All-optical image processing has been viewed as a promising technique for its high computation speed and low power consumption.However,current methods are often restricted to few functionalities and low reconfigurabil...All-optical image processing has been viewed as a promising technique for its high computation speed and low power consumption.However,current methods are often restricted to few functionalities and low reconfigurabilities,which cannot meet the growing demand for device integration and scenario adaptation in next-generation vision regimes.Here,we propose and experimentally demonstrate a bilayer liquid crystal computing platform for reconfigurable image processing.Under different in-situ/ex-situ twisted/untwisted conditions of the layers,our approach allows for eight kinds of image processing functions,including one/two-channel bright field imaging,one/two-channel vortex filtering,horizontally/vertically one-dimensional edge detection,vertex detection,and photonic spin Hall effect-based resolution adjustable edge detection.A unified theoretical framework for this scheme is established on the transfer function theory,which coincides well with the experimental results.The proposed method offers an easily-switchable multi-functional solution to optical image processing by introducing mechanical degrees of freedom,which may enable emerging applications in computer vision,autonomous driving,and biomedical microscopy.展开更多
The flexible structure of photonic crystal fibre not only offers novel optical properties but also brings some difficulties in keeping the fibre structure in the fabrication process which inevitably cause the optical ...The flexible structure of photonic crystal fibre not only offers novel optical properties but also brings some difficulties in keeping the fibre structure in the fabrication process which inevitably cause the optical properties of the resulting fibre to deviate from the designed properties. Therefore, a method of evaluating the optical properties of the actual fibre is necessary for the purpose of application. Up to now, the methods employed to measure the properties of the actual photonic crystal fibre often require long fibre samples or complex expensive equipments. To our knowledge, there are few studies of modeling an actual photonic crystal fibre and evaluating its properties rapidly. In this paper, a novel method, based on the combination model of digital image processing and the finite element method, is proposed to rapidly model the optical properties of the actual photonic crystal fibre. Two kinds of photonic crystal fibres made by Crystal Fiber A/S are modeled. It is confirmed from numerical results that the proposed method is simple, rapid and accurate for evaluating the optical properties of the actual photonic crystal fibre without requiring complex equipment.展开更多
Total green leaf area(GLA)is an important trait for agronomic studies.However,existing methods for estimating the GLA of individual rice plants are destructive and labor-intensive.A nondestructive method for estimatin...Total green leaf area(GLA)is an important trait for agronomic studies.However,existing methods for estimating the GLA of individual rice plants are destructive and labor-intensive.A nondestructive method for estimating the total GLA of individual rice plants based on multi-angle color images is presented.Using projected areas of the plant in images,linear,quadratic,exponential and power regression models for estimating total GLA were evaluated.Tests demonstrated that the side-view projected area had a stronger relationship with the actual total leaf area than the top-projected area.And power models fit better than other models.In addition,the use of multiple side-view images was an efficient method for reducing the estimation error.The inclusion of the top-view projected area as a seoond predictor provided only a slight improvement of the total leaf area est imation.When the projected areas from multi angle images were used,the estimated leaf area(ELA)using the power model and the actual leaf area had a high correlation cofficient(R2>0.98),and the mean absolute percentage error(MAPE)was about 6%.The method was capable of estimating the total leaf area in a nondestructive,accurate and eficient manner,and it may be used for monitoring rice plant growth.展开更多
This paper surveys models and statistical properties of random systems of hard particles. Such systems appear frequently in materials science, biology and elsewhere. In mathematical-statistical investigations, simulat...This paper surveys models and statistical properties of random systems of hard particles. Such systems appear frequently in materials science, biology and elsewhere. In mathematical-statistical investigations, simulations of such structures play an important role. In these simulations various methods and models are applied, namely the RSA model, sedimentation and collective rearrangement algorithms, molecular dynamics, and Monte Carlo methods such as the Metropolis-Hastings algorithm. The statistical description of real and simulated particle systems uses ideas of the mathematical theories of random sets and point processes. This leads to characteristics such as volume fraction or porosity, covariance, contact distribution functions, specific connectivity number from the random set approach and intensity, pair correlation function and mark correlation functions from the point process approach. Some of them can be determined stereologically using planar sections, while others can only be obtained using three-dimensional data and 3D image analysis. They are valuable tools for fitting models to empirical data and, consequently, for understanding various materials, biological structures, porous media and other practically important spatial structures.展开更多
基金supported in part by the National Natural Science Foundation of China(12421005,12374273,and 61805077)in part by the Natural Science Foundation of Hunan Province(2025JJ50046)in part by the Hunan Provincial Major Sci-Tech Program(2023ZJ1010)。
文摘All-optical image processing has been viewed as a promising technique for its high computation speed and low power consumption.However,current methods are often restricted to few functionalities and low reconfigurabilities,which cannot meet the growing demand for device integration and scenario adaptation in next-generation vision regimes.Here,we propose and experimentally demonstrate a bilayer liquid crystal computing platform for reconfigurable image processing.Under different in-situ/ex-situ twisted/untwisted conditions of the layers,our approach allows for eight kinds of image processing functions,including one/two-channel bright field imaging,one/two-channel vortex filtering,horizontally/vertically one-dimensional edge detection,vertex detection,and photonic spin Hall effect-based resolution adjustable edge detection.A unified theoretical framework for this scheme is established on the transfer function theory,which coincides well with the experimental results.The proposed method offers an easily-switchable multi-functional solution to optical image processing by introducing mechanical degrees of freedom,which may enable emerging applications in computer vision,autonomous driving,and biomedical microscopy.
基金Project supported by the National Basic Research Program of China(Grant No.2010CB328206)the National Natural Science Foundation of China(Grant No.60977033)the Science and Technology Innovation Foundation for Excellent Doctors of Beijing Jiaotong University,China(Grant Nos.141055522 and 141060522)
文摘The flexible structure of photonic crystal fibre not only offers novel optical properties but also brings some difficulties in keeping the fibre structure in the fabrication process which inevitably cause the optical properties of the resulting fibre to deviate from the designed properties. Therefore, a method of evaluating the optical properties of the actual fibre is necessary for the purpose of application. Up to now, the methods employed to measure the properties of the actual photonic crystal fibre often require long fibre samples or complex expensive equipments. To our knowledge, there are few studies of modeling an actual photonic crystal fibre and evaluating its properties rapidly. In this paper, a novel method, based on the combination model of digital image processing and the finite element method, is proposed to rapidly model the optical properties of the actual photonic crystal fibre. Two kinds of photonic crystal fibres made by Crystal Fiber A/S are modeled. It is confirmed from numerical results that the proposed method is simple, rapid and accurate for evaluating the optical properties of the actual photonic crystal fibre without requiring complex equipment.
基金supported by grants from the National Program on High Technology Development (2013AA102403)the National Program for Basic Research of China (2012CB114305)+2 种基金the National Natural Science Foundation of China (30921091,31200274)the Program for New Century Excellent Talents in University (No.NCET-10-0386)the Fundamental Research Funds for the Central Universities (No.2013PY034).
文摘Total green leaf area(GLA)is an important trait for agronomic studies.However,existing methods for estimating the GLA of individual rice plants are destructive and labor-intensive.A nondestructive method for estimating the total GLA of individual rice plants based on multi-angle color images is presented.Using projected areas of the plant in images,linear,quadratic,exponential and power regression models for estimating total GLA were evaluated.Tests demonstrated that the side-view projected area had a stronger relationship with the actual total leaf area than the top-projected area.And power models fit better than other models.In addition,the use of multiple side-view images was an efficient method for reducing the estimation error.The inclusion of the top-view projected area as a seoond predictor provided only a slight improvement of the total leaf area est imation.When the projected areas from multi angle images were used,the estimated leaf area(ELA)using the power model and the actual leaf area had a high correlation cofficient(R2>0.98),and the mean absolute percentage error(MAPE)was about 6%.The method was capable of estimating the total leaf area in a nondestructive,accurate and eficient manner,and it may be used for monitoring rice plant growth.
文摘This paper surveys models and statistical properties of random systems of hard particles. Such systems appear frequently in materials science, biology and elsewhere. In mathematical-statistical investigations, simulations of such structures play an important role. In these simulations various methods and models are applied, namely the RSA model, sedimentation and collective rearrangement algorithms, molecular dynamics, and Monte Carlo methods such as the Metropolis-Hastings algorithm. The statistical description of real and simulated particle systems uses ideas of the mathematical theories of random sets and point processes. This leads to characteristics such as volume fraction or porosity, covariance, contact distribution functions, specific connectivity number from the random set approach and intensity, pair correlation function and mark correlation functions from the point process approach. Some of them can be determined stereologically using planar sections, while others can only be obtained using three-dimensional data and 3D image analysis. They are valuable tools for fitting models to empirical data and, consequently, for understanding various materials, biological structures, porous media and other practically important spatial structures.
