement such that the global and local visual effects of an enhanced image can both be significantly improved. Methods: The approach utilizes the normalized incomplete Beta transform to map pixel intensities from an original image to its enhanced one. An objective function that consists of two parts is optimized to determine the parameters in the transform. One part of the objective function reflects the global visual effects in the enhanced image and the other one evaluates the enhanced visual effects on the most important local details in the original image. The optimization of the objective function is performed with an optimization technique based on the particle swarm optimization method. Results: Experimental results show that the approach is suitable for the automatic enhancement of images. Conclusion: The proposed approach can significantly improve both the global and visual contrasts of the image.

Solving Solid Transportation Problems With Multi-Choice Cost and Stochastic Supply and Demand

2018 ◽  
pp. 137-170 ◽  
Author(s):  
Sankar Kumar Roy ◽  
Deshabrata Roy Mahapatra
Keyword(s):  
Stochastic Programming ◽  
Objective Function ◽  
Transportation Problem ◽  
Supply And Demand ◽  
Optimal Solution ◽  
Programming Approach ◽  
Solid Transportation Problem ◽  
New Approach ◽  
Non Linear Programming ◽  
The Cost

In this chapter, the authors propose a new approach to analyze the Solid Transportation Problem (STP). This new approach considers the multi-choice programming into the cost coefficients of objective function and stochastic programming, which is incorporated in three constraints, namely sources, destinations, and capacities constraints, followed by Cauchy's distribution for solid transportation problem. The multi-choice programming and stochastic programming are combined into a solid transportation problem, and this new problem is called Multi-Choice Stochastic Solid Transportation Problem (MCSSTP). The solution concepts behind the MCSSTP are based on a new transformation technique that will select an appropriate choice from a set of multi-choice, which optimize the objective function. The stochastic constraints of STP converts into deterministic constraints by stochastic programming approach. Finally, the authors construct a non-linear programming problem for MCSSTP, and by solving it, they derive an optimal solution of the specified problem. A realistic example on STP is considered to illustrate the methodology.

Method for Fundamental Matrix Estimation Combined with Line Features

2013 ◽  
Vol 33 (10) ◽  
pp. 1015003
Author(s):  
周凡 Zhou Fan ◽  
邵世维 Shao Shiwei ◽  
吴建华 Wu Jianhua ◽  
付仲良 Fu Zhongliang
Keyword(s):  
Fundamental Matrix ◽  
Matrix Estimation ◽  
Line Features

Leader–follower-based dynamic trajectory planning for multirobot formation

Robotica ◽  
2013 ◽  
Vol 31 (8) ◽  
pp. 1351-1359 ◽  
Author(s):  
Shuang Liu ◽  
Dong Sun
Keyword(s):  
Analytical Solution ◽  
Objective Function ◽  
Collision Avoidance ◽  
Trajectory Planning ◽  
Trajectory Optimization ◽  
Optimal Trajectory ◽  
Dynamic Environment ◽  
Current Paper ◽  
New Approach ◽  
Dynamic Trajectory

SUMMARYThe present paper presents a new approach to a leader–follower-based dynamic trajectory planning for multirobot formation. A near-optimal trajectory is generated for each robot in a decentralized manner. The main contributions of the current paper are the proposal of a new objective function that considers both collision avoidance and formation requirement for the trajectory generation, and an analytical solution of trajectory parameters in the trajectory optimization. Simulations and experiments on multirobots are performed to demonstrate the effectiveness of the proposed approach to the multirobot formation in a dynamic environment.

New Approach for the Continuing Dynamic Programming

2012 ◽  
Vol 459 ◽  
pp. 575-578
Author(s):  
Peng Zhang ◽  
Xiang Huan Meng
Keyword(s):  
Dynamic Programming ◽  
Objective Function ◽  
Iteration Method ◽  
Programming Model ◽  
State Equations ◽  
New Approach ◽  
Optimal Value ◽  
Convergent Method ◽  
Optimal Values ◽  
Dynamic Programming Model

The paper proposes the discrete approximate iteration method to solve single-dimensional continuing dynamic programming model. The paper also presents a comparison of the discrete approximate iteration method and bi- convergent method to solve multi-dimensional continuing dynamic programming model. The algorithm is the following: Firstly, let state value of one of state equations be unknown and the others be known. Secondly, use discrete approximate iteration method to find the optimal value of the unknown state values, continue iterating until all state equations have found optimal values. If the objective function is convex, the algorithm is proved linear convergent. If the objective function is non-concave and non-convex, the algorithm is proved convergent.

Modeling and Simulation of Holonic Meta-Algorithm in Scheduling Process Using PERT Technique − Optimization in Job Shop Scheduling Problem

2015 ◽  
Vol 760 ◽  
pp. 199-204
Author(s):  
Mircea Gorgoi ◽  
Corneliu Neagu
Keyword(s):  
Objective Function ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
New Approach ◽  
Shop Scheduling ◽  
Technique Optimization ◽  
Optimum Solution

In generally scheduling can be viewed as optimization, bound by sequence and resource constrain and the minimization of the makespan is often used as the criterion. In this paper minimization of the makespan or complete time will be used such as an objective function and not the criterion of the decision. The new approach use heuristic elementary priority dispatch rules as the criterion of the decision. This research purpose a new methodology which use a specific elements of PERT techniques to find the optimum solution. New approach establish a solution's space where are find the all solution of the problem. Determination of the solution's space is realized by a meta-algorithm which take in account all the variant of the solutions of the process.

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