WO2011082490A1

WO2011082490A1 - Method and apparatus for performing a security scan

Info

Publication number: WO2011082490A1
Application number: PCT/CA2011/000024
Authority: WO
Inventors: Dan Gudmundson
Original assignee: Optosecurity Inc
Current assignee: Vanderlande APC Inc
Priority date: 2010-01-07
Filing date: 2011-01-07
Publication date: 2011-07-14
Anticipated expiration: 2012-07-07

Abstract

A method for performing a security screening at security checkpoint on an individual. The method includes subjecting the individual to a scan from a source producing electromagnetic radiation to generate scan data and processing the scan data with software executed on a CPU to determine of the scan data contains a signature of a threatening object.

Description

TITLE: Method and apparatus for performing a security scan

FIELD OF THE INVENTION

The invention relates to techniques for determining if a clothed individual presents a security threat. The invention can be used for determining topographic information about the person' s body, in particular it can be used to render an image of the person' s body on a display monitor for use in determining whether the person carries concealed weapons, explosives or contraband material.

BACKGROUND

Body scanners are used at airports or other security checkpoints to determine if clothed individuals present a security threat. A body scanner operates by interrogating the subject with electromagnetic radiation that easily penetrates clothing but is reflected by the skin. In this fashion, it is possible to create an image of the subject in a virtually "unclothed" state likely to reveal potential threats, such as weapons, explosives or contraband material.

Body scanners are very useful because they can perform a security scan relatively rapidly, in a fully automated fashion. Most importantly, they replace the more traditional "pat-down" search that requires a security agent to physically touch the person to check for threats concealed under the clothing. In addition to its lack of effectiveness, the "pat-down" search is also objectionable since it can be very uncomfortable for the subject.

However, the body scanners that are currently in use have limitations. Although the actual scanning operation required to gather body image data and to render the image are automated, the threat assessment operation is not. The threat assessment requires a security agent to examine the image and determine if the subject presents a security threat. The requirement to manually review the image for every subject reduces the system throughput and is also objectionable for privacy concerns.

Therefore there is a need in the industry to provide an improved methodology and devices for determining if a clothed individual presents a security threat.

SUMMARY OF THE INVENTION

As embodied and broadly described herein the invention provides a method for performing a security screening at security checkpoint on an individual, comprising :

a. subjecting the individual to a scan from a source producing electromagnetic radiation to generate scan data;

b. processing the scan data with software executed on a CPU to determine of the scan data contains a signature of a threatening obj ect .

As embodied and broadly described herein the invention further provides a system for performing a security screening at security checkpoint on an individual, said system comprising:

c. a full body scanning device for subjecting the individual to a scan from a source producing electromagnetic radiation to generate scan data; d. a processor including a machine readable storage encoded with software for execution by a CPU for processing the scan data to determine if the scan data contains a signature of a threatening object.

BRIEF DESCRIPTION OF THE DRAWINGS

A detailed description of examples of implementation of the present invention is provided hereinbelow with reference to the following drawings, in which:

Figure 1 is a flowchart describing a method for performing security screening according to a non-limiting example of implementation of the present invention;

Figure 2 is of a block diagram of system for performing a security screening that implements the method shown in Figure 2 ;

Figure 3 is an example of an image of a virtually unclothed body rendered on a monitor and generated by a full body scanner that uses millimeter wave electromagnetic radiation;

Figure 4 is a perspective view of a scanner using millimeter wave electromagnetic radiation;

Figure 5 is an example of a virtually unclothed body rendered on a monitor and generated by a full body scanner using X-ray backscattering;

Figure 6 is yet another example of an image of a virtually unclothed body rendered on a monitor and generated by a full body scanner that uses millimeter wave electromagnetic radiation;

Figure 7 is a depiction of a user interface that communicates to a user the results of the automated threat processing based on the image shown in Figure 6;

Figure 8 is a block diagram of the system for performing a security scan, according to a variant; and

Figure 9 is a flow chart illustrating a process for scanning a body by using different spectral sources

In the drawings, embodiments of the invention are illustrated by way of example. It is to be expressly understood that the description and drawings are only for purposes of illustration and as an aid to understanding, and are not intended to be a definition of the limits of the invention.

DETAILED DESCRIPTION

Figure 1 is a flowchart of a method used for performing a security screening operation. The security screening operation can be carried out at a security checkpoint at an airport or any other suitable location.

The method is performed on a clothed individual and aims to determine if the individual hides under his or her clothes any potential threats such as concealed weapons, explosives or contraband material.

At step 10, image data from the clothed subject is collected. Different image data sources can be used. One example is to use image data generated by a full body scanner of the type shown in Figure 4 that uses electromagnetic radiation to irradiate the subject in the frequency range of about 200 MHz to about 1 THz. At this frequency range, the electromagnetic radiation tends to easily penetrate clothing but is reflected by the skin. An example of the operation of a full body scanner of this type can be found in the US patent 6, 507, 309 the contents of which are incorporated herein by reference.

Another example of image data source is an X-ray machine that uses more penetrating radiation. A specific example is a full body scanner X-ray apparatus using X-ray backscattering to generate a virtually unclothed image of the body. An example of such image rendered on a monitor is shown in Figure 5.

Yet another example of image data source is a visible light camera which uses visible light with little or no clothes penetrating capabilities to produce an image of the person being scanned. In the specific example of implementation described herein, this image source is used in conjunction with a full body scanner.

Yet another example of image data source is an infrared camera which senses temperature patterns over the body of the subject. This type of image data source can also be used in conjunction with a full body scanner.

The process at step 10 therefore includes the gathering of digital information which is produced by one or more of the selected image sources. Preferably, the gathering of digital information includes the storage of that data on a storage device such that the data can subsequently processed with software.

At step 12, surface features of the subject are being extracted from the image data. The extraction process is software implemented and includes processing of the image data to produce a virtual representation of the human body or portions thereof. When the image data source used to perform the scan relies on millimeter wave electromagnetic radiation the source of the topology information that is conveyed by the image data is obtained from the reflections of the electromagnetic radiation. More specifically, the interrogation source produces electromagnetic radiation that easily penetrates the clothing but is reflected back by the skin. By successively sending bursts of the electromagnetic radiation and measuring the time of flight of the reflections, it is possible to generate a three dimensional map of the body surface.

Step 12 also includes the combination of the extracted surface features into a complete virtual model of the human body. Optionally, as illustrated by the dotted line, the complete virtual body model is displayed on a monitor, at step 14. An example of such rendering is shown in Figure 3. The image illustrates two views of the same body, one being from the front and one from the back. The rendering of the surface features appears to the eye as a removal of the outer clothes layer, leaving exposed skin and body features.

At step 16, the extracted surface features are processes by software to automatically determine the presence of any security threats, such as concealed weapons, explosives or contraband material. The processing will be described in greater detail later.

At step 18 the result of the automatic threat assessment operation is released. If no security threat is determined to exist, then the passenger is released through the checkpoint, as shown at step 20. Otherwise, when a potential security threat is identified, the subject is subjected to a secondary screening operation 24 to more clearly establish his/her security status. The secondary screening operation 24 may involve another automated screening by a different method or a manual screening such as by the "pat-down" method. The outputting of the automatic threat assessment may be made by generating a signal, visually, audibly or both that conveys the results of the processing. Optionally, as shown by the dotted line, the outputting of the results may also include the generation on the monitor of an image that indicates the existence of possible security threats and the location of those threats on the human body. An example of image that would be rendered on the monitor is shown in Figure 7. The image provides a rendering of the body features assembled in a complete image and also shows locations of anomalies indicative of possible security threats. The anomalies shown in the image are highlighted as at 22. Any suitable highlighting method can be used such as adding color to the anomalies, overlaying highly visible geometric figures (such as the circles shown in the drawing) or any other suitable image treatment technique .

Figure 2 is a block diagram of an automated threat detection system that implements the method discussed earlier. The detection system uses a computer based platform to perform the various steps of the data processing necessary to perform the threat assessment. Software executed on the computer based platform implements the various functions discussed below. A machine readable storage (not shown) is encoded with the software which is executed by a CPU (not shown) of the computer platform. As a possible alternative, the software can be replaced wholly or in part by dedicated hardware.

Figure 2 describes the detection system 30 by functional blocks which reflect the software architecture and also describe some hardware components that are used by the software to perform the detection function.

The detection system 30 includes a general input that receives image data. The image data originates from one or more image sources. The image sources 32 are shown collectively at 32. An example of an image source is the millimeter wave full body scanner shown in Figure 4. Another example is a full body scanner that uses X-rays. Alternatively or in addition to those image sources, other image sources can also be used such as a visible image camera or an infrared camera.

The image data from a single image source or from multiple image sources is conveyed over a communication link 34 that can be wire line or wireless. The image data is received by a surface features builder module which is software implemented. The surface features builder receives a multitude of data points in the image data stream which represent topographic information of different points of the body surface. The surface features builder 36 will then combine those data points in a continuous map that provides a three-dimensional representation of the skin surface. Optionally, the surface features builder module 36 has an output to produce an image signal that is directed to a monitor 40. The image that would be produced is similar to the one shown in Figures 3 and 6. For image data derived from a full body scanner using X-rays, the image such as the one in Figure 5 would appear.

The three dimensional representation of the skin surface that is produced by the surface features builder 36 is directed to a threat assessment processor 42. The treat assessment processor 42 is also software implemented but other forms of implementation are also possible without departing from the spirit of the invention. The threat assessment processor 42 comprises two main modules, namely a an anomalies detector 46 and an anomalies processor 48. Optionally, the anomalies detector 46 may use information stored in a database 50.

In one possible form of implementation, the anomalies detector 46 produces reference topology information against which surface features extracted from the real image data are compared to determine if a security threat exists. More generally, the anomalies detector 46 predicts on the basis of contextual information what the image of the person that is being scanned should look like. If the real virtually "unclothed" image generally matches that reference, the system infers that no security threats exist. However, if the real image shows features under the clothing that are not expected to be there, those features may be indicative of a security threat such as a concealed weapon or explosive. The contextual information on the basis of which the anomalies detector 46 produces the reference topology information can be derived from different sources. One source is the three dimensional information of the skin surface (topology information) derived from the full body scanner. In such case, the real topology information can be analyzed to extract a number of parameters that can be used to generate the reference topology information. For instance, the real topology information can be analyzed to extract (1) dimension information such as the height of the person, its shoulder size, its waist size, crotch height and thigh size and (2) the sex by determining if bulges are present in the chest area in the image. On the basis of those parameters a standardized body outline can be generated and used for building the reference topology. In one possible example of implementation, the parameters extracted from the real topology information are communicated to a database that maps parameters with corresponding body outlines. In this example, the output of the database is reference topology information providing a general indication of what the image of person having those parameters should look like. Therefore, the reference topology information provides a basis against which the real topology information can be compared to determine the presence of anomalies indicating possible security threats.

Instead of using a database it is possible to modify electronically a basic image of an individual such as to customize it on the basis of the extracted parameters. For instance the image can be resized according to the height dimension and width dimension. Individual body parts can be altered or removed depending on the values of the parameters. In the case of a large waist size, which would indicate an obese person, the basic image is modified to grow the waist portion as per the waist dimensions. Breasts can be adjusted to size or removed from the image if none is seen in the real topology information, which indicates that the person is likely a male. The length of the legs can be adjusted depending on the crotch dimension observed. The size of the shoulders can also be varied according to the real dimension of the shoulders. Limbs can be removed in the case of amputees. Accordingly, this process produces a customized version of the basic image, adapted to match the outline of the person that is being scanned.

Another possible source of context information is the image of the subject produced by a scan using a different spectral source such as a visible light camera. The visible light information picks up information on clothing features that are unlikely to be fully visible in the real topology information generated as a result of the scan. For example the visible light camera can convey the location on large shirt or coat buttons, belt buckles or other features that may be large enough or made of denser material such that they will continue to show to at least some extent in the real topology information. It other words they will not be fully erased. This contextual knowledge can then be used to further customize the reference topology, by integrating them to the topology to avoid that they appear as anomalies suggesting a security threat. The integration process may involve extracting the signature of those objects in the real topology information and copying it in the corresponding location on the reference topology.

Yet another source of context information is an X-ray scan or an infrared camera that senses temperature patterns over the body of the person being scanned. The temperature patterns may indicate hot or cold spots that may suggest the presence of material covering the skin. For example a thin layer of foil covering an area of the body is not likely to have the same temperature as the remainder of the skin surface. The layer of foil will be picked up by the infrared camera on the basis of the temperature difference.

More generally, as described by the flowchart in Figure 9, different spectral scans can be used to generate specific contextual information which is then processed to identify "features of interest". The process, which is performed by the anomalies detector 46 uses two separate processing paths which eventually merge to combine information from different sources. More specifically, the process starts at 900 and branches to two processing steps 902 and 904, the step 902 including performing a scan with a first spectral source while the step 904 includes performing a scan with a second spectral source. Each spectral source can be selected in the group consisting of electromagnetic radiation in the frequency range of about 200 MHz to about 1 THz, an infrared source, a visible source or an X-ray source, such as X- backscattering . The first spectral source is different from the second spectral source. For instance the first spectral source scan 902 can use electromagnetic radiation in the frequency range of about 200 MHz to about 1 THz while the second spectral source scan 904 can use visible light . step 906 the information generated by the scans 902 and 904 is jointly processed. In this fashion, the topology information can be augmented to include features of the scanned body which are observed as a result of one scan but can not be seen in the other. Specifically, the reference topology information can be augmented to include features of the scanned body that is unclothed (by using electromagnetic radiation in the frequency range of about 200 MHz to about 1 THz) and also include clothing features, not seen by the electromagnetic radiation in the frequency range of about 200 MHz to about 1 THz, but seen with a visible source scan, such as a video camera.

The processing at step 906 includes processing each scan information separately to identify features of interest. What constitutes a "feature of interest" is built into the software logic performing the image analysis. The features of interest that are being searched are likely to be different from one source of electromagnetic radiation to another. In the case of electromagnetic radiation in the frequency range of about 200 MHz to about 1 THz, which reveals features under the clothes, examples of features of interest are:

. Pixel formations indicating the presence of a mass where no such mass is expected to exist on a normal human body. For instance, the system may be designed to search for such pixel formations at areas of the human body where a threatening object is likely to be hidden, such as the crotch portion, underarms, the belt and feet (the shoes) . If a pixel formation is identified which is of a shape and/or size that is not expected in a normal human body it is classified by the processing as a "feature of interest".

2. Geometric shapes that do not occur normally in a human body. The system may search for certain atypical shapes or shape fragments suggesting an extraneous object. The human body normally has a gently curvilinear outline and any sharp edged objects or objects having an outline that made up of segments that are straight or of certain geometric form, such as circles, triangles, rectangles, etc are considered suspect and classified as "features of interest".

In the case of a visible source examples of features interest are:

1. Clothing features which may register in some confusing way on a scan performed with another source. Examples include jewelry, such a large necklace, watches, heavy bracelets, large belt buckles, heavy shoes or shoe features (large buckles or straps), or heavy clothing that may not be fully erased by the millimeter wave scan. Examples of heavy clothing include bulky pants, such as cargo pants and heavy sweaters or clothing with certain decorative features such as chains or buckles that the millimeter wave scan is unlikely to erase.

2. Distinguishing external body features, such as a large abdomen in the case of an overweight person or any other oversized body part. In this instance, it would be possible to co-relate the presence of the large body part into the other spectral scan (such as the scan using electromagnetic radiation in the frequency range of about 200 MHz to about 1 THz) . If they do not match, in other words, no large body part shows where the first scan finds one, this suggest the presence of some padding material on the body that would require some further investigation .

3. The general outline of the clothed individual may be in itself a "feature of interest" since it can be matched against the image of the unclothed body obtained by a different scan to show if both match. If there is a significant disparity between the scans, that disparity may suggest the presence of extraneous material on the body suggesting further investigation.

In the case of an infrared source examples of features of interest are:

Cold or hot spots on the person body that can be used to confirm the presence of certain objects (such as jewelry or a watch) that appear on another spectral scan such as to confirm what they are, namely normal objects unlikely to be threatening. The cold or hot spot information can be used also to identify the presence of hidden objects on the body by showing abnormal temperature patterns in areas of the body where no such pattern should normally be present. For instance if the infrared scan shows an area that is relatively colder in the tighs or legs of the person being scanned, that lower temperature area may suggest the presence of an extraneous ob ect .

In the case of an X-ray source an example of features of interest is and X-ray absorption patterns showing high density objects on the person that are likely to be extraneous objects.

The processing of the data generated by the scans at steps 902 and 904 at step 906 includes the extraction from each scan identification of the features of interest and also generating for each feature of interest location data to specify where that feature of interest is. In this fashion, it is possible to co-relate the features of interest from different scans by determining if the location data matches. The identification of the features of interest is made by performing an image analysis. In the case of the millimeter wave scan, known image analysis techniques are used to identify the pixel formations which are atypical. For instance a bulge having a surface area above a certain threshold and located along one of the arms or legs is considered as a "feature of interest". Also, certain edge shapes or edge patterns in the image that are atypical for an unclothed human body are classified as "features of interest". Those edge or edge patterns are also identified in the image by performing image processing with known algorithms.

Similar techniques are used for identifying the features of interest in the scans using different spectral sources .

In the previously described example of implementation of the invention the person is subjected to two scans by different spectral sources. In a possible variant, more than two scans can be used, such as three or four scans, with the data generated from each scan being subjected to the same or similar processing, namely identification of features of interest and location data to specify at what location on the body that feature of interest is found.

The multiple scans are preferably performed in parallel, but they can also be performed in sequence. In this fashion one scan is run and when this scan completes another scan is triggered and so on. A possible drawback to this approach is that the person may not stay fully stationary during the multi-scan operation with the consequence that the position of the body being scanned may shift from one scan to another. However, if the scans are performed relatively rapidly position shifts can be reduced to a minimum.

Yet another possibility is to run a first scan, say using electromagnetic radiation in the frequency range of about 200 MHz to about 1 Hz, perform some degree of image processing to determine if features of interest exist in the image and in the affirmative trigger one or more subsequent scans. The subsequent scans can be scans of the full body or scans of only parts of the body in which the features of interest have been identified. In this case the location data generated by the first scan which specifies the location of the features of interest drives the subsequent scans. The location data is used by the scanning devices to obtain images of the areas of interest of the body.

Therefore, the output of the anomalies detector 46 is features of interest data that specifies:

1. whether features of interest have been identified during the scanning operation (one spectral source or several different spectral sources) ;

2. if features of interest have been identified, any characterization information of the features of interest such as location information, size such as surface area, location on the body (close to arms, legs, etc) , temperature (for infrared scans) among others. In general for each scan the features of interest and their characteristics are reported separately for further analysis by the anomalies processor.

The anomalies detector 48 receives and examines the features of interest data to determine its relevance in terms of potential security treat. The logic for determining if a feature of interest is an "anomaly" in the sense of being a security threat relies on rules, such as :

1. The shape and dimension data for a certain feature of interest can be used to compute volume information which can be a trigger as to what is considered to be a security threat or not. For example, anomalies having a volume beyond a certain threshold can be considered to be likely security threats and are treated as such. Volumes below the threshold are dismissed;

Factors such as the location of the feature of interest with relation to the body of the person can also be used as indicators to determine the likelihood of the security threat. For example, a large feature of interest on the leg is likely to be a security threat since leg shapes in the general population do not vary much from one another.

Co-relation between features of interest obtained from different spectral scans. If features of interest exist in two or more of the scans, the anomalies processor 48 will first determine if the locations of the features of interest match. If they do, this means that the features of interest observed in two or more different scans relate to the same object or thing. Accordingly, the information about the features of interest seen several scans are accretive, in other words they can be combined to better assess if the feature of interest is threatening or non-threatening. For example, if a feature of interest in the scan made with a visible source shows a large belt buckle, which is identified as such by image processing techniques, the residual signature of the belt buckle that may still be observed in the millimeter wave scan now considered to be unlikely a threat since it is much more likely a belt buckle. In this case the co-relation between multiple features of interest negates false positives.

The topographic anomalies processor 48 may also perform a shape recognition search, depicted by the bloc diagram in Figure 8 to try identifying features of interest on the basis of the shape of the feature of interest as seen in the image. That image processing can be run on images produced by the millimeter wave scan or scans from other spectral sources. Examples of objects that can be identified as threatening on the basis of their shape include guns or stabbing objects that have very characteristic shapes. The topographic anomalies processor 46 essentially performs an image analysis to determine if anyone of those characteristic shapes exists in the image. The image analysis can be driven on the basis of the location data generated earlier that specifies the location of the features of interest. Alternatively, the image processing can be made in the entire image. A reference image database 46a stores characteristic shape information for a variety of possible threatening objects. The anomalies processor 46 will extract from the database 46a the various shapes and process the image to determine the likelihood of presence of this shape on the person being scanned. Note that the database 46a stores characteristic shapes information identifying the shapes from different perspectives. For example, in the case of a hand gun, the database 46a will generate data that shows how the handgun looks like from different angles, namely from the side, from the bottom, from the top or any other intermediate position.

The anomalies processor 46 generates at output 52 a signal which indicates the presence or the absence of anomalies indicative of a security threat. In the instance no security threat is found to exist, the person may be allowed to proceed beyond the security checkpoint, otherwise the person may be subjected to an additional screening such as a manual "pad down" search.

Optionally, the anomalies detector does not implement any reference topology building In this instance, the anomalies detector 46 is designed to process only the real topography information from the millimeter scan wave and/or scan information from other spectral sources. In this case the processing would not involve any comparison between a reference (what is expected) and what is observed in the image (s). The processing is an image analysis to locate the presence or absence of image features that are either expected to be found in the image or not expected to be found. An example of a feature expected to be found is the crotch portion; consider the topography rendering the back of the person in Figure 3. The crotch 60 can be clearly seen. The crotch 60 is expected to be there and if it is not present in the image, it may indicate that a layer of some material obscuring the crotch is placed in the underwear of the person being scanned.

In the case of extraneous items, that should not be there, consider the image at Figure 6 which shows several anomalies appearing as bulges at several locations along the legs and tights of the person. The bulges 62 are of a shape and size that is unlikely to be a normal component of the human body, hence they are classified as anomalies indicative of a security threat.

The image processing is performed by using known image deconstruction and feature extraction techniques to identify the presence of anomalies or elements that are required (a missing element is considered as an anomaly in the image) .

The image information is generated from the threat assessment processor 42 which is directed to the monitor 40 to render the topography and also highlight the location of the anomalies. The example of a display is shown in Figure 7. The display shows an image of the body of the person being scanned and highlights the areas in which potentially threatening objects exist. The highlighting effect can be obtained by placing in the image a symbol such as a circle or arrow to visually draw the attention of the operator, by changing the color of image locally or by blurring the image around the feature of interest in order to make it more visually prominent.

Although various embodiments have been illustrated, this was for the purpose of describing, but not limiting, the invention. Various modifications will become apparent to those skilled in the art and are within the scope of this invention, which is defined more particularly by the attached claims.

Claims

CLAIMS:

A method for performing a security screening at security checkpoint on an individual, comprising:

A method for performing a security screening as defined in claim 1, wherein the processing includes identifying in the scan data features of interest indicative of potentially threatening objects.

A method for performing a security screening including subjecting the individual to at least two scans using different spectral sources of electromagnetic radiation.

A method as defined in claim 3, wherein each source is selected in the group consisting of a source generating electromagnetic radiation in the frequency range of about 200 MHz to about 1 THz, an X-rays source, visible light source, infrared light source.

A method as defined in claim 4, including generating a first scan data associated with a one of the at least two scans and second scan data associated with the other of the at least two scans.

6. A method as defined in claim 5, including processing each scan data to identify features of interest.

7. A method as defined in claim 6, wherein the processing includes generating location information indicative of a position of an identified feature of interest.

8. A method as defined in claim 7, wherein the processing includes co-relating a feature of interest identified in the first scan data with a feature of interest identified in the second scan data to determine if the feature of interest present a security threat.

9. A method as defined in claim 9, wherein the co-relating includes determining if the feature of interest in the first scan data matches a location of a feature of interest in the second scan data.

10. A method as defined in claim 1, including displaying on a display device results of the processing.

11. A method as defined in claim 10, including displaying on a display device information about a location of the threatening object.

12. A method as defined in claim 10, including rendering on the display device an image of the individual and highlighting in the image a location at which a potentially threatening object exists.

13. A system for performing a security screening at security checkpoint on an individual, said system comprising: full body scanning device for subjecting the individual to a scan from a source producing electromagnetic radiation to generate scan data;

d. a processor including a machine readable storage encoded with software for execution by a CPU for processing the scan data to determine if the scan data contains a signature of a threatening object.

14. A security system for performing a security screening as defined in claim 13, wherein the processing includes identifying in the scan data features of interest indicative of potentially threatening objects.

15. A security system for performing a security screening as defined in claim 14, including at least two different spectral sources of electromagnetic radiation for performing at least two different scans on the individual.

16. A security system as defined in claim 15, wherein each source is selected in the group consisting of a source generating electromagnetic radiation in the frequency range of about 200 MHz to about 1 Hz, an X- rays source, visible light source, infrared light source .

17. A security system as defined in claim 16, wherein the processor generates a first scan data associated with a one of the at least two scans and second scan data associated with the other of the at least two scans.

18. A security system as defined in claim 17, wherein the processor processes each scan data to identify features of interest. 19. A security system as defined in claim 18, wherein the processing includes generating location information indicative of a position of an identified feature of interest . 20. A security system as defined in claim 19, wherein the processing includes co-relating a feature of interest identified in the first scan data with a feature of interest identified in the second scan data to determine if the feature of interest present a security threat.

21. A security system as defined in claim 20, wherein the co-relating includes determining if the feature of interest in the first scan data matches a location of a feature of interest in the second scan data.

22. A security system as defined in claim 13, including a display device for displaying results of the processing.

23. A security system as defined in claim 22, including displaying on a display device information about a location of the threatening object.

24. A security system as defined in claim 22, wherein the display device renders an image of the individual and highlights in the image a location at which a potentially threatening object exists.