Particle Swarm Contour Search Algorithm.

Dominik Weikert,Sebastian Mai,Sanaz Mostaghim

doi:10.3390/e22040407

Dominik Weikert, Sebastian Mai + Show 1 more

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https://doi.org/10.3390/e22040407

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Abstract

In this article, we present a new algorithm called Particle Swarm Contour Search (PSCS)—a Particle Swarm Optimisation inspired algorithm to find object contours in 2D environments. Currently, most contour-finding algorithms are based on image processing and require a complete overview of the search space in which the contour is to be found. However, for real-world applications this would require a complete knowledge about the search space, which may not be always feasible or possible. The proposed algorithm removes this requirement and is only based on the local information of the particles to accurately identify a contour. Particles search for the contour of an object and then traverse alongside using their known information about positions in- and out-side of the object. Our experiments show that the proposed PSCS algorithm can deliver comparable results as the state-of-the-art.

Highlights

Finding the contour of an object, known as contour search, has a large variety of applications.Beside the conventional applications in image processing, there are other applications in robotics.Imagine a scenario of identifying the contour of wildfire or oil spill on the ocean
Our modified the Inverted Generational Distance (IGD) indicator calculates the average of the distances between reference solutions pre f and the closest solution p A stored in the archive A: IGD =
|re f | ∀ p ∑∈re f pa re f where re f is the set of reference points which are located on the contour and are computed using the state-of-the-art approach from the image processing literature [19]

Summary

Introduction

Finding the contour of an object, known as contour search, has a large variety of applications.Beside the conventional applications in image processing, there are other applications in robotics.Imagine a scenario of identifying the contour of wildfire or oil spill on the ocean. Finding the contour of an object, known as contour search, has a large variety of applications. Beside the conventional applications in image processing, there are other applications in robotics. Imagine a scenario of identifying the contour of wildfire or oil spill on the ocean. The major challenges concern searching for an object and identifying the corresponding contour. The existing algorithms typically rely on image processing technologies [1,2,3], which typically require knowledge about the entire search space. We aim to unify both of the search processes for the object and the contour identification in one algorithm. Since we work on PSO for search, this algorithm can be applied to real-world applications such as in collective robotic search scenarios for the detection of wildfires and oil spills. We aim to provide the algorithmic background for contour search

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