Proceedings ArticleDOI
Line and circle finding by the weighted Mahalanobis distance transform and extended Kalman filtering
Sergio A. Velastin,Chengping Xu +1 more
- pp 258-263
TLDR
The Weighted Mahalanobis Distance Hough Transform (WMDHT) as discussed by the authors was proposed to improve the efficiency, accuracy and reduce the size of the accumulator arrays by combining with extended Kalman filter refinement.Abstract:
The paper presents a new parameter space approach, called the Weighted Mahalanobis Distance Hough Transform (WMDHT) whose main merit is to incorporate formal stochastic image and feature noise models. It is aimed at improving the efficiency, accuracy and reducing the size of the accumulator arrays by combining it with extended Kalman filter refinement. It works by detecting image feature points in the neighbourhood of a contour instead of exactly on the contour through a Mahalanobis distance measure modified by a weight function inversely proportional to the distance between the point and an ideal contour. The method is applicable to geometric features of any dimensionality and the paper illustrates it by considering detection of straight and circular segments. >read more
Citations
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Journal ArticleDOI
Flight formation of UAVs in presence of moving obstacles using fast-dynamic mixed integer linear programming
TL;DR: The paper presents elaborate construction of constraint equations to enforce the formation to visit pre-defined way-points and avoid the collisions with any intruder aircraft and proposes a cost function that minimizes time and energy consumption.
Journal ArticleDOI
Grey wolf optimization based sense and avoid algorithm in a Bayesian framework for multiple UAV path planning in an uncertain environment
TL;DR: A Grey Wolf Optimization (GWO) based algorithm is proposed to find the optimal UAV trajectory in presence of moving obstacles, referred to as Intruder Aircraft (IAs), with unknown trajectories, using an efficient Bayesian formalism with a notion of cell weighting based on Distance Based Value Function (DBVF).
Journal ArticleDOI
Dynamic optimal UAV trajectory planning in the National Airspace System via mixed integer linear programming
TL;DR: The paper formulates the problem of path planning using the mathematical paradigm of mixed integer linear programming and provides a solution strategy for solving this problem in the dynamic sense and presents the solution of the MILP problem.
Proceedings ArticleDOI
Grey wolf optimization based sense and avoid algorithm for UAV path planning in uncertain environment using a Bayesian framework
TL;DR: Grey Wolf Optimization (GWO) is proposed to find the optimal UAV trajectory in presence of moving obstacles, referred to as Intruder Aircrafts (IAs), with unknown trajectories, using an efficient Bayesian formalism with a notion of cell weighting based on Distance Based Value Function (DBVF).
Journal ArticleDOI
Distributed Detect-and-Avoid for Multiple Unmanned Aerial Vehicles in National Air Space
Mohammad Sarim,Mohammadreza Radmanesh,Matthew Dechering,Manish Kumar,Ravikumar V. Pragada,Kelly Cohen +5 more
TL;DR: A novel UAV traffic management (UTM) architecture that enables the integration of such UAVs in NAS is presented and a combined A*–mixed integer linear programming (MILP) and distributed detect-and-avoid (DAA) algorithm based on the concept of resource allocation using a market-based approach is presented.
References
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Journal ArticleDOI
Use of the Hough transformation to detect lines and curves in pictures
Richard O. Duda,Peter E. Hart +1 more
TL;DR: It is pointed out that the use of angle-radius rather than slope-intercept parameters simplifies the computation further, and how the method can be used for more general curve fitting.
Journal ArticleDOI
A survey of the Hough transform
John Illingworth,Josef Kittler +1 more
TL;DR: This survey will provide a useful guide to quickly acquaint researchers with the main literature in this research area and it seems likely that the Hough transform will be an increasingly used technique.
Journal ArticleDOI
The Adaptive Hough Transform
John Illingworth,Josef Kittler +1 more
TL;DR: This correspondence illustrates the ideas of the Adaptive Hough Transform, AHT, by tackling the problem of identifying linear and circular segments in images by searching for clusters of evidence in 2-D parameter spaces and shows that the method is robust to the addition of extraneous noise.
Journal ArticleDOI
Comparative study of Hough transform methods for circle finding
TL;DR: A variety of circle detection methods which are based on variations of the Hough Transform are investigated, and the accuracy, reliability, computational efficiency and storage requirements of each of the methods are presented.
Journal ArticleDOI
Which Hough transform
TL;DR: An update on state of the art Hough techniques is offered, which includes comparative studies of existing techniques, new perspectives on the theory, very many novel algorithms, parallel implementations, and additions to the task-specific hardware.