Improvement in automated Aluminum Casting Inspection by Finding Correspondence of Potential Flaws in Multiple Radioscopic Images

摘要

This paper presents a new methodology for inspecting aluminum castings automatically using existing defect detection technologies which are combined with a new multiple view algorithm. In practice, casting defects are detected in individual radioscopic images using classic image processing methods without taking into account the useful information about the correspondence between the different views of the casting. These methods work as follows: 1) radioscopic images are taken at programmed positions of the casting being tested; 2) an error free reference image is estimated from each radioscopic image using modified median filters and a priori knowledge of the structure of the casting; and 3) flaws are detected when the pixels exhibit a significant difference between radioscopic and reference images. The threshold values of these methods are carefully optimized in order to minimize false detections while maximizing detection probability. However, by the reduction of false detections, real flaws may be also eliminated and the high quality of inspection may be compromised. In this paper, we address the above problems using a very efficient method, which is based on a two-step analysis: segmentation and correspondence finding. The first step segments potential casting defects in each radioscopic image using a classic method, namely the PXV 5000 developed by YXLON International X-Ray GmbH (successor to German Philips Industrial X-Ray and Danish Andrex). In this step the identification of real defects is ensured while the number of false detections is not considered. The second step attempts to find a correspondence between the segmented potential flaws from image to image. The key idea of this work is to consider as false detections those potential defects, which cannot be corresponded with any other one in the multiple images. The correspondence finding of potential defects in the images follows the principles of multiple view geometry, that is the position of real flaws in the radioscopic images must fulfill some geometric constraints. In order to reduce the computation times, new bifocal, trifocal and quadrifocal tensors, developed recently in the computer vision community, are used to find the correspondence between two, three and four views respectively. Additionally, a linear 3D reconstruction of the center of gravity of corresponding potential flaws is used to exclude impossible 3D points, which do not belong to the space occupied by the casting. The inspection throughput of the method has been verified on real radioscopic images recorded from cast aluminum wheels. Using this method the real defects can be detected with high probability and the false detections can be eliminated. The detection of the real flaws was successful in our labor experiments while the number of false detections were reduced to nil.