Article
Computer Science, Hardware & Architecture
Longzhen Duan, Shuqing Yang, Dongbo Zhang
Summary: An improved cuckoo search algorithm (ICS) is proposed for multilevel thresholding image segmentation in this paper, and the experimental results show that the proposed algorithm is superior to other seven well-known heuristic algorithms.
JOURNAL OF SUPERCOMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Tulika Dutta, Sandip Dey, Siddhartha Bhattacharyya, Somnath Mukhopadhyay, Prasun Chakrabarti
Summary: A Qutrit Genetic Algorithm based method for hyperspectral image segmentation is proposed, utilizing quantum logic operators and ternary chromosomes to optimize accuracy and efficiency. Experimental results and comparisons with various optimization algorithms and supervised methods demonstrate the effectiveness and advantages of the proposed approach.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Andrea H. del Rio, Itzel Aranguren, Diego Oliva, Mohamed Abd Elaziz, Erik Cuevas
Summary: The paper introduces a new method for multilevel image thresholding segmentation based on iOSA and 2D histograms, which enhances performance by introducing new optimization strategies and applying opposition-based learning, while maintaining more image information to explore the search space better.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2021)
Article
Computer Science, Information Systems
Chunzhi Wang, Chengkun Tu, Siwei Wei, Lingyu Yan, Feifei Wei
Summary: This paper proposes a multilevel thresholding image segmentation technique based on an improved whale optimization algorithm. The results of algorithm evaluation experiments demonstrate that the MSWOA has higher search accuracy and faster convergence speed. The image segmentation experimental results show that the MSWOA-Kapur technique can effectively and accurately search multilevel thresholds.
Article
Computer Science, Information Systems
A. Renugambal, K. Selva Bhuvaneswari, A. Tamilarasan
Summary: A hybrid strategy based on Sine-Cosine Crow Search Algorithm (SCCSA) is proposed in this study for efficient image segmentation. By combining Crow Search Algorithm and Sine-Cosine Algorithm, a better balance between exploration and exploitation is achieved, leading to improved search results.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Mohamed Abd Elaziz, Neggaz Nabil, Reza Moghdani, Ahmed A. Ewees, Erik Cuevas, Songfeng Lu
Summary: The study proposes an alternative multilevel thresholding image segmentation method called VPLWOA, which improves the learning phase of the VPL algorithm by using WOA as a local search system. Experimental results show that VPLWOA outperforms other methods in terms of performance measures.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Qiuping Guo, Hao Peng
Summary: In this paper, a novel and efficient color image multilevel thresholding method is proposed, which utilizes an energy function to generate an energy curve for improved segmentation performance. Experimental results demonstrate that the presented method outperforms other algorithms and that Kapur's entropy based on energy curve is superior for color image multilevel thresholding segmentation.
Article
Computer Science, Artificial Intelligence
Essam H. Houssein, Kashif Hussain, Laith Abualigah, Mohamed Abd Elaziz, Waleed Alomoush, Gaurav Dhiman, Youcef Djenouri, Erik Cuevas
Summary: The paper introduces an enhanced version of the Marine Predators Algorithm (MPA) called MPA-OBL, which incorporates Opposition-Based Learning (OBL) to improve search efficiency and convergence. Through comprehensive experiments, MPA-OBL is shown to outperform other algorithms in solving complex optimization problems, demonstrating superior quality of solutions and faster convergence speed.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Alokeparna Choudhury, Sourav Samanta, Sanjoy Pratihar, Oishila Bandyopadhyay
Summary: Microscopic image segmentation is crucial for detecting and diagnosing diseases like Alzheimer's, kidney disease, and cancer. This study introduces an enhanced firefly algorithm-based segmentation method using quantum superposition and update operations, showing effective results in segmenting hippocampus images.
APPLIED INTELLIGENCE
(2022)
Article
Computer Science, Information Systems
Yagmur Olmez, Abdulkadir Sengur, Gonca Ozmen Koca, Ravipudi Venkata Rao
Summary: This paper proposes a multilevel image thresholding approach that simplifies the thresholding problem and automatically determines the number of thresholds using a simple optimization technique instead of metaphor-based algorithms. Experimental results show that the proposed method outperforms compared methods in terms of performance and convergence.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Ling Peng, Dongbo Zhang
Summary: This paper proposes a method to obtain optimal thresholds for multilevel thresholding image segmentation using the Levy flight firefly algorithm (FAFA) by maximizing Renyi entropy, showing superior performance over five competitive algorithms in terms of objective function value, image quality measures, and computational efficiency.
JOURNAL OF SUPERCOMPUTING
(2022)
Article
Computer Science, Hardware & Architecture
Yi Wang, Shuran Song
Summary: In this paper, a novel adaptive firefly algorithm (AFA) has been proposed for multilevel thresholding image segmentation. The algorithm outperforms other five algorithms in terms of image segmentation quality, accuracy, and computation time, as indicated by the experimental results.
JOURNAL OF SUPERCOMPUTING
(2022)
Article
Computer Science, Information Systems
Ehsan Ehsaeyan
Summary: This paper proposes a novel thresholding approach that combines EM and SSA to overcome the weaknesses of the EM algorithm. It also introduces a mechanism to maintain the desired number of clusters. Experimental results show that the proposed method outperforms traditional EM algorithm and other state-of-the-art methods in terms of segmentation performance.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Taymaz Akan, Diego Oliva, Ali-Reza Feizi-Derakhshi, Amir-Reza Feizi-Derakhshi, Marco Perez-Cisneros, Mohammad Alfrad Nobel Bhuiyan
Summary: Image segmentation is a fundamental step in image processing with crucial applications in computer vision, medical imaging, and object recognition. Histogram-based thresholding is a prevalent method for image segmentation. The Battle Royal Optimizer (BRO) is a recent optimization algorithm that shows promise in multilevel image thresholding.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Physics, Multidisciplinary
Yuncong Feng, Wanru Liu, Xiaoli Zhang, Zhicheng Liu, Yunfei Liu, Guishen Wang
Summary: The paper introduces a novel interval iteration multilevel thresholding method (IIMT) for brain MR image segmentation, which decomposes and fuses the original image to achieve more refined and accurate segmentation results. Experimental results demonstrate that the proposed algorithm is effective and outperforms standard Otsu-based and other optimization-based segmentation methods.
