Study on Quantitative Identification Method of Rock Fracture Based on Image Processing Technology

The traditional rock fracture feature extraction method is difficult to extract the fracture features timely and accurately, and the existing digital processing methods are not systematic. A method of quantitative identification and characterization of rock fractures based on image processing technology is proposed, and an automatic threshold segmentation algorithm is established on the basis of wavelet analysis to segment the fracture area of image. The region growth method is used to calculate the fracture area, after the image is segmented. The boundary tracking algorithm is used to extract the edge contour, and the zhang-Suen algorithm is used to calculate the crack skeleton. The momentum method is used to fit the skeleton tangent line, and the normal vector of the tangent line is calculated. The trigonometric function is transformed to calculate the crack inclination angle, and the crack width information is extracted and calculated with the DDA line drawing algorithm. The results show that the automatic threshold segmentation algorithm based on wavelet analysis is superior to the traditional Otsu algorithm in terms of segmentation effect, threshold selection and calculation speed. In the extraction and calculation of fracture characteristic values, this method not only ensures the smoothness of the skeleton, but also improves the fitting degree of the skeleton. This method is simpler and requires less calculation compared with the traditional method.