CHORD: Cascaded and a contrario method for hole crack detection

We propose a cascaded and a contrario hole crack detection (CHORD) method for defect inspection in digital images of turbine blade surfaces. This is the first time an automatic image processing-based method is proposed for such a task. It consists of two major steps: first, the appearance of holes is approximated by ellipses and cascaded pose regression is used to estimate the position and orientation of the holes; Second, we define hole cracks as geometrical structures and a contrario method is used to assess the meaningfulness of each crack. The model-based CHORD method fully considers the features of hole cracks including the characteristics of brightness, length, and orientation, and therefore can accurately detect cracks in the images. The threshold on the strength of cracks is determined automatically and the computational time is about five seconds for each image.