Previous collaborative studies have shown the main fringe patterns and their typical classification with regard to defects.Nevertheless,the complexity of the results prevents defect detection automation based on a fri...Previous collaborative studies have shown the main fringe patterns and their typical classification with regard to defects.Nevertheless,the complexity of the results prevents defect detection automation based on a fringe pattern classification table.The use of fringe patterns for the structural diagnosis of artwork is important for conveying crucial detailed information and dense data sources that are unmatched compared to those obtained using other conventional or modern techniques.Hologram interferometry fringe patterns uniquely reveal existing and potential structural conditions independent of object shape,surface complexity,material inhomogeneity,multilayered and mixed media structures,without requiring contact and interaction with the precious surface.Thus,introducing a concept that from one hand allows fringe patterns to be considered as a powerful standalone physical tool for direct structural condition evaluation with a focus on artwork conservators'need for structural diagnosis while sets a conceptual basis for defect detection automation is crucial.The aim intensifies when the particularities of ethics and safety in the field of art conservation are considered.There are ways to obtain the advantages of fringe patterns even when specialized software and advanced analysis algorithms fail to convey usable information.Interactively treating the features of fringe patterns through step-wise reasoning provides direct diagnosis while formulates the knowledge basis to automate defect isolation and identification procedures for machine learning and artificial intelligence(AI)development.The transfer of understanding of the significance of fringe patterns through logical steps to an AI system is this work's ultimate technical aim.Research on topic is ongoing.展开更多
文摘Previous collaborative studies have shown the main fringe patterns and their typical classification with regard to defects.Nevertheless,the complexity of the results prevents defect detection automation based on a fringe pattern classification table.The use of fringe patterns for the structural diagnosis of artwork is important for conveying crucial detailed information and dense data sources that are unmatched compared to those obtained using other conventional or modern techniques.Hologram interferometry fringe patterns uniquely reveal existing and potential structural conditions independent of object shape,surface complexity,material inhomogeneity,multilayered and mixed media structures,without requiring contact and interaction with the precious surface.Thus,introducing a concept that from one hand allows fringe patterns to be considered as a powerful standalone physical tool for direct structural condition evaluation with a focus on artwork conservators'need for structural diagnosis while sets a conceptual basis for defect detection automation is crucial.The aim intensifies when the particularities of ethics and safety in the field of art conservation are considered.There are ways to obtain the advantages of fringe patterns even when specialized software and advanced analysis algorithms fail to convey usable information.Interactively treating the features of fringe patterns through step-wise reasoning provides direct diagnosis while formulates the knowledge basis to automate defect isolation and identification procedures for machine learning and artificial intelligence(AI)development.The transfer of understanding of the significance of fringe patterns through logical steps to an AI system is this work's ultimate technical aim.Research on topic is ongoing.
