AUTOMATED DEFECTS RECOGNITION TECHNIQUE BASED ON MULTIPLE RADIOGRAPHIC IMAGES

Abstract

The current automated recognition of digital radio-graphic images is mostly carried out in individual images. Certain false detections exist because the threshold values of these methods are difficult to be optimized. To solve this problem, a new automated recognition methodology for digital radio-graphic images is put forward, which is based on a two-step analysis: Defects extraction and defects tracking. The first step segments potential defects in each radioscopic image using a classic method. 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 false detections as those potential defects, which can't be corresponded with any other one in the multiple images. The defects tracking 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. The inspection throughput of the method has been verified on real radioscopic images recorded from turbine blade. Using this method the real defects can be detected with high probability and the false detections can be eliminated.