LabVIEW Helps Secure Airports by Facilitating On-Belt Tomosynthesis Baggage Screening

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"We chose LabVIEW because it has a proven record of worthy applications and is a fast and intuitive programming environment with wide-spread built-in functions and capabilities. LabVIEW’s aptitudes, together with the support offered by NI engineers, made the graphical programming environment an excellent choice."

- Selina Kolokytha, University College London

The Challenge:
Creating a cost-effective check-in baggage screening system designed to address the limitations of the most common method of baggage screening today, which is conventional projection radiography. These limitations can lead to loss of information and an increase in baggage-handling time, as baggage is manually searched or screened with less-advanced systems.

The Solution:
Developing a LabVIEW application to link between 12 X-ray strip detectors and control them using .NET functions to collect the required data. LabVIEW image processing functions, known as NI-IMAQ functions process the data to create and display an X-ray projection image of the baggage item corresponding to each detector.

Selina Kolokytha - University College London

Project Background

We developed the ObT baggage screening system as part of a PhD project, “Three-Dimensional Imaging of Baggage for Security Applications,” at the Department of Security and Crime Science, University College London. The department is funded by the UK Home Office and the Engineering and Physical Sciences Research Council.

Tomosynthesis is the construction of pseudo-3D images, created from a restricted number of 2D X-ray projection images, which are acquired at a range of different orientations around a static object. These 2D projections are appropriately pieced together using image-reconstruction algorithms to create a pseudo-3D image of the object. Figure 1 illustrates the basic principles of tomosynthesis. This figure shows how, by taking projections of an object from different angles and using appropriate image-reconstruction algorithms (in this case, a simplistic one named “shift-and-add”), we can distinguish details (circle and triangle objects) inside the object and bring them into focus.


Figure 1. The principle of shift-and-add tomosynthesis. (a) The three X-ray tube positions and the projected locations of a circle in Plane A and a triangle in Plane B. (b) We can bring the structures in either Plane A or Plane B into focus by shifting the projection images appropriately and superimposing them. Structures outside the plane of focus are then spread across the image (blurred).

The ObT System

The ObT project led to the creation of a cost-effective check-in baggage screening system while overcoming the limitations of current technologies, creating a fully automated pseudo-3D imaging system by combining X-ray imaging and close-range photogrammetry to form digital tomograms. In the ObT system, instead of moving the source and detectors around the object, as in conventional computed tomography, bag movement around bends in the baggage transport system provides the required relative motion between the source, object, and a fan configuration of strip detectors. In total, the system uses 12 strip detectors, each group of six placed around a 90-degree conveyor-belt bend and illuminated by one X-ray source, as seen in Figure 2.


Figure 2. 2D top view of the ObT system. Main components: Two X-ray sources (S1, S2) and the 12 strip detectors placed around the conveyor belt bends.


The 12 strip detectors connect to one central detector control box, as seen in Figure 3.


Figure 3. ObT Detectors and Detector Control Box Connections


The detector control box is able to collect data corresponding to the x-ray image projection of the baggage item on the detector strip.  This is done by first converting X-rays to light using a scintillator and then detecting the light using an array of light-sensitive pixels on each detector. The data is transmitted from the control box to the computer as a single stream of information through an Ethernet connection, as seen in Figure 4.


Figure 4. Computer Connected to the Detector Control Box via Ethernet Cable


To acquire the required X-ray images, the detectors need to operate using the appropriate DLLs provided by the detectors’ manufacturer. These DLLs were written and compiled in .NET languages, which is why LabVIEW was particularly useful. 


 Figures 5 and 6. Physical ObT System Setup Showing Conveyor Belts, X-Ray Strip Detectors, and X-Ray Sources


Image Acquisition

An X-ray image of the object is projected on each detector as it moves along the conveyor belt system. This data needs to be collected and displayed as 12 consecutive 2D projection images. Because the detector cluster is wired to the control box, which transmits the acquired data as a continuous string to the computer, software needs to establish a connection to the control box, collect the data, and appropriately decluster the data corresponding to each detector. To connect to the detectors’ control box, we used a series of LabVIEW Call Library Function Nodes. This way, the system can call the manufacturer’s DLL files and connect to the control box. Having set the required parameters for an acquisition, the retrieved data is logically converted into 12 images using existing LabVIEW NI-IMAQ subVIs (virtual instruments (VIs) used in the block diagram of another VI). These correspond to 2D X-ray images of the object projection on each detector for the duration of each acquisition. NI-IMAQ is an existing library of LabVIEW VIs for developing machine vision and scientific imaging applications. We used three NI-IMAQ functions in our code to create a temporary memory location for the images, construct the required images from the 2D array of data collected from the detectors, and write the images to a file in the selected format.


Photogrammetry, as camera 3D measurement technology, uses central projection imaging as its fundamental mathematical model. A low-cost photogrammetry system, using off the shelf web-cameras, has been developed for the accurate determination of object spatial location. For moving objects, the system has displayed sub millimetre accuracy.  The shape and position of an object can be computed by reconstructing image rays corresponding to specific points on an object. Given that the location of the imaging system in object space, as well as the internal imaging geometry of the camera, are known, every image ray can be defined in 3D object space. An object is, therefore, defined in 3D object space by intersecting two or more corresponding, spatially separated image rays.

Why LabVIEW?

We chose LabVIEW to build the required software for many reasons, especially because it has a proven record of worthy applications and is a fast and intuitive programming environment with wide-spread built-in functions and capabilities. Also, LabVIEW effectively integrates with third-party tools, such as DLLs, which was vital in our case. The final important factor was the proven track record of timely and helpful assistance by the NI community and staff. LabVIEW’s aptitudes, together with the support offered by NI engineers, made the graphical programming environment an excellent choice.

Key Benefits of the On-Belt Tomosynthesis System

Our system is substantially less costly than alternative 3D X-ray imaging systems, such as computed tomography scanners. It also offers:

  • Advanced imaging results with higher object discrimination and more information in images.
  • Preflight operation time optimisation due to decreased baggage handling time, as less baggage will be required to be screened with alternative 3D methods.
  • Able to retrofit on existing conveyor belt systems in virtually any airport.

Author Information:
Selina Kolokytha
University College London
Gower Street
London WC1E 6BT
United Kingdom

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