Hybrid improved capuchin search algorithm for plant image thresholding

Shujing Li; Zhangfei Li; Qinghe Li; Mingyu Zhang; Linguo Li

doi:10.3389/fpls.2023.1122788

Hybrid improved capuchin search algorithm for plant image thresholding

Front Plant Sci. 2023 Jan 26:14:1122788. doi: 10.3389/fpls.2023.1122788. eCollection 2023.

Authors

Shujing Li¹, Zhangfei Li¹, Qinghe Li¹, Mingyu Zhang¹, Linguo Li^{1

2}

Affiliations

¹ School of Computer and Information Engineering, Fuyang Normal University, Fuyang, China.
² School of Computer, Nanjing University of Posts and Telecommunications, Nanjing, China.

Abstract

With the development and wider application of meta-heuristic optimization algorithms, researchers increasingly apply them to threshold optimization of multi-level image segmentation. This paper explores the performance and effects of Capuchin Search Algorithm (CAPSA) in threshold optimization. To solve problems of uneven distribution in the initial population of Capuchin Search Algorithm, low levels of global search performance and premature falling into local optima, this paper proposes an improved Capuchin Search Algorithm (ICAPSA) through a multi-strategy approach. ICAPSA uses chaotic opposite-based learning strategy to initialize the positions of individual capuchins, and improve the quality of the initial population. In the iterative position updating process, Levy Flight disturbance strategy is introduced to balance the global optimization and local exploitation of the algorithm. Finally, taking Kapur as the objective function, this paper applies ICAPSA to multi-level thresholding in the plant images, and compares its segmentation effects with the original CAPSA, the Fuzzy Artificial Bee Colony algorithm (FABC), the Differential Coyote Optimization Algorithm (DCOA), the Modified Whale Optimization Algorithm (MWOA) and Improved Satin Bowerbird Optimization Algorithm (ISBO). Through comparison, it is found that ICAPSA demonstrates superior segmentation effect, both in the visual effects of image segmentation and in data comparison.

Keywords: capuchin search algorithm; chaotic mapping; levy flight; opposite-based learning; plant image thresholding.

Grants and funding

This paper is supported by the National Youth Natural Science Foundation of China under Grant 61802208, the Natural Science Foundation of Anhui under Grant 1908085MF207, KJ2020A1215, KJ2020A1216 and KJ2021A1251, the Excellent Youth Talent Support Foundation of Anhui under Grant gxyqZD2019097 and gxyqZD2021142, the Postdoctoral Foundation of Jiangsu under Grant 2018K009B, the Foundation of Fuyang Normal University under Grant TDJC2021008 and the Quality Engineering Project of Anhui under Grant 2021jyxm1117, 2021kcszsfkc307 and 2019sjjd81.