您当前的位置：
首页 >
文章列表页 >
Sand microscopic image segmentation with enhanced tuna swarm optimization exponential entropy
Information Sciences | 更新时间：2024-05-08
|

    • Sand microscopic image segmentation with enhanced tuna swarm optimization exponential entropy

    • “地质评估领域迎来了一项重要突破。针对砂粒显微图像分割这一难题，研究者提出了一种增强型金枪鱼群优化指数熵的分割方法（ETSO-EXP）。该方法能够有效保留各类砂粒的纹理特征，为地质评估提供了更为准确的图像分割手段。研究者首先针对金枪鱼群优化算法（TSO）的不足，提出了混沌扰动策略、动态权重策略和余弦干扰策略进行增强。实验表明，这些改进使得ETSO在收敛精度和速度上都有了显著提升。随后，研究者将ETSO应用于确定EXP的分割阈值，并通过信息量标准验证了该方案的可行性。在雅鲁藏布江砂粒显微图像数据集上的实验结果显示，与TSO-EXP相比，ETSO-EXP在峰值信噪比、结构相似性、特征相似度和寻优速度等方面均取得了显著的提升。这一研究成果不仅展示了ETSO-EXP在砂粒显微图像分割中的优越性能，还为地质评估领域提供了新的解决方案。该方法对于处理对比度较高、纹理丰富或砂粒碎屑尺寸差异较大的图像具有较高的分割精度和计算速度，为地质评估提供了有力的技术支持。”
      ”
    • Optics and Precision Engineering   Vol. 32, Issue 8, Pages: 1199-1211(2024)

    • DOI：10.37188/OPE.20243208.1199    

      CLC： TP399

    • Published：25 April 2024，

      Received：21 June 2023，

      Revised：22 August 2023，

    扫 描 看 全 文

  • WANG Mengfei,WANG Weixing,XU Kun,et al.Sand microscopic image segmentation with enhanced tuna swarm optimization exponential entropy[J].Optics and Precision Engineering,2024,32(08):1199-1211. DOI： 10.37188/OPE.20243208.1199.

  •  
  •  

0

Views

23

下载量

0

CSCD

Alert me when the article has been cited
提交
Tools
Download
Export Citation
Share
Add to favorites
Add to my album

Related Articles

Brain tumor image segmentation based on Semantic Flow Guided Sampling and Attention Mechanism
Automatic segmentation of aggregate images with MET optimized by chaos SSA
Skin lesion segmentation based on high-resolution composite network
Colorectal polyp segmentation algorithm using DoubleUNet network
Crack detection and segmentation in CT images using Hessian matrix and support vector machine

Related Author

SONG Jianli
LÜ Xiaoqi
GU Yu
Liming LIANG
Longsong ZHOU
Jun FENG
Xiaoqi SHENG
Jian WU

Related Institution

School of Information Engineering， Inner Mongolia University of Technology
School of Information Engineering， Inner Mongolia University of Science and Technology
School of Computer Science and Engineering，South China University of Technology
School of Electrical Engineering and Automation，Jiangxi University of Science and Technology
College of Information Engineering， Jiangxi University of Science and Technology
0