The radiographic testing (RT) is a non-destructive testing (NDT) method capable of finding volumetric and open planar defects depending on their orientation. The radiographic contrast is higher for larger penetrated length of the defect in a component. Even though, the detectability of defects does not only depend on the contrast, but also on the noise, the defect area and the geometry of the defect. The currently applied Probability of Detection (POD) approach uses a detection threshold that is only based on a constant noise level or on a constant contrast threshold. This does not reflect accurately the results of evaluations by human observers. A new approach is introduced, using the widely applied POD evaluation and additionally a detection threshold depending on the lateral area and shape of the indication. This work shows the process of calculating the POD curves with simulated data by the modeling software aRTist and with artificial reference data of different defect types, such as ASTM E 476 EPS plates, flat bottom holes and notches. Additional experiments with different operators confirm that the depth of a defect, the lateral area and shape of its indication contribute with different weight to the detectability of the defect if evaluated by human operators on monitors.

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