In this chapter, segmentation techniques for terahertz (T-ray) computed tomographic (CT) imaging are described. A set of linear image fusion and novel wavelet scale correlation segmentation techniques is adopted to achieve material discrimination within a three-dimensional (3D) object. A case study is given where methods are applied to a T-ray CT image data set taken from a plastic vial containing a plastic tube. This setup simulates the imaging of a simple nested organic structure, which provides an indication of the potential for using T-ray CT imaging to achieve T-ray pulsed signal classification of heterogeneous layers. The wavelet-based fusion scheme enjoys the additional benefit that it does not require the calculation of a single threshold and there is a single parameter to adjust.
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