Crack and Fracture central line delineation on Steger and Hydrodynamics with improved Fractional differential.

The complex rock fracture and road pavement cracks are more difficult to extract than the other linear objects in an image. In rock engineering, the rock fracture is an important factor that might cause tunnel and bridge collapse, or rock slope or dam damage. In road construction, the crack is one of the main pavement diseases. To avoid the difficultly of extracting fractures/cracks in an image, a new algorithm for tracking the central lines of fractures or cracks is studied to alleviate the problem for image segmentation. It includes four aspects: (1) a new fractional differential template is established to enhance the blurring and weak fractures/cracks in an image, compared with the traditional fractional differential template Tiansi, the new template has no zero coefficient and can enhance the micro-fractures/cracks; (2) in order to decrease the difficulty level of fracture/crack extraction, an algorithm for extracting the feature points of the fracture/crack central line is proposed based on the idea of Steger algorithm; (3) after linking short gaps based on distance, the long gap linking is made according to the principle of hydrodynamics, it first makes judgment if the two neighboring feature points are in one crack or not, in which, the feature points are regarded as two spring resources, then in light on the idea of water gushed out of the spring, when the two water flows meet together, the two points are recognized in one crack, otherwise they are not in one crack and cannot be connected together and (4) if the two neighboring feature points are in one crack, then the distance and the curvature between the two line segments are calculated, if they are less than the given thresholds, the linking path is searched and the gap is filled. Compared with the four traditional algorithms by testing hundred images, the new algorithm can accurately and quickly extract the central lines in complex rock fracture and rough road pavement cracks, which can increase the accuracy of crack/fracture image segmentation compared to the other algorithms. [ABSTRACT FROM AUTHOR]