Abstract—Drilling is one of the routine operations carried out in geotechnical projects in order to retrieve samples from the ground. The retrieved samples, i.e. cores, are stored in boxes and analyzed by the geologists and mining engineers to determine several parameters required for rock mass classification systems, such as RMR (Rock Mass Rating), GSI (Geological Strength Index), and Q. For this routine task to be automated, cores should be segmented properly. In this paper, a method is introduced for the segmentation of cores and detection of their fracture paths by using shadows. First of all, three digital true color images of a core box, with the same camera position but different light source positions, are taken using a high resolution camera. After the detection of the core box with color thresholding, the sections of the box are detected by using Hough transform and boundary tracing algorithms. Then, after extracting cores from each row of the box using color thresholding, touching cores are separated from each other with the help of shadows, concave points, and edges. Finally, fracture paths of the cores are detected by taking positions of the light sources into account and tracing the boundaries of the detected shadows. All coding routines are developed in MATLAB 2017a. Two different core boxes with 4 and 5 rows storing HQ and NQ diameter cores having various joint/bedding plane angles are photographed to conduct the study.

Index Terms—core segmentation, fracture path detection, shadows, image processing

Cite: Hasan Ozturk and I. Turgut Saricam, "Core Segmentation and Fracture Path Detection Using Shadows," Journal of Image and Graphics, Vol. 6, No. 1, pp. 69-73, June 2018. doi: 10.18178/joig.6.1.69-73