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Here we present a novel method to detect the boundaries of wood defects in X-ray wood images using the Hopfield Neural Network (HNN) algorithm based on Matlab programming. An improved energy function was designed for the HNN to perform the boundary detection which was formulated, in this paper, as an optimization process that could locate the boundary points of wood defects. The gray value of each...
The recognition of wood defects is very significant for reasonable selection and scientific utilization of wood. X-ray was adopted as a measure method for wood nondestructive testing. The difference of X-ray intensity after exposure is tested in order to judge whether the wood defects exist or not. Then the defects images were processed effectively. A group of describing shape features parameters...
X-ray real-time digital imaging technique is applied in getting log image without log destruction. This paper presents the average density value of the specific spot of log is measured quickly and exactly according to log perimeter and log image information using the method of artificial neural network. According to the basic knowledge of X-ray testing technique, the method of getting high quality...
Log image was acquired by X-ray real-time digital imaging system without log destruction. This paper presents the average density value of the specific spot of log is measured quickly and exactly according to log perimeter and log image information using the method of artificial neural network. According to the basic knowledge of X-ray testing technique, the method of getting high quality digital...
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