Macroparticle Detection in Surface Coating Using Image Processing

The thin films are coated on various surfaces to change or modify the characteristics of materials. The thin films are not very efficient because of macro particle formation. So there was a need to identify the reason behind macro particle formation, if there is a pattern in the formation of these macro particles and how these macro particles can be removed. Though there are various machines and software’s that do these particle detections but they are so expensive that those are only used by huge research labs. But the coating process is done in various organizations and for different applications even at smaller level. So there was a need to design a low cost thin film analysis model which can detect these macro particles and also identify if the coating quality is good or not. So the imaging of the thin films in this research was done using scanning electron microscopy. The images were analyzed and macro particles were detected using digital image processing algorithms like: gaussian filters to remove noise, image segmentation, watershed algorithm to separate & identify the particles and machine learning to make a film coating quality predicting model.