To explore the correlation between crop leaf digital RGB(Red,Green and Blue)image features and the corresponding moisture content of the leaf,a Canon digital camera was used to collect image information from detached ...To explore the correlation between crop leaf digital RGB(Red,Green and Blue)image features and the corresponding moisture content of the leaf,a Canon digital camera was used to collect image information from detached leaves of heading-stage maize.A drying method was adopted to measure the moisture content of the leaf samples,and image processing technologies,including gray level co-occurrence matrices and grayscale histograms,was used to extract the maize leaf texture feature parameters and color feature parameters.The correlations of these feature parameters with moisture content were analyzed.It is found that the texture parameters of maize leaf RGB images,including contrast,correlation,entropy and energy,were not significantly correlated with moisture content.Thus,it was difficult to use these features to predict moisture content.Of the six groups of eigenvalues for the leaf color feature parameters,including mean,variance,energy,entropy,kurtosis and skewness,mean and kurtosis were found to be correlated with moisture content.Thus,these features could be used to predict the leaf moisture content.The correlation coefficient(R2)of the mean-moisture content relationship model was 0.7017,and the error of the moisture content prediction was within±2%.The R2 of the kurtosis-moisture content relationship model was 0.7175,and the error of the moisture content prediction was within±1.5%.The study results proved that RGB images of crop leaves could be used to measure moisture content.展开更多
Crackles are an important kind of abnormal and discontinuous lung sounds,which have been found to be correlated to types of pulmonary diseases.The purpose of this work is to show a new perspective to solve the problem...Crackles are an important kind of abnormal and discontinuous lung sounds,which have been found to be correlated to types of pulmonary diseases.The purpose of this work is to show a new perspective to solve the problem of crackle detection,based on an emerging theory of fractional Hilbert transform.By applying fractional Hilbert transform to lung sound signals,a two-dimension texture image can be generated.The texture features corresponding to crackles are quite easy to be extracted.Experiments illustrate the effectiveness of our method.展开更多
基金This paper was founded by the National Science&Technology Supporting Plan(2012BAH29B04-02)the Science and Technology Innovation Project from Northwest A&F University(Z109021202).
文摘To explore the correlation between crop leaf digital RGB(Red,Green and Blue)image features and the corresponding moisture content of the leaf,a Canon digital camera was used to collect image information from detached leaves of heading-stage maize.A drying method was adopted to measure the moisture content of the leaf samples,and image processing technologies,including gray level co-occurrence matrices and grayscale histograms,was used to extract the maize leaf texture feature parameters and color feature parameters.The correlations of these feature parameters with moisture content were analyzed.It is found that the texture parameters of maize leaf RGB images,including contrast,correlation,entropy and energy,were not significantly correlated with moisture content.Thus,it was difficult to use these features to predict moisture content.Of the six groups of eigenvalues for the leaf color feature parameters,including mean,variance,energy,entropy,kurtosis and skewness,mean and kurtosis were found to be correlated with moisture content.Thus,these features could be used to predict the leaf moisture content.The correlation coefficient(R2)of the mean-moisture content relationship model was 0.7017,and the error of the moisture content prediction was within±2%.The R2 of the kurtosis-moisture content relationship model was 0.7175,and the error of the moisture content prediction was within±1.5%.The study results proved that RGB images of crop leaves could be used to measure moisture content.
文摘Crackles are an important kind of abnormal and discontinuous lung sounds,which have been found to be correlated to types of pulmonary diseases.The purpose of this work is to show a new perspective to solve the problem of crackle detection,based on an emerging theory of fractional Hilbert transform.By applying fractional Hilbert transform to lung sound signals,a two-dimension texture image can be generated.The texture features corresponding to crackles are quite easy to be extracted.Experiments illustrate the effectiveness of our method.
