Steels are alloys of iron and carbon, widely used in construction and other applications. The evolution of steel microstructure through various heat treatment processes is an important factor in controlling properties and performance of steel. Extensive experimentations have been performed to enhance the properties of steel by customizing heat treatment processes. However, experimental analyses are always associated with high resource requirements in terms of cost and time. As an alternative solution, we propose an image processing-based technique for refinement of raw plain carbon steel microstructure images, into a digital form, usable in experiments related to heat treatment processes of steel in diverse applications. The proposed work follows the conventional steps practiced by materials engineers in manual refinement of steel images; and it appropriately utilizes basic image processing techniques (including filtering, segmentation, opening, and clustering) to automate the whole process. The proposed refinement of steel microstructure images is aimed to enable computer-aided simulations of heat treatment of plain carbon steel, in a timely and cost-efficient manner; hence it is beneficial for the materials and metallurgy industry. Our experimental results prove the efficiency and effectiveness of the proposed technique.