An adaptive density spatial clustering algorithm based on tuna swarm optimization for image segmentation

Wei Zhou; Limin Wang; Xuming Han; Yizhang Wang

doi:10.1117/12.2668042

20 April 2023 An adaptive density spatial clustering algorithm based on tuna swarm optimization for image segmentation

Wei Zhou, Limin Wang, Xuming Han, Yizhang Wang

Proceedings Volume 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022); 1260237 (2023) https://doi.org/10.1117/12.2668042
Event: International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 2022, Changchun, China

Abstract

The density-based spatial clustering of applications with noise (DBSCAN) method is exceptionally sensitive to the selection of parameters, making it difficult to obtain more accurate clustering results. To solve the above problem, we propose an adaptive TSO-DBSCAN algorithm using the excellent global search performance of the Tuna Swarm Optimization (TSO) method. We take the clustering radius parameter as the search objective of the TSO method. Then, the obtained evaluation metrics are used as the fitness function of the TSO method to adaptively search for the best parameter value and the optimal clustering result. The experimental results show that the proposed method has better clustering accuracy and effect on the processing of image segmentation.

Citation Download Citation

Wei Zhou, Limin Wang, Xuming Han, and Yizhang Wang "An adaptive density spatial clustering algorithm based on tuna swarm optimization for image segmentation", Proc. SPIE 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 1260237 (20 April 2023); https://doi.org/10.1117/12.2668042

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KEYWORDS

Image segmentation

Image processing algorithms and systems

Evolutionary algorithms

Mathematical optimization

Algorithm development

Image processing

Technology

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