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粒子群轮廓搜索算法

Particle Swarm Contour Search Algorithm.

作者信息

Weikert Dominik, Mai Sebastian, Mostaghim Sanaz

机构信息

Faculty of Computer Science, Otto-von-Guericke University Magdeburg, 39106 Magdeburg, Germany.

出版信息

Entropy (Basel). 2020 Apr 2;22(4):407. doi: 10.3390/e22040407.

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.

摘要

在本文中,我们提出了一种名为粒子群轮廓搜索(PSCS)的新算法——一种受粒子群优化启发的算法,用于在二维环境中找到物体轮廓。目前,大多数轮廓查找算法基于图像处理,并且需要对要找到轮廓的搜索空间有完整的概述。然而,对于实际应用来说,这将需要关于搜索空间的完整知识,而这可能并非总是可行或可能的。所提出的算法消除了这一要求,并且仅基于粒子的局部信息来准确识别轮廓。粒子搜索物体的轮廓,然后利用它们关于物体内外位置的已知信息沿着轮廓遍历。我们的实验表明,所提出的PSCS算法能够产生与当前最先进算法相当的结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f57a/7516883/0cbca47c5000/entropy-22-00407-g001.jpg

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