Study On Nanometer Particle Size Measurement Method Based On Partial Differential Equation

The properties of materials synthesized with Nanoparticles (NPs) are highly correlated to the sizes and shapes of the NPs. The transmission electron microscopy (TEM) image can be used to measure size and observe the morphological characteristics of NPs. To analyze and measure NPs with the image processing technology can effectively enhance the efficiency, accuracy and automation degree of the size measurement of NPs. In this thesis, partial differential equation (PDE) methods are used for NPs filter and segmentation. On the basis of NPs segmentation, size measurement and evaluation are achieved automatically.The main contents of this thesis are as follows. Firstly, PDE is used for NPs image preprocessing. The filtering capacity of the PDE diffusion models is analyzed for NPs image, the proper filtering method is chosen depending on the type of NPs. Secondly, NPs are segmented with the level set image segmentation method in PDE framework. The advantages and shortcomings of several active contour models are studied from the principle of curve evolution, and the segmentation performance for NPs is analyzed. To overcome the challenges like uneven gray-level and weak edge of NPs, RSF level set segmentation model is adopted. Next, NPs boundaries obtained from the segmentation results are fitted into the basic geometric shapes similar to NPs. Finally, according to the fitting results, the statistical parameters are measured including size parameters (such as partical size, area, etc.) and shape parameters (such as aspect ratio, sphericity, etc.). We evaluated the uniformity of the particles based on the statistical results. The experimental results show the proposed NPs size measurement method based on the partial differential equation is effective.