In an effort to reduce the amount of false alarms and improve screening times, one method that has been developed is using size cut-offs in the automatic explosive detection algorithms to lower the number of false alarms.
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X-Ray Automatic Detection Size Discrimination to Lower False Alarm Rates
1. X-Ray Automatic Detection Size Discrimination to Lower
False Alarm Rates
John Howell
Director of Explosive Technologies
DSA Detection
Security X-ray systems today have the ability to automatically detect potential explosive materials based on
looking at the density and effective atomic number. Potential explosive materials are typically identified by
placing a red box around anything that falls into the known ranges of explosives, as shown in Figure 1 below.
Figure 1: Automatic Detection (Red Box)
around 3 sticks of dynamite
One of the problems with the automatic explosive detection feature is that there are many non-explosive
materials that fall into the same windows as explosives. This creates false alarms that the operators must clear,
which in turn can take more time. Many studies have proven that the use of automatic detection greatly
increases detection rates for security screeners. Due to the false alarms, some people do not use the automatic
detection feature, because they do not understand how helpful and accurate the feature is when a real explosive
threat is presented to an X-ray operator. The below chart (Figure 2) displays the overlap between live explosives
and common false alarms in an X-ray detection density and average effective atomic number range.
Figure 2
2. False alarms are an inherent part of the screening process when using an X-ray system, but due to the large
number that can be encountered on single generator systems, people disable the automatic detection feature and
rely solely on operator image interpretation to detect an explosive threat. In any study that has been done,
automatic detection greatly enhances the X-ray operator’s ability to detect an explosive threat.
“In order to aid decision support, artificial colour may be used to highlight potential threats. McCarley,
(2009) has described the work of different types of performance aids on the baggage screening detection
task by varying the detection thresholds of these aids. They found that human performance was
dramatically improved with the use of an appropriate aid” [4].
In an effort to reduce the amount of false alarms and improve screening times, one method that has been
developed is using size cut offs in the automatic explosive detection algorithms to lower the number of false
alarms. The most common method is by looking at the explosive based on its size and determining that anything
under a certain size/range will not generate a red box alarm. In the Interagency Security Committees (ISC)
Design Basis Threat (DBT) guidelines, they list several different scenarios where an explosive device can be
encountered and even provide the net explosive weight (NEW). Figure 3 below is from the DBT guide and lists
the NEW at 1.1 pounds (2.3kg) based on the relative effectiveness factor (R/E) for black powder (.55) [1].
Figure 3
Using the ISC information and the NEW of 1 lb. (.45 kg) one could potentially estimate that a size cut off
could be developed based on that amount of explosives. This would be a mistake and could potentially be very
dangerous based on how powerful the explosives are and the damage they can do at amounts under 1 lb. The
human body begins to suffer critical to terminal injuries at around 275 kpa (40 psi) and death at 413 kpa (60
psi). A mail device opened by a person containing 1.1 lbs. of black powder would deliver 817 kpa (118.5 PSI)
in blast pressure. Even at ½ lb. (.22 kg) NEW, a person would suffer 449 kpa (65.12 psi) in blast pressure,
which is still above the lethal threshold. The blast pressure does not drop into a lower and less lethal range until
the NEW is dropped to ¼ lb. (.11 kg) which causes a blast pressure of 263.44 kpa (38 psi) (Zipf, R. K.). Blast
calculators can be used to calculate blast pressure [3].
Based on the above, it could potentially be theorized that ¼ pound of explosives would be an acceptable
range to implement a size cut off for X-ray automatic detection. The problem is that we are only basing this on
one explosive that has one of the lowest R/E factors and also has one of the lowest velocities of detonation
(VOD). If we were to look at a more powerful and energetic explosive, the ¼ lb. (.11 kg) theory does not work.
The below chart (Figure 4) breaks down the weight of the explosive and kpa/psi based on 1 lb., ½ lb., and ¼ lb.
NEW [2].
4. When looking at X-ray automatic detection algorithms, the weight of the explosive cannot be determined by
the unit. X-rays can only do size cuts offs for automatic detection based on the area that falls into the detection
windows. A one size fits all cut off when dealing with explosives cannot work because each explosive has a
different density.
An explosive that has a density of .88 g/cc will take up more area than an explosive that has a density of 1.59
g/cc. If we were to model the area based on 1 inch in height and ¼ pound, each explosive would take up the
following area in cm (Figure 5):
1. HTMD Density .88 g/cc .25 lb. area = 50.73 cm2
2. C-4 Density 1.59 g/cc .25 lb. area = 28.08 cm2
3. TSA 3.4oz Density 1.0 g/cc .25 lb. area = 34.00 cm2
Figure 5
5. Conclusion:
IED threats are the most difficult to detect in X-rays, but the automatic detection feature greatly
enhances your security staff’s ability to detect an explosive threat. Many studies have proven that of all
of the threats an X-ray operator is trying to locate in an X-ray image, the IED threat is the most difficult.
“However it was noted that both groups performed badly at detecting IEDs, even though the
trained observer’s eye dwelled on the threat, but invariably ignored it, underlining the need for
appropriate training on this, the most difficult of threats for detection. This was also supported
by other prior work (Wales et al., 2009), showing similar reductions when the detection task
becomes more challenging (i.e. baggage image complexity increases), with poorest performance
demonstrated for IEDs which do not exhibit such regular image-based features as other threat
objects such as guns and knives” (Wells, et. al.).
In an effort to lower false alarm rates and speed throughput, an option is to use size discrimination for
smaller size materials that have density and Zeff values in the range of explosives. The risks associated
with trying to use size discrimination cut offs in X-ray automatic detection algorithms far outweigh the
nuisance of false alarms. When you look at the density of the explosives and factor in the relative
effectiveness factor (R/E), the blast pressure even at 1 meter (3.2 feet) for most explosives exceeds the
lethal threshold for the human body even at ¼ pound NEW. When you shorten the distance to ½ meter
(1.6 feet) the blast pressure in all scenarios exceeds the lethal threshold. Until such time that X-rays can
better differentiate between explosive and non-explosive alarms, security staff must be trained on how to
clear false alarms. IED threats are the most difficult to detect in X-rays, and the use of the automatic
detection feature greatly enhances your security staff’s ability to detect an explosive threat.
References:
[1] Keil, Todd, comp. "The Design-Basis Threat (U): An Interagency Security Committee Report."
(2010): n. pag. 12 Apr. 2010. Web. <https://info.publicintelligence.net/DHS-
DesignBasisThreat.pdf>.
[2] "Relative Effectiveness Factor." N.p., 22 Dec. 2016. Web. 18 Jan. 2017.
<https://en.wikipedia.org/wiki/Relative_effectiveness_factor>.
[3] "UN SaferGuard - Kingery Bulmash Blast Parameter Calculator." United Nations. United
Nations, n.d. Web. 18 Jan. 2017. <https://www.un.org/disarmament/un-saferguard/kingery-
bulmash/>.
[4] Wells, K., and D. A. Bradley. "A review of X-ray explosives detection techniques for checked
baggage." Applied Radiation and Isotopes 70.8 (2012): 1729-1746.
<https://core.ac.uk/download/pdf/17180209.pdf>.
[5] Zipf, R. K., and Kenneth J. Cashdollar. Explosions and Refuge Chambers. Rep. Centers for
Disease Control and Prevention (U.S. Government), n.d. Web.
<https://www.cdc.gov/niosh/docket/archive/pdfs/NIOSH-125/125-
ExplosionsandRefugeChambers.pdf>.