Analysis and Characterization of Dendrite Structures From Microstructure Images of Material

Abstract

Digital Image processing (DIP) and Computer vision (CV) techniques have great support role in material manufacturing by providing precise insight of materials. The morphology of constituents in metal alloys basically depends on the process of solidification. The solidification method (air, oil or water) and time are the reasons for definite morphology of constituents. Dendrite structures are one of the, such morphological structures and many important properties of materials are closely related to the morphology of the dendrite. The information about solidification process of materials is a must-know information in the process of production of materials which can be extracted through characterization of dendrite structures. In this paper, an automated and robust method that comprises of image processing, computer vision and serial sectioning techniques as a means of 3D characterization of the solidified microstructures of magnesium-based alloys is presented. The phase fraction and morphologies of intermetallics of magnesium -aluminium alloy material are determined. The results obtained by proposed method are compared with the manual computations based on the Scheil-Gulliver solidification model [12,13] for the authenticity of proposed method. The comparison of results indicates that the results of the proposed method are much accurate compared to other methods. Therefore, the proposed method will enable a comprehensive understanding of solidification variables, microstructure, and properties.