Multilevel thresholding using a modified ant lion optimizer with opposition-based learning for color image segmentation

DOI10.3934/MBE.2021155zbMath1472.94019OpenAlexW3141579742MaRDI QIDQ1984041

Wanying Zhang, Heming Jia, Kangjian Sun, Shikai Wang

Publication date: 13 September 2021

Published in: Mathematical Biosciences and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/mbe.2021155

zbMATH Keywords

image segmentationopposition-based learningmultilevel thresholdingant lion optimizerKapur entropyOtsu entropy

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (3)

An improved arithmetic optimization algorithm with forced switching mechanism for global optimization problems ⋮ An improved remora optimization algorithm with autonomous foraging mechanism for global optimization problems ⋮ Opposition-based Laplacian distribution with prairie dog optimization method for industrial engineering design problems

Cites Work

• Breast cancer mitotic cell detection using cascade convolutional neural network with U-net
• An ameliorated teaching-learning-based optimization algorithm based study of image segmentation for multilevel thresholding using Kapur's entropy and Otsu's between class variance
• Image edge detection based on singular value feature vector and gradient operator
• Modified salp swarm algorithm based multilevel thresholding for color image segmentation
• Improved graph cut model with features of superpixels and neighborhood patches for myocardium segmentation from ultrasound image
• FSIM: A Feature Similarity Index for Image Quality Assessment

This page was built for publication: Multilevel thresholding using a modified ant lion optimizer with opposition-based learning for color image segmentation