Nondestructive Testing Wood Internal Defects by Fractional Brownian Motion Processor

Applying the fractional Brownian motion model, we investigate and analyze fractal dimension of the X-ray image of log with rotten knot. Firstly, pre-process the wood image so that the image features are enhanced and more suitable for later processing. Then derive fractal dimension estimation algorithm based on the fractional Brownian motion model and calculate fractal dimensions of all the sub areas in wood image one by one. The results show that the fractal dimensions in the normal regions are higher than that of the rotten knot edges. We can extract the edges of wood defects effectively according to this rule. It can be known from the experimental results that this method is effective for testing inner defects of wood, and has important significance for promoting the application of fractal theory. At the same time this study provides a new method for digital image processing and edge detection.