Flotation image segmentation by combining Fractional Differential, improved Level set and Watershed

Wang Weixing; 白明辉

您当前的位置：

首页 >

文章列表页 >

Flotation image segmentation by combining Fractional Differential, improved Level set and Watershed

更新时间：2023-11-14

- Flotation image segmentation by combining Fractional Differential, improved Level set and Watershed
- Advanced Engineering Sciences Vol. 48, Issue 4, Pages: 107-114(2016)
- 作者机构：
  
  1. 长安大学信息工程学院福州大学物理与信息工程学院
  2. 福州大学物理与信息工程学院18059148790 270629224@qq.com
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2016，
  
  Published Online：4 May 2016，
扫描看全文
王卫星,白明辉.基于分数阶微分、水平集及分水岭的铅锌浮选图像分割[J].工程科学与技术,2016,48(4):107-114.

Wang Weixing, 白明辉. Flotation image segmentation by combining Fractional Differential, improved Level set and Watershed. [J]. Advanced Engineering Sciences 48(4):107-114(2016)
王卫星,白明辉.基于分数阶微分、水平集及分水岭的铅锌浮选图像分割[J].工程科学与技术,2016,48(4):107-114. DOI：

Wang Weixing, 白明辉. Flotation image segmentation by combining Fractional Differential, improved Level set and Watershed. [J]. Advanced Engineering Sciences 48(4):107-114(2016) DOI：

摘要

中文摘要: 针对铅锌浮选气泡暗颜色、细节弱、分割难的特征，提出了一种新的图像分割算法。该算法分成三个部分：气泡边界增强：基于分形学改进分数阶微分算法，主要是根据图像的纹理特性自动确定分数阶微分的非整数阶数，以自适应分数阶微分算法增强气泡边缘；气泡亮点区域提取：在改进传统的水平集算法基础上，进行精确的气泡亮点区域的提取，克服了全局自动阈值算法在提取气泡亮点时存在的缺陷；图像分割：利用内外标记修正梯度图像，最后运用分水岭算法对浮选图像进行分割。对于不同铅锌矿大小气泡图像的实验，并通过与多种传统的图像分割算法分析比较，实验结果表明新算法不仅提高了浮选气泡图像的分割精度，并且有效地减少了传统图像分割算法的过分割问题，本文算法对于浮选气泡具有良好的分割效果。

Abstract

Abstract:In order to solve the problem of flotation bubbles that the information is weak in bubble edges

which causes image segmentation hard

the new algorithm combining the Fractional Differential

improved level set and Watershed was proposed. The algorithm includes three steps: Image enhancement: the Fractional differential order is automatically determined on image texture information by using fractal analysis

and the improved adaptive fractional differential algorithm is used to enhance bubble edges; Bubble white spot extraction: the traditional Level set algorithm is improved

and it is applied for extracting white spots of bubbles; Image segmentation: the internal and external markers of bubbles are utilized to correct the gradient images

and finally the marked Watershed segmentation algorithm is used to delineate bubbles. For a number of Lead Zink ore froth images with different bubble sizes

we compared several traditional image segmentation algorithms with the new algorithm

the experimental result shows the proposed algorithm can improve the image segmentation accuracy and is effective in reducing the over-segmentation problem. The proposed algorithm is effective in segmenting flotation bubbles.

关键词

浮选分数阶微分分形学水平集分水岭

Keywords

Flotationfractional differentialFractal analysisLevel setWatershed

references

更多指标>

Views

2052

下载量

CNKI被引量

Alert me when the article has been cited

提交

Tools

Publicity Resources

Edge Detection Based on Fractional Differential

Physicochemical Characteristics and Mineral Separation of A Phosphate Rock with Siliceous and Carbonates Gangues

Interactive Segmentation Method of 3D Fetal Ultrasound Image Based on Level Set Approach

Flotation Surface Bubble Displacement Motion Estimation Based on Bubble Tracking and Phase Correlation

Related Author

No data

Related Institution

四川大学电子信息学院四川

四川大学计算机学院四川

四川大学化学工程学院

中国科学院成都计算机应用研究所中国科学院大学

福州大学物理与信息工程学院

⁰