Microstructural Images Segmentation Techniques: A Review

Abstract

Image segmentation is the process of automatically dividing an image into distinct, meaningful, and non-overlapping regions. The quality of the segmentation process determines the efficiency of other image processing tasks. Analyzing microstructural images is crucial since the mechanical properties are strongly dependent on the microstructural phases’ statistics. These images are considered one of the most difficult and challenging images to deal with due to their special characteristics, such as the convergence in pixels intensity values, overlapping in colors, boundaries and textures in phase regions, infinite shapes of grains and colonies, etc. As there is no generic technique suitable to be used with all microstructures, this work reviews techniques that have been effectively used and recommended to be employed in metallurgical research, with a brief description of their principles, advantages, and disadvantages, and discusses their applicability. The major aim of this work is to spare time and effort searching for and experimenting with all the available methods for future researchers.