Application of Bidimensional Empirical Mode Decomposition in Liquid Turbidity Detection

GUO Qiang; DIAO Yuan-peng; ZHAO Qun; MAO Liang-ming

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Application of Bidimensional Empirical Mode Decomposition in Liquid Turbidity Detection

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- Application of Bidimensional Empirical Mode Decomposition in Liquid Turbidity Detection
- Vol. 17, Issue 2, Pages: 5-9(2012)
- 作者机构：
  
  1. 哈尔滨工程大学信息与通信工程学院
  2. 黑龙江省科学院自动化研究所
  3. 西南电子设备研究所电子信息控制重点实验室
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391.41;TP274
- Published：2012
- 稿件说明：
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GUO Qiang, DIAO Yuan-peng, ZHAO Qun, et al. Application of Bidimensional Empirical Mode Decomposition in Liquid Turbidity Detection[J]. 2012, 17(2): 5-9.
DOI：

GUO Qiang, DIAO Yuan-peng, ZHAO Qun, et al. Application of Bidimensional Empirical Mode Decomposition in Liquid Turbidity Detection[J]. 2012, 17(2): 5-9. DOI：

摘要

针对液体混浊度检测易受噪声影响这一技术问题

提出了一种基于二维经验模态分解联合Robert算子的医疗液体混浊度检测方法

对医疗液体图像进行二维经验模态分解

将液体图像分解成多层本征模态函数(IMF)

并利用Robert算子对各分量IMF进行边缘检测

选择性地逐层重构出图像边缘

从而将图像与杂质的边缘细节突显出来.实验结果表明

该方法有效地降低了随机噪声对液体混浊度检测的影响

提高了液体混浊度检测的精度

进而验证了该算法的可行性和有效性.

Abstract

The liquid turbidity detection is easily affected by the noise

So a Robert operator edge detection algorithm based on Bidimensional Empirical Mode Decomposition(BEMD) to detect medical liquid opacity is proposed

which divides the medical liquid images into Intrinsic Mode Function(IMF)by using BEMD.Then we employ a Robert operator to detect the edge of each IMF.The image edge is rebuilt layer by layer selectively.Such process can highlight the edge details of the image and impurities.

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