基于图像阈值分割算法的污水悬浮颗粒浓度检测方法  

Detection Method of Suspended Particle Concentration in Sewage Based on Image Threshold Segmentation Algorithm

作　　者：刘琴[1] 安见才让[1] Liu Qin;Aanjiancairang(College of Computer Qinghai University for Nationalities,Xining,Qinghai 810007)

机构地区：[1]青海民族大学计算机学院,青海西宁810007

出　　处：《佳木斯大学学报（自然科学版）》2024年第11期6-9,共4页Journal of Jiamusi University：Natural Science Edition

基　　金：教育部第二批新工科研究与实践项目(2020);青海民族大学校级教学改革研究项目(2021-JYZD-002)。

摘　　要：为实现对污水悬浮颗粒浓度的准确检测,提出基于图像阈值分割算法的污水悬浮颗粒浓度检测研究。先采集污水悬浮颗粒图谱信息,提取污水悬浮颗粒红外光谱的熵特征量,然后构建污水红外光谱图像的阈值分割和多尺度特征分解模型,求解污水悬浮颗粒流体域和固体域的图像特征耦合性特征量,最后通过污水悬浮颗粒红外特征变量类型与取值范围的差异性,实现污水悬浮颗粒浓度检测。测试表明,该方法检测精度高于0.9,证明所提方法提高了污水悬浮颗粒的有效治理能力。In order to achieve the accurate detection of sewage suspended particle concentration,a study of sewage suspended particle concentration detection based on image threshold segmentation algorithm was proposed.Firstly,the spectrum information of sewage suspended particles is collected,and the entropy characteristic quantity of the infrared spectrum of sewage suspended particles is extracted.Then,the threshold segmentation and multi-scale feature decomposition model of sewage infrared spectral image are constructed to solve the coupling characteristic quantity of image features of sewage suspended particles in the fluid domain and the solid domain.Finally,the differences between the types and value ranges of infrared characteristic variables of sewage suspended particles are analyzed.The concentration of suspended particles in sewage can be detected.The test results show that the detection accuracy of this method is higher than 0.9,which proves that the proposed method can improve the effective treatment ability of sewage suspended particles.

关 键 词：图像阈值分割 污水 悬浮颗粒 浓度检测 红外光谱 

分 类 号：TQ028[化学工程] TP391[自动化与计算机技术—计算机应用技术]