Automatic and Accurate Measurement of Microhardness Profile Based on Image Processing
Yongjie Zhao, Wen Xu, Chang Ze Xi, Dong Liang, Haonan Li
Abstract
The micro/nanohardness profile has been extensively used in manufacturing to understand material properties from external surfaces to internal material. The microhardness profile requires the indentation dimension and depth measurements. Dimension measurement in most cases is interfered by noise, texture, or defects, while depth identification asks for accurate stitching of local micrographs and recognition of tilted machined surfaces. However, few commercial microhardness testers can address the issues, while the manual measurement is limited by low robustness and efficiency. To fill this gap, this paper proposes an automatic and accurate measurement method of microhardness profile based on image processing. The method can stitch local micrographs, recognize indentation dimensions and depths, generate the microhardness profile, and analyze the material property with only one click. Experiments proved the method enjoys high accuracy, automation, and robustness.