A Pose Estimation Algorithm for Polyhedral Objects in X-Ray Image (特集 実環境におけるマシンビジョン適用技術)
In an x-ray vision, identifying the pose, i. e. the position and orientation of objects from x-ray projection images is extremely important to monitor in real time and analyze mechanical parts which are invisible from outside. It is assumed here that the x-ray imaging conditions that include the relative coordinates of the x-ray source and the image plane are predetermined and the object geometry is known. In this situation, an x-ray image of an object at a given pose can be estimated computationally by using a priori known x-ray projection image model. It is based on the assumption that a pose of an object can be determined uniquely to a given x-ray projection image. Thus, once we have the numerical model of x-ray imaging process, x-ray image of the known object at any pose could be estimated. Then, among these estimated images, the best matched image could be searched and found. When adequate features in the images are available instead of the image itself, the problem becomes easier and simpler. In this work, we propose an efficient pose estimation algorithm for polyhedral objects whose image features consist of corner points and edge lines in their projection images. Based on the corner points and lines found in the images, the best-matched pose of a polyhedral object can be determined. To achieve this, we proposed an adequate and efficient image processing algorithm to extract the features of objects in x-ray images. The performance of the algorithm is discussed in detail including the limitations of the method. To evaluate the performance of the proposed method a series of simulation studies is carried out for various imaging conditions.