Automatic identification of grains of material samples

A number of techniques are now available for the characterization of solid surfaces using an Optical Laser Microscope (OLM). It has firmly established its role in industry and elsewhere for routing high-resolution studies of surface structure and topography. One of the most common operations in machine vision is finding the connected components in an image. In this work, a component-labeling algorithm will find all connected components in an image and assigns a unique label to all points in the same component. After capturing the image from OLM, various grains features were extracted at the first step and shipped to the second step for the final statistical analysis, performed with the aid of MATLAB software. The raster graphics is used to visualize the surface data which is one of the best techniques that has occupied computer graphics analysis. All observable features in material sample can be counted and measured with the aid of the (computerized optical laser microscope).