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.
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.The experimental results show that the method can effectively reduce the random noise on liquid turbidity detection effect,improving the liquid turbidity detection accuracy,which proves the feasibility and effectiveness of the proposed algorithm.
出处
《哈尔滨理工大学学报》
CAS
2012年第2期5-9,共5页
Journal of Harbin University of Science and Technology
基金
国家自然科学基金(60872108)
中国博士后科学基金(20080430903)
中国博士后科学基金特别资助(200902411)
哈尔滨市科技攻关计划项目(2011AA2CG007-2)
哈尔滨市科技创新人才研究专项基金(2008RFQXG030
2010RFQXG030)
黑龙江省博士后基金(LBH-Z08129)
中央高校基本科研专项(HEUCFZ1015)
关键词
二维经验模式分解
ROBERT算子
混浊度检测
bidimensional empirical mode decomposition（BEMD）
Robert operator
turbidity detection
