{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T00:07:04Z","timestamp":1772928424178,"version":"3.50.1"},"reference-count":20,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2020,4,2]],"date-time":"2020-04-02T00:00:00Z","timestamp":1585785600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>In this article, we present a new algorithm called Particle Swarm Contour Search (PSCS)\u2014a 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.<\/jats:p>","DOI":"10.3390\/e22040407","type":"journal-article","created":{"date-parts":[[2020,4,2]],"date-time":"2020-04-02T11:57:14Z","timestamp":1585828634000},"page":"407","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Particle Swarm Contour Search Algorithm"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1643-6680","authenticated-orcid":false,"given":"Dominik","family":"Weikert","sequence":"first","affiliation":[{"name":"Faculty of Computer Science, Otto-von-Guericke University Magdeburg, 39106 Magdeburg, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2255-3277","authenticated-orcid":false,"given":"Sebastian","family":"Mai","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, Otto-von-Guericke University Magdeburg, 39106 Magdeburg, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9917-5227","authenticated-orcid":false,"given":"Sanaz","family":"Mostaghim","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, Otto-von-Guericke University Magdeburg, 39106 Magdeburg, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1109\/TPAMI.1986.4767851","article-title":"A Computational Approach to Edge Detection","volume":"PAMI-8","author":"Canny","year":"1986","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1007\/BF00133570","article-title":"Snakes: Active contour models","volume":"1","author":"Kass","year":"1988","journal-title":"Int. J. Comput. Vis."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Seo, J., Chae, S., Shim, J., Kim, D., Cheong, C., and Han, T.D. (2016). Fast Contour-Tracing Algorithm Based on a Pixel-Following Method for Image Sensors. Sensors, 16.","DOI":"10.3390\/s16030353"},{"key":"ref_4","unstructured":"Kennedy, J., and Eberhart, R. (December, January 27). Particle swarm optimization (PSO). Proceedings of the IEEE International Conference on Neural Networks, Perth, Australia."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Li, X. (2004). Adaptively choosing neighbourhood bests using species in a particle swarm optimizer for multimodal function optimization. Genetic and Evolutionary Computation Conference, Springer.","DOI":"10.1007\/978-3-540-24854-5_10"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Zambrano-Bigiarini, M., Clerc, M., and Rojas, R. (2013, January 20\u201323). Standard particle swarm optimisation 2011 at cec-2013: A baseline for future pso improvements. Proceedings of the 2013 IEEE Congress on Evolutionary Computation, Cancun, Mexico.","DOI":"10.1109\/CEC.2013.6557848"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1109\/TSMCC.2010.2054080","article-title":"Particle swarm optimization in wireless-sensor networks: A brief survey","volume":"41","author":"Kulkarni","year":"2010","journal-title":"IEEE Trans. Syst. Man, Cybern. Part (Appl. Rev.)"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Mostaghim, S., Steup, C., and Witt, F. (2016, January 6\u20139). Energy aware particle swarm optimization as search mechanism for aerial micro-robots. Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence (SSCI), Athens, Greece.","DOI":"10.1109\/SSCI.2016.7850263"},{"key":"ref_9","first-page":"1","article-title":"Analysis of the Publications on the Applications of Particle Swarm Optimisation","volume":"2008","author":"Poli","year":"2008","journal-title":"J. Artif. Evol. Appl."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Canny, J. (1987). A computational approach to edge detection. Readings in Computer Vision, Elsevier.","DOI":"10.1016\/B978-0-08-051581-6.50024-6"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1027","DOI":"10.1109\/TPAMI.2003.1217608","article-title":"A method for objective edge detection evaluation and detector parameter selection","volume":"25","author":"Yitzhaky","year":"2003","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1109\/34.56205","article-title":"Scale-space and edge detection using anisotropic diffusion","volume":"12","author":"Perona","year":"1990","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Duda, R.O., and Munson, J.H. (1967). Graphical-Data-Processing Research Study and Experimental Investigation, Stanford Research Institute. Technical Report.","DOI":"10.21236\/AD0657670"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/0734-189X(85)90016-7","article-title":"Topological structural analysis of digitized binary images by border following","volume":"30","author":"Suzuki","year":"1985","journal-title":"Comput. Vision Graph. Image Process."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Dorigo, M., Birattari, M., Blum, C., Christensen, A.L., Reina, A., and Trianni, V. (2018). The Importance of Component-Wise Stochasticity in Particle Swarm Optimization. Swarm Intelligence, Springer International Publishing.","DOI":"10.1007\/978-3-030-00533-7"},{"key":"ref_16","unstructured":"Yang, S., Wang, M., and Jiao, L. (2004, January 19\u201323). A quantum particle swarm optimization. Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004, Portland, OR, USA."},{"key":"ref_17","unstructured":"Blackwell, T.M., and Bentley, P.J. Dynamic search with charged swarms. Proceedings of the 4th Annual Conference on Genetic and Evolutionary Computation."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Blackwell, T., and Branke, J. (2004). Multi-swarm optimization in dynamic environments. Workshops on Applications of Evolutionary Computation, Springer.","DOI":"10.1007\/978-3-540-24653-4_50"},{"key":"ref_19","unstructured":"Bradski, G. (2020, March 16). The OpenCV Library. Available online: https:\/\/www.drdobbs.com\/open-source\/the-opencv-library\/184404319."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1109\/TEVC.2003.810758","article-title":"Performance assessment of multiobjective optimizers: An analysis and review","volume":"7","author":"Zitzler","year":"2003","journal-title":"IEEE Trans. Evol. 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