Article
Computer Science, Information Systems
Dongmei Wu, Chengzhi Yuan
Summary: Threshold segmentation based on swarm intelligence optimization algorithm is proposed in this paper, with improved sparrow search algorithm and 2-D maximum entropy method. Experimental results show the superiority of the proposed method in terms of segmentation effect.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Feng Zhao, Lulu Cao, Hanqiang Liu, Zihan Tang, Jiulun Fan
Summary: The rough clustering algorithm optimizes nonlocal spatial information to improve noise robustness, simultaneously optimizing cluster centers to adapt to different segmentation requirements. It introduces an adaptive threshold determination mechanism to enhance the accuracy of rough cluster upper and lower approximations.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Computer Science, Information Systems
Linguo Li, Lijuan Sun, Yu Xue, Shujing Li, Xuwen Huang, Romany Fouad Mansour
Summary: This article combines COA with fuzzy median aggregation to form FCOA and FICOA, achieving better image segmentation results and outperforming other algorithms. By improving the COA algorithm, the quality of image segmentation is enhanced.
Article
Computer Science, Artificial Intelligence
Reza Vafashoar, Hossein Morshedlou, Mohammad Reza Meybodi
Summary: The paper improves particle swarm optimizer by adjusting the neighborhood structures of particles, dividing the search task between even and uneven particles for deep search, and utilizing a tree structure for neighborhood implementation. Experimental results show significant improvement in particle swarm optimization and successful application in solving challenging real-world problems.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Dong Zhao, Lei Liu, Fanhua Yu, Ali Asghar Heidari, Mingjing Wang, Guoxi Liang, Khan Muhammad, Huiling Chen
Summary: By enhancing the selection mechanism of the ACOR method and introducing random spare strategy and chaotic intensification strategy, the convergence speed and accuracy can be significantly improved, effectively avoiding local optima. Through a series of experiments, these improved methods demonstrate superior performance in problem-solving, and compared to other techniques, RCACO has a more reliable ability to step out of local optima.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Hanuman Verma, Deepa Verma, Pawan Kumar Tiwari
Summary: The hybrid FCM-PSO algorithm combines the advantages of FCM and PSO algorithms, demonstrating better clustering performance in handling complex problems. Experimental results show the effectiveness of the algorithm through numerical and visual comparisons, as well as statistical tests.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Chemistry, Multidisciplinary
Jianfeng Zheng, Yinchong Gao, Han Zhang, Yu Lei, Ji Zhang
Summary: This paper proposes an improved particle swarm optimization algorithm for OTSU multi-threshold image segmentation. The method reduces the particle search range by calculating the particle contribution degree and balances global and local search using asynchronous monotone increasing social learning factor and asynchronous monotone decreasing individual learning factor. Experimental results demonstrate the robustness and superiority of the algorithm, achieving higher segmentation accuracy and efficiency.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Artificial Intelligence
Swarnajit Ray, Arunita Das, Krishna Gopal Dhal, Jorge Galvez, Prabir Kumar Naskar
Summary: This study introduces a multi-level hematology color image thresholding method based on the Eagle Strategy coupled with Whale Optimization Algorithm (ES-WOA), analyzing its performance over five well-known objective functions. The proposed ES-WOA with Tsallis' entropy outperforms other algorithms in terms of computational effort, image segmentation quality, and robustness.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Mathematical & Computational Biology
Xiuzhi Zhao, Lei Liu, Ali Asghar Heidari, Yi Chen, Benedict Jun Ma, Huiling Chen, Shichao Quan
Summary: The novel coronavirus pneumonia (COVID-19) is a respiratory disease that requires effective diagnostic methods such as X-ray imaging-based diagnosis. This paper proposes an enhanced version of ant colony optimization for continuous domains (MGACO) for highly effective pre-processing of COVID-19 pathological images. Additionally, a method called MGACO-MIS based on MGACO is developed, which demonstrates strong adaptability and high-quality segmentation results compared to other methods.
FRONTIERS IN NEUROINFORMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Rupak Chakraborty, Garima Verma, Suyel Namasudra
Summary: This article introduces an improved Fractional Order Darwinian PSO (IFODPSO) algorithm for color image segmentation, which reduces the dependence on fractional coefficient by incorporating the delta potential model of quantum mechanics. The algorithm achieves better segmentation accuracy by utilizing Multi-level Massi Entropy as the objective function.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2021)
Article
Computer Science, Interdisciplinary Applications
Yunlou Qian, Jiaqing Tu, Gang Luo, Ce Sha, Ali Asghar Heidari, Huiling Chen
Summary: This paper investigates the application of remote sensing images in urban surface morphology and geographic conditions, using the multi-threshold image segmentation method for image segmentation research. The performance of the original algorithm is enhanced by introducing salp foraging behavior. The experimental results demonstrate the advantages of SSACO in remote sensing image segmentation.
JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING
(2023)
Article
Computer Science, Information Systems
Manoj Kumar Naik, Rutuparna Panda, Aneesh Wunnava, Bibekananda Jena, Ajith Abraham
Summary: Multilevel image thresholding is essential in multimedia tools to understand objects in the real world, but the 1-D Masi entropy-based thresholding lacks consideration of contextual information. To address this, a 2-D Masi entropy-based thresholding method utilizing a 2-D histogram was proposed. The computational complexity was reduced by using a nature-inspired optimizer, the leader Harris hawks optimization (LHHO), which improved performance compared to the Harris hawks optimization (HHO).
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Yi Chen, Mingjing Wang, Ali Asghar Heidari, Beibei Shi, Zhongyi Hu, Qian Zhang, Huiling Chen, Majdi Mafarja, Hamza Turabieh
Summary: In this study, a multi-strategy-driven shuffled frog leaping algorithm with horizontal and vertical crossover search (HVSFLA) is proposed for medical image segmentation. The algorithm achieves a better balance between diversification and intensification through horizontal and vertical crossover search. Experimental results demonstrate that HVSFLA outperforms other competing algorithms, showing great potential for medical image segmentation.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Biology
Songwei Zhao, Pengjun Wang, Ali Asghar Heidari, Huiling Chen, Wenming He, Suling Xu
Summary: This paper presents a novel approach to improve the Salp Swarm Algorithm (SSA), named EHSSA, which is applied to Multi-threshold image segmentation (MIS). By enhancing the global search capability of the algorithm, it successfully avoids local optimal drawbacks and proves its effectiveness and performance through experiments.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Computer Science, Artificial Intelligence
Xue Fu, Liangkuan Zhu, Bowen Wu, Jingyu Wang, Xiaohan Zhao, Arystan Ryspayev
Summary: This paper proposes an efficient multilevel thresholding segmentation method based on improved Chimp Optimization Algorithm (IChOA) to improve traditional image segmentation. Kapur entropy is used as the objective function to find the best threshold values for RGB images. Several strategies are introduced including population initialization strategy combining with Gaussian chaos and opposition-based learning, the position update mechanism of particle swarm algorithm (PSO), the Gaussian-Cauchy mutation, and the adaptive nonlinear strategy. These methods enhance the diversity of the population and improve the exploration and exploitation capabilities of IChOA. Furthermore, the search ability, accuracy, and stability of IChOA are significantly enhanced.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2023)
