Abstract:
A method of detecting a presence or absence of subject matter of interest, for example, sheet explosives and/or other potential threat objects is provided by various local and/or global gradient analysis methods including determining characteristics of gradient information of regions in an X-ray image to determine if the regions are associated with subject matter of interest for which detection may be desired, for example, contraband, explosives and/or other prohibited or unauthorized material.
Abstract:
A method of detecting a presence or absence of subject matter of interest, for example, sheet explosives and/or other potential threat objects is provided by various local and/or global gradient analysis methods including determining characteristics of gradient information of regions in an X-ray image to determine if the regions are associated with subject matter of interest for which detection may be desired, for example, contraband, explosives and/or other prohibited or unauthorized material.
Abstract:
A method for inspecting a component of a gas turbine engine or the like having a plurality of similarly shaped structural portions, such as the gear teeth of a gear, the dovetail slots of a turbine disk or the like, includes the steps of: scanning a surface of at least one of the similarly shaped structural portions with an eddy current probe to induce eddy currents in the component; generating a two-dimensional image of the at least one portion from eddy current signals received during scanning, the image including a multiplicity of pixels arranged in a two-dimensional array and each pixel having a gray scale intensity responsive to the eddy current induced in the component at a component location corresponding to a position of the pixel in the matrix array; preprocessing the image to substantially reduce any signals or changes in the gray scale intensity of any pixels relative to the background pixel intensities of the image caused by geometrical characteristics and background noise common to all similarly shaped structuaral portions; identifying any suspected defect regions from the preprocessed image; determining a defect signal for each suspected defect region; and rejecting the component if any defect signal exceeds a predetermined reference value.