Detection of visual defects on rotationally symmetric objects

The paper describes a method using digital image processing in the detection of vaguely defined visual defects on objects symmetric with respect to a rotation axis. Automotive wheels and hubcaps, fans, turbines, symmetrical ceramic goods, merchandise, etc., are examples of such objects. The method uses the object's surface symmetry to identify areas that do not meet the requirement for the symmetry. The method is based on the brightness comparison of areas of the object's surface under test corresponding to each other with respect to the object's rotational symmetry. The area containing a defect is located through the difference between its brightness and average brightness of the all symmetric areas. The reliability of the method requires opaque and not too broken surfaces with solitary defects that do not overlap when the object is rotated. The method is advantageous for larger defects. Minimum defect size is limited by segmentation of the object and its production tolerances. Uniform illumination is another prerequisite for the reliable detection of the defects. This work focuses on testing the method and determination of the optimum brightness difference characterizing the defect. Next, limitations of the method are analyzed, especially the relationship between the uncertainty of the object shape, the camera resolution, and the minimum size of the detected defect. (C) 2020 Optical Society of America