Log x-ray image edge detection based on fractal-morphology analysis

The aim of this study is to assess log quality and extract the internal defects information from a log x-ray image with fractal and mathematical morphology method. Firstly, the log image is divided into sub areas, calculate the multi-scale fractal feature (D_MF) of each sub areas, the D_MF values of different regions in a log image are normally different. According to the values of D_MF the internal defects in log can be detected and classified. In order to obtain more continuous edges of the defects in log x-ray image, mathematical morphology theory was also applied in this paper and square structuring element is selected to do a further processing. The experimental result show that, compare to the traditional methods, the method for edge detection of the image based on fractal and mathematical morphology, achieved a better anti-noise performance and preserving the useful defects detail of the log x-ray image effectively.