In this project, digital image analysis is applied to Scanning Electron Microscope images of dispersion barriers to measure specific properties. The thin barriers are used as protection for paperboard packaging and are made of polymers and fillers.
The orientation, area, length and density distributions of the fillers determine the functionality and quality of the barrier. Methods built on image analysis tools are developed with the objective to measure these quantities.
Input for the methods are Scanning Electron Microscope images showing the cross-section of the barriers. To make the images relevant for the methods they are pre processed by reducing noise and distinguishing fillers from the background. For measuring the orientation distribution of the fillers two different methods are implemented and compared. The first one is based on a structure tensor and the other one applies a co variance matrix.
The structure tensor is preferable because of its flexibility and better performance for complex images. The area and length distributions are measured by applying mathematical morphology together with soft-clipping. The density distribution is obtained by filtering the underlying image twice with a uniform filter which creates a heat map.
The developed methods are evaluated by applying them on fabricated binary test images with known properties. The methods are very accurate when applied on simple test images but for more complex test images with greater variation the accuracy decreases. However, for most applications the results are still on an acceptable level.
Source : Uppsala University
Author : Aiesh, Basel