A novel method to separate and simultaneously record the Moiréinterferometry fringe patterns of three deformation fields with only one CCD camera is developed;details of its operation principle,key points and err...A novel method to separate and simultaneously record the Moiréinterferometry fringe patterns of three deformation fields with only one CCD camera is developed;details of its operation principle,key points and error analysis are presented.With this technique,the deformation in U,V and W fields can be measured simultaneously,so dynamic test with comprehensive information can be performed.The advantage of this technique over other similar techniques lies in its simplicity,easy implementation and low cost.An application of this technique is given to show its feasibility.Technical problems that may be caused with this technique are also analyzed.展开更多
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
Structured illumination microscopy(SIM)is a promising super-resolution technique for imaging subcellular structures and dynamics due to its compatibility with most commonly usedffuorescent labeling methods.Structured ...Structured illumination microscopy(SIM)is a promising super-resolution technique for imaging subcellular structures and dynamics due to its compatibility with most commonly usedffuorescent labeling methods.Structured illumination can be obtained by either laser interference or projection of fringe patterns.Here,we proposed a fringe projector composed of a compact multiwavelength LEDs module and a digital micromirror device(DMD)which can be directly attached to most commercial invertedffuorescent microscopes and update it into a SIM system.The effects of the period and duty cycle of fringe patterns on the modulation depth of the structured lightfield were studied.With the optimized fringe pattern,1:6×resolution improvement could be obtained with high-end oil objectives.Multicolor imaging and dynamics of subcellular organelles in live cells were also demonstrated.Our method provides a low-cost solution for SIM setup to expand its wide range of applications to most research labs in thefield of life science and medicine.展开更多
The knowledge of wing orientation and deformation during flapping flight is necessary for a complete aerodynamic analysis, but to date those kinematic features have not been simultaneously quantified for free-flying i...The knowledge of wing orientation and deformation during flapping flight is necessary for a complete aerodynamic analysis, but to date those kinematic features have not been simultaneously quantified for free-flying insects. A projected comb-fringe (PCF) method has been developed for measuring spanwise camber changes on free-flying dragonflies and on beating-flying dragonflies through the course of a wingbeat, which bases on projecting a fringe pattern over the whole measurement area and then measuring the wing deformation from the distorted fringe pattern. Experimental results demonstrate substantial camber changes both along the wingspan and through the course of a wingbeat. The ratio of camber deformation to chord length for hind wing is up to 0.11 at 75% spanwise with a flapping angle of -0.66 degree for a free-flying dragonfly.展开更多
Three-dimensional(3D)imaging with structured light is crucial in diverse scenarios,ranging from intelligent manufacturing and medicine to entertainment.However,current structured light methods rely on projector-camera...Three-dimensional(3D)imaging with structured light is crucial in diverse scenarios,ranging from intelligent manufacturing and medicine to entertainment.However,current structured light methods rely on projector-camera synchronization,limiting the use of affordable imaging devices and their consumer applications.In this work,we introduce an asynchronous structured light imaging approach based on generative deep neural networks to relax the synchronization constraint,accomplishing the challenges of fringe pattern aliasing,without relying on any a priori constraint of the projection system.To overcome this need,we propose a generative deep neural network with U-Net-like encoder-decoder architecture to learn the underlying fringe features directly by exploring the intrinsic prior principles in the fringe pattern aliasing.We train within an adversarial learning framework and supervise the network training via a statisticsinformed loss function.We demonstrate that by evaluating the performance on fields of intensity,phase,and 3D reconstruction.It is shown that the trained network can separate aliased fringe patterns for producing comparable results with the synchronous one:the absolute error is no greater than 8μm,and the standard deviation does not exceed 3μm.Evaluation results on multiple objects and pattern types show it could be generalized for any asynchronous structured light scene.展开更多
文摘A novel method to separate and simultaneously record the Moiréinterferometry fringe patterns of three deformation fields with only one CCD camera is developed;details of its operation principle,key points and error analysis are presented.With this technique,the deformation in U,V and W fields can be measured simultaneously,so dynamic test with comprehensive information can be performed.The advantage of this technique over other similar techniques lies in its simplicity,easy implementation and low cost.An application of this technique is given to show its feasibility.Technical problems that may be caused with this technique are also analyzed.
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.
基金The study was funded by the National Key Technologies R&D Program of China(2018YFC0114800 and 2017YFC0109900)the Natural Science Foundation of China(NSFC)(61405238)+1 种基金the Natural Science Foundation of Jiangsu Province(BK20141206)the Key Technologies R&D Program of Jiangsu Province(BE2018666).
文摘Structured illumination microscopy(SIM)is a promising super-resolution technique for imaging subcellular structures and dynamics due to its compatibility with most commonly usedffuorescent labeling methods.Structured illumination can be obtained by either laser interference or projection of fringe patterns.Here,we proposed a fringe projector composed of a compact multiwavelength LEDs module and a digital micromirror device(DMD)which can be directly attached to most commercial invertedffuorescent microscopes and update it into a SIM system.The effects of the period and duty cycle of fringe patterns on the modulation depth of the structured lightfield were studied.With the optimized fringe pattern,1:6×resolution improvement could be obtained with high-end oil objectives.Multicolor imaging and dynamics of subcellular organelles in live cells were also demonstrated.Our method provides a low-cost solution for SIM setup to expand its wide range of applications to most research labs in thefield of life science and medicine.
文摘The knowledge of wing orientation and deformation during flapping flight is necessary for a complete aerodynamic analysis, but to date those kinematic features have not been simultaneously quantified for free-flying insects. A projected comb-fringe (PCF) method has been developed for measuring spanwise camber changes on free-flying dragonflies and on beating-flying dragonflies through the course of a wingbeat, which bases on projecting a fringe pattern over the whole measurement area and then measuring the wing deformation from the distorted fringe pattern. Experimental results demonstrate substantial camber changes both along the wingspan and through the course of a wingbeat. The ratio of camber deformation to chord length for hind wing is up to 0.11 at 75% spanwise with a flapping angle of -0.66 degree for a free-flying dragonfly.
基金funding from the National Natural Science Foundation of China(Grant Nos.62375078 and 12002197)the Youth Talent Launching Program of Shanghai University+2 种基金the General Science Foundation of Henan Province(Grant No.222300420427)the Key Research Project Plan for Higher Education Institutions in Henan Province(Grant No.24ZX011)the National Key Laboratory of Ship Structural Safety
文摘Three-dimensional(3D)imaging with structured light is crucial in diverse scenarios,ranging from intelligent manufacturing and medicine to entertainment.However,current structured light methods rely on projector-camera synchronization,limiting the use of affordable imaging devices and their consumer applications.In this work,we introduce an asynchronous structured light imaging approach based on generative deep neural networks to relax the synchronization constraint,accomplishing the challenges of fringe pattern aliasing,without relying on any a priori constraint of the projection system.To overcome this need,we propose a generative deep neural network with U-Net-like encoder-decoder architecture to learn the underlying fringe features directly by exploring the intrinsic prior principles in the fringe pattern aliasing.We train within an adversarial learning framework and supervise the network training via a statisticsinformed loss function.We demonstrate that by evaluating the performance on fields of intensity,phase,and 3D reconstruction.It is shown that the trained network can separate aliased fringe patterns for producing comparable results with the synchronous one:the absolute error is no greater than 8μm,and the standard deviation does not exceed 3μm.Evaluation results on multiple objects and pattern types show it could be generalized for any asynchronous structured light scene.
