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A digital radiography (DR) image is essentially a projected image image of the inspected object. In most cases, the contrast of defects in the inspected object is too low to distinguish easily. Therefore, for X-ray inspection of castings, especially large-scale castings, it is difficult to detect defects in the casting's X-ray images in real time. In this paper, a rapid DR image defect detection method, based on image registration, is proposed using the casting's online DR detection characteristics. Firstly, the DR image of the inspected casting is enhanced using a fusion method to highlight defects. Secondly, the appropriate standard DR image is selected from a library according to a model of the inspected casting. Thirdly, the enhanced DR image and selected standard DR image are registered. Lastly, the difference image method and prior knowledge are used to detect defects in the casting. Experimental results show that the proposed method can effectively detect casting defects at high speed. The method is particularly suitable for the online X-ray inspection of large castings. [ABSTRACT FROM AUTHOR]

X-ray testing of complex objects - such as luggage screening at airports - is usually performed manually. This is not always effective, since it depends strongly on the pose of the objects of interest (target objects) and occlusion, as well as human capabilities. Additionally, certain target objects are difficult to detect using only one viewpoint. For this reason, we have developed an active X-ray testing framework that is able to find an adequate viewpoint of the target object in order to obtain better X-ray images to analyse. The key idea of our method is to adapt automatically the viewpoint of the X-ray images in order to project the target object in poses where the detection performance should be higher. Thus, the detection inside complex objects can be performed in a more effective way. Using a robotic arm and a semi- automatic manipulator system, the robustness and reliability of the method have been verified in the automated detection of razor blades located inside nine different objects, showing promising preliminary results: in 130 experiments we were able to detect the razor blade 115 times with 10 false alarms, achieving a recall of 89% and a precision of 92%. [ABSTRACT FROM AUTHOR]

We report a new procedure for the accurate estimation of the density of a vibro-compacted boron carbide (B4C) capsule using digital X-ray radiography combined with suitable beam pre-hardening filters. Under identical radiography exposure conditions, the grey values of both the boron carbide capsule and a standard stainless steel (SS) step-wedge are compared and the variation of density along the length of the capsule is evaluated. Without filters, due to the continuous X-ray spectrum, the absorption of mass thickness is influenced by soft X-rays and characteristic peak energy. Compared to the results obtained without filters, a 6% improvement in the density measurements is achieved with SS and brass filters in B4C. To validate the procedure, density estimation was carried out in a pellet of TiO2 with known density. For the TiO2 pellet, the average densities estimated without filter and with filter were 3.93 g/cm3 and 4.13 g/cm3, respectively, against the actual value of 4.20 g/cm3 measured by gas pycnometry. The beam hardening correction led to a 5% improvement in the density estimation due to flattening of the X-ray spectrum by the filters. [ABSTRACT FROM AUTHOR]

In this paper, the X-ray non-destructive testing method for the detection of small defects in laser weldments of titanium alloy with complex structure is presented. To resolve the difficulty of segmentation of small defects in a variable grey-grade image with low contrast and to improve the processing effects and speed, the methods of image processing based on wavelet transformation and morphology filtering were adopted. After the superimposition de-noising was adopted to remove the impulse noises, wavelet transformation was used to eliminate the residual noise for better resolution in both time domain and frequency domain. At the same time, one-dimensional morphology filtering was carried out to simulate the background, and the small defects in a variable grey-grade image with low contrast can be segmented. The experimental results show that the method can not only extract the small defects in a variable grey-grade image with low contrast, but can also improve the image processing speed, and the morphology of small defects can also be retained. This will provide a good basis for the quantitative research concerned with detecting small defects in variable grey-grade images with low contrast. [ABSTRACT FROM AUTHOR]

The preservation of human achievements and progress is undoubtedly a pillar of our society. This includes detecting threats in time to prevent disasters that may occur from forces of nature, defective technology, human failure or malicious intent. In this respect, there is arguably no difference between safety and security, though different institutions are involved in the regulation and control of them. However, the unifying rationale ought to result in the building of bridges between them. This is the Working Group's mission. [ABSTRACT FROM AUTHOR]