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
Engineering, Multidisciplinary
R. Srikanth, K. Bikshalu
Summary: Image segmentation is the process of dividing an image into regions, with multilevel thresholding being a mature method and Otsu's method being a significant technique. Traditional histogram-based methods lack spatial details of contextual information, leading to the proposal of a novel method using Energy Curve instead.
AIN SHAMS ENGINEERING JOURNAL
(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
Engineering, Biomedical
J. Ramya, H. C. Vijaylakshmi, Huda Mirza Saifuddin
Summary: The proposed method in this paper utilizes discrete wavelet transform for skin lesion segmentation, effectively addressing the complexities in dermoscopic images. By analyzing color components and using thresholding techniques, the method separates skin lesion region from background with promising results. Experimental comparisons with state-of-the-art methods demonstrate the effectiveness and superiority of the proposed method.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2021)
Article
Computer Science, Information Systems
Taymaz Rahkar Farshi, Ahad K. Ardabili
Summary: This study explores optimizing image segmentation with a hybrid optimization algorithm and applying it to multilevel image thresholding. The experiments show that the proposed method outperforms other optimization algorithms in various metrics.
MULTIMEDIA SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Mohammad Hashem Ryalat, Osama Dorgham, Sara Tedmori, Zainab Al-Rahamneh, Nijad Al-Najdawi, Seyedali Mirjalili
Summary: Digital image processing techniques and algorithms are used to support medical experts in disease identification, studies, and diagnosis. Image segmentation methods are widely used in this area to simplify image representation and analysis. Among various approaches, multilevel thresholding methods have shown better results. However, traditional statistical approaches like the Otsu and Kapur methods suffer from high computational costs for multilevel thresholding. In this work, the Harris hawks optimization technique is combined with Otsu's method to reduce computational costs while maintaining optimal outcomes.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Medicine, General & Internal
Seena Joseph, Oludayo O. Olugbara
Summary: Despite advances in immune therapies, melanoma remains difficult to treat. This study aims to investigate the effects of image preprocessing on the performance of a saliency segmentation method for skin lesions. The results show that preprocessing can be eliminated in the segmentation of skin lesions in dermoscopic images, and the applied segmentation method is competitive with leading supervised and unsupervised segmentation methods.
Article
Computer Science, Artificial Intelligence
Essam H. Houssein, Bahaa El-din Helmy, Diego Oliva, Ahmed A. Elngar, Hassan Shaban
Summary: This paper introduces the use of the Black Widow Optimization (BWO) algorithm to find the best threshold configuration for multi-level image segmentation, achieving higher efficiency and reliability compared to other meta-heuristic algorithms. Experimental results demonstrate the superior performance of the BWO-based method, showing potential applications in the field of image processing.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Mathematical & Computational Biology
Shikai Wang, Kangjian Sun, Wanying Zhang, Heming Jia
Summary: The paper proposes a modified ant lion optimizer algorithm based on opposition-based learning for optimizing multilevel thresholding in image segmentation, and experimental results show that the method outperforms others in terms of segmentation performance.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Simrandeep Singh, Nitin Mittal, Harbinder Singh
Summary: This paper introduces a new hybrid Dragonfly algorithm and Firefly Algorithm for image segmentation, showing that the proposed method outperforms other optimization algorithms such as MTEMO, GA, PSO, and BF in terms of performance metrics.
Article
Automation & Control Systems
Ashish Kumar Bhandari, Anurag Singh, Immadisetty Vinod Kumar
Summary: This study proposes a context-based 3-D Otsu algorithm that takes into account pixel intensity values and spatial information, showing significant advantages in performance metrics compared to histogram-based methods. Experimental results demonstrate its effectiveness in producing more promising segmentation results from both objective and subjective observations.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Computer Science, Information Systems
Simrandeep Singh, Nitin Mittal, Harbinder Singh, Diego Oliva
Summary: Image segmentation is a critical stage in image analysis and pre-processing, where pixels are divided into segments based on threshold values. Multi-level thresholding approaches are more effective than bi-level methods, and a new modified Otsu function is proposed that combines Otsu's between-class variance and Kapur's entropy. Experimental results demonstrate the high efficiency of the modified Otsu method in terms of performance metrics.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Ashish Kumar Bhandari, Neha Singh, Anurag Singh
Summary: This paper presents a method that combines two newly proposed evolutionary computational algorithms (ECAs) with the Otsu thresholding method to achieve brightness preserving image contrast enhancement. The method utilizes an improved histogram equalization technique and optimized constraint parameters to achieve balanced contrast enhancement and better color preservation.
NEURAL COMPUTING & APPLICATIONS
(2022)
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
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)