Segmentation and Classification of Zn-Al-Mg-Sn SEM BSE Microstructure

Abstract

The microstructure of materials is shaped not only by their chemical composition, but also by the thermomechanical processes used during the processing of a specific piece. The correct interpretation of the microstructure gives a rich source of information. This consists of several related steps, such as segmentation. Successful segmentation enables the qualitative as well as quantitative analysis of the individual microstructure components. The current paper deals with the segmentation and classification of four basic microstructure components of the Zn-Al-Mg-Sn alloy system. This is attempted with the help of several image processing techniques, where thresholding is the main one used. The investigated samples are the cast and annealed Zn-Al-Mg-Sn alloy bulks. The input data for this analysis are the SEM BSE images. These were taken for all alloys with a varying Sn content, covering a significant area of each investigated sample at different zoom levels. A semiautomatic algorithm running under Matlab is introduced. It addresses several tasks, such as preprocessing, noise filtering and decision methods. For the individual procedures, the time requirements for their execution are also indicated.