Identification and characteristic statistics of surface microstructure of titanium metal based on cavitation water jet

The application of cavitation water jet technology to modify medical implant surfaces facilitates the formation of distinctive microporous structures, thereby enhancing the contact area between the implant and alveolar bone, and improving osseointegration. Therefore, the microstructure characteristics of the modified implant are one of the important evaluation indicators of the modification effect. This paper proposes a processing method for the identification and statistical analysis of surface micro-morphology images. The method incorporates techniques such as image enhancement, image segmentation, morphological image processing methods, and pixel matrix operations, enabling automated quantification of pit counts, the relative positions of the pits, and other topographic characteristics of the material surface. Simultaneously, the microstructure of each pit is spatially fitted and reconstructed to standardize measurement benchmarks for pit diameter and depth characteristics. This facilitates in-depth multi-dimensional analysis of material surface characteristic information and provides foundational support for further exploration of cavitation jet modification technology. In the study, the modification effect of processing time on the surface morphology of titanium metal was used as an application case. A surface morphology feature information database was established under different processing times, and statistical analysis was conducted on proportion, structural distribution, and other characteristics in the focus areas. The results show that the diameter and proportion distribution of the pits produced by cavitation jet modification tend to be stable when the jet pressure and standoff distance remain constant, while the depth of the pit increases with the increasing processing time.