Regression-based detection of missing boundaries in multiphase polycrystalline microstructures

An efficient alternative approach for detecting missing boundaries in micrographs is presented in the current work. By treating the missing boundaries as a class of object, a suitable detection algorithm is extended to realise discontinuities in interfaces separating phases and grains. The metrics, including precision and recall, estimated during the development of the model indicate noteworthy performance. Moreover, a direct comparison with actual situations attests to the accuracy of the current approach in detecting missing boundaries across different multiphase polycrystalline micrographs.