Research On Two-dimensional Image Reconstruction Algorithm Of Log Defect Based On Linux System

There are a lot of research results on non-destructive testing of wood based on stress wave at home and abroad.However,most of the research results show that the internal information of wood is not accurate enough.Improving the accuracy of the results of non-destructive testing technology will greatly improve the practical value of stress wave nondestructive testing technology and can promote the rational use of wood.Therefore,the research of wood defect reconstruction algorithm is of great significance.In this paper,the statistical Gaussian mixture model is combined with the existing point velocity model to study the internal defect image reconstruction from a new perspective.The research of the two-dimensional image reconstruction algorithm based on Linux is based on the stress wave technique to collect the internal structure of the logs by and analyzing and building the mathematical model.Finally,the internal defects of the logs are modeled in the form of images by running on the Linux platform.The internal data of the log obtained from the stress wave is the propagation time of the stress wave in the wood.Then,the velocity of the stress wave in the logs is calculated by measuring the outer contour of the logs.Finally,the Gaussian mixture model is used to model and generate the final Defect image.In this paper,the FAKOPP stress wave measuring device is used to measure the logs,obtain the stress wave propagation time data,and measure the outer contour size of the logs.The Gaussian mixture model is used to establish the model of the stress wave propagation velocity data.Finally,OpenCV will get the model results in the form of images displayed.The image reconstruction method proposed in this paper is used to evaluate and analyze the image reconstruction results.The accuracy and generalization ability of the Gaussian mixture model were verified by different groups of experiments with different kinds of logs as experimental materials.The image reconstruction algorithm is implemented on the Linux platform to verify its engineering value.It can be concluded that the effect of using the Gaussian mixture model to reconstruct the log image is better than that of the existing point velocity model.The results of the reconstructed model of the cell multiplication model are accurate.The quantization result can be obtained by comparing the reconstructed image The Gaussian mixture model for image reconstruction fit can reach about 90%.By applying the model to the Linux platform,the engineering value of the image reconstruction model is greatly improved...