Defect inspection system by dot data

We successfully develop a defect inspection method based on a robust method for matching the distance between points in three dimensions. The three-dimensional distance data of an object is measured by means of a laser range finder. The data is compared with the measured data of a high-quality item. Then, we examine the differences between two sets of data in order to detect defects in the target object. The three-dimensional distance data is matched with high robustness by using the proposed method. Furthermore, we attach labels to sets of points corresponding to a detected defect. By performing an experiment with real data, we show that a high-quality object and a defect object can be distinguished on the basis of the features of each label.