Research Of Liquid Impurities Detection Based On Embedded System

The impurities which mixed in the medical liquid in the production process has seriously harm to the health of patients. As the result of the manual detection methods which affected by the subjectivity is not satisfactory, therefore the research of automatic detection system for medical liquid impurity has great theoretical significance and application value.Firstly, the related theory and technology of the detection of liquid impurities are introduced. For the characteristic of impurities image, the digital image processing technology and commonly used algorithms which related to the detection system of liquid impurities were analyzed, such as image enhancement, image segmentation and binary image with mathematical morphology.Secondly, the basic model and the simplified model of the pulse coupled neural network were analyzed. As the shortcomings of parameters need to be re-set in the model, the least-squares approach and gradient descent algorithm have been integrated in the adaptive pulse coupled neural network, which solved the demand of ignition time series to the light sensitivity. On this basis, the image enhancement, image segmentation, region labeling algorithm and area calculation method based on pulse coupled neural network which combined with the relevant theory of digital image processing have been researched.Finally, the impurity detection embedded system has been designed based on the processor DM642, and the hardware and software analysis and design of the system have been given separately in detail. The system hardware includes three parts:video capture, image processing and control unit, and the following functions which include system video capture, image enhancement, impurity detection, impurity identification and substandard products removal have been implemented in software. The experimental results show that the proposed algorithm and designed system meets the online detection requirements.