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Automatic Recognition of Dendritic Solidification Structures: DenMap

Bogdan Nenchev, Joel Strickland, Karl Tassenberg, S. J. Perry, Simon P.A. Gill, Hongbiao Dong

2020Journal of Imaging20 citationsDOIOpen Access PDF

Abstract

Dendrites are the predominant solidification structures in directionally solidified alloys and control the maximum length scale for segregation. The conventional industrial method for identification of dendrite cores and primary dendrite spacing is performed by time-consuming laborious manual measurement. In this work we developed a novel DenMap image processing and pattern recognition algorithm to identify dendritic cores. Systematic row scan with a specially selected template image over an image of interest is applied via a normalised cross-correlation algorithm. The DenMap algorithm locates the exact dendritic core position with a 98% accuracy for a batch of SEM images of typical as-cast CMSX-4® microstructures in under 90 s per image. Such accuracy is achieved due to a sequence of specially selected image pre-processing methods. Coupled with statistical analysis the model has the potential to gather large quantities of structural data accurately and rapidly, allowing for optimisation and quality control of industrial processes to improve mechanical and creep performance of materials.

Topics & Concepts

Dendrite (mathematics)Computer sciencePosition (finance)Artificial intelligenceImage (mathematics)Image processingPattern recognition (psychology)Computer visionMaterials scienceMathematicsEconomicsGeometryFinanceIndustrial Vision Systems and Defect DetectionSolidification and crystal growth phenomenaMetallurgical Processes and Thermodynamics
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