With an increasing trend of anti-social activities and terrorist attacks, there is a persistent demand for rapid and effective security screening systems, particularly in crowded public places such as in metros stations, airports, etc. Nowadays, terahertz (THz) based rapid scanners and cameras are employed as an alternative to the traditional X-ray baggage scanners due to the ability of THz waves to penetrate most nonmetallic materials and low ionizing radiation. Although such rapid THz line scanners and cameras are commercially available, the quality of the THz images acquired with these devices are very poor. This requires advanced image processing techniques to be employed for rapid threat object detection and identification. In this work, a sequence of image processing steps has been adopted which include (i) Weiner filtering, (ii) Lucy-Richardson deconvolution with the appropriate point-spread function, (iii) histogram based global thresholding of the image. This sequence of image processing operations has resulted in refined images thereby enabling rapid threat object detection and identification. This approach may be utilized as a preprocessing step before implementing sophisticated neural networks for automatic threat object detection and classification.

Advanced Image Processing for Rapid Threat Object Identification in Terahertz Images

Terahertz (THz) imaging is an attractive alternate to ultrasonic based Non-destructive Evaluation (NDE) especially for Fiber Reinforced Polymers (FRPs) such as Glass FRP (GFRP) composites as the latter demands proximity and additional coupling medium for the best performance. Typically, THz imaging system uses a single emitter-detector configuration employing raster scan method for image acquisition. The image acquisition speed is greatly limited by the speed of the mechanical stages and hence its usage in real-time industrial NDT applications such as in-line quality control has been limited. Alternatively, having an array of detectors will significantly increase the system cost. As an optimal compromise for speed and cost, line scanners are highly desirable. In this work, rapid imaging performance of a THz line scanner has been studied by imaging closely spaced defects in GFRP composites using a 100 GHz source. The total acquisition time for imaging the GFRP sample of dimensions 55× 35 mm2 is 10 s, which is >100 times faster compared to a conventional raster scanning technique. In addition, image deconvolution techniques such as Lucy Richardson and Weiner deconvolution have been adopted to improve the quality of the acquired THz images. The results show that the THz line scanners can successfully be employed for rapid defect detection in GFRP composites.

Supriyanka Rayapureddy

Papers

Rapid nondestructive evaluation of defects in GFRP composites using terahertz line scanner