HK1160977B - System and method for detection of eas marker shielding - Google Patents

Description

System and method for detecting EAS marker shielding

Technical Field

The present invention relates generally to methods and systems for detecting electronic article surveillance ("EAS") marker shielding, and more particularly, to methods and systems for detecting EAS marker shielding using a combination of metal detection sensors, radio frequency identification ("RFID") sensors, and video sensors to identify detected metal items and prevent false alarms.

Background

The resulting method for deactivating an electronic article surveillance ("EAS") system uses readily available metal foil, such as aluminum foil, to shield the EAS marker from detection by the EAS system. Thieves line shopping bags, handbags and backpacks with foil to provide a concealed barrier for placing items to be stolen while in the store so that they can exit without being detected through the detection zone of the EAS exit system. In response to this problem, retailers are increasingly using metal detection systems that are tuned to detect metal foil so that they can be alerted if a foil-lined bag or backpack passes through an exit.

The main problem with this approach is the presence of many metal objects and products that pass through the EAS system detection zone that are not associated with theft. Some examples of such items are shopping carts, wheelchairs, products with metal or aluminum coated packaging, and foil lined bags for keeping hot cooked food supplies warm, etc. The effectiveness of metal detection systems depends on reducing alarms from non-stolen items passing through the detection zone and increasing detection of genuine foil bags and backpacks.

The metal detector is typically made up of a transmitter and receiver pair. When the metal is within the interrogation zone, the transmitter transmits a signal and the receiver receives an attenuated and/or phase-shifted transmitter signal. Traditionally, these systems have distinguished foil-lined bags from other metal objects by only alerting when metal is detected that has a response signal with an amplitude that falls within a range that is indicative of the foil-lined bag and not the other object. Unfortunately, relying on amplitude is not entirely reliable, as foil-lined bags that are physically close to the metal detector antenna may exhibit response signal strengths similar to those of shopping carts located further away from the metal detector. This problem limits the metal detection system to narrow channels (open) and severely limits the range of definite detection of foil bags, which reduces the sensitivity of the system.

As another attempted solution, retailers sometimes place metal detection systems so that shopping carts do not pass through. That is, the metal detector and/or EAS system is configured so that the shopping cart will not fit through the exit. However, controlling traffic flow to exclude false alarms caused by shopping carts interferes with the normal behavior of the customer and degrades the customer experience. This approach is generally not ideal since a positive customer experience is extremely important to the retailer.

Retailers may also exclude products that cause false alarms, such as metal or metal coated packaging, or foil bags used to keep hot cooked foods in supply, etc. Eliminating products that cause false alarms also degrades the shopping experience and limits customer options that are of paramount importance to the retailer. Thus, this approach is also not ideal for retailers.

Therefore, there is a need for a system and method that can identify items that are likely to be used as foil-lined containers, so that metal detector signals can be validated, and automatically identify items entering the detection zone that may cause false alarms and disable these false alarms.

Disclosure of Invention

The present invention advantageously provides a method and system for detecting electronic article surveillance marker shielding by coordinating inputs from various subsystems, including an electronic article surveillance subsystem, a metal detection subsystem, a video analysis subsystem, and a radio frequency identification system. Correlating known conditions with predefined object classes advantageously allows accurate mask detection and prevents false alarms.

In accordance with one aspect of the present invention, a system for detecting electronic article surveillance marker shielding includes an electronic article surveillance subsystem, a metal detection subsystem, a video analysis subsystem, and a system controller. The system controller is communicatively connected to the electronic article surveillance subsystem, the metal detection subsystem, and the video analysis subsystem. The electronic article surveillance subsystem detects electronic article surveillance markers in a detection zone. The metal detection subsystem includes at least one transmit antenna and detects metal objects within the detection zone. The video analysis subsystem captures at least one video image of the metal object. The system controller determines a first possible classification for the metallic object and calculates a confidence weight for the first possible classification. The system controller further identifies the metallic object as electronic article surveillance marker shielding according to the first possible classification and corresponding confidence weight, and generates an alert.

In accordance with another aspect of the present invention, a system for detecting shielding of an electronic article surveillance marker includes an electronic article surveillance subsystem, a metal detection subsystem, a radio frequency identification subsystem, and a system controller. The system controller is communicably connected to the electronic article surveillance subsystem, the metal detection subsystem, and the radio frequency identification subsystem. The electronic article surveillance subsystem detects electronic article surveillance markers in a detection zone. The metal detection subsystem detects metal objects within the detection zone. The radio frequency identification subsystem detects a radio frequency identification tag within the detection zone, receives a tag code from the radio frequency identification tag, and determines whether the tag code is included in a list of false alarm item codes. The system controller generates an alarm if the metal detection subsystem detects a metal object within the detection zone and the radio frequency identification subsystem determines that the tag code is not included in the list of false alarm item codes. The system controller does not identify a metal object as electronic article surveillance marker shielding if the metal detection subsystem detects the metal object within the detection zone and the radio frequency identification subsystem determines that the tag code is included in the list of false alarm item codes.

In accordance with yet another aspect of the present invention, a method for detecting electronic article surveillance marker shielding is provided. An electronic article surveillance subsystem is provided to detect electronic article surveillance markers within a detection zone. A metal object is detected within the detection zone and a video image of the metal object is taken. A first possible classification for the metal object is determined, and a confidence weight for the first possible classification is calculated. Identifying the metallic object as an electronic article surveillance marker shield according to the first possible classification and corresponding confidence weight, and generating an alert.

Drawings

A more complete understanding of the present invention, and the attendant advantages and features thereof, will be more readily understood by reference to the following detailed description when considered in conjunction with the accompanying drawings wherein:

FIG. 1 is a block diagram of an exemplary electronic article surveillance ("EAS") marker shield detection system constructed in accordance with the principles of the present invention;

FIG. 2 is a block diagram of an alternative EAS marker shield detection system configuration constructed in accordance with the principles of the present invention;

FIG. 3 is a block diagram of an exemplary control system of the EAS marker shield detection system of FIGS. 1 and 2 constructed in accordance with the principles of the present invention;

FIG. 4 is a flow chart of an exemplary metal detection process performed by a metal detection subsystem of an EAS marker shield detection system according to the principles of the present invention;

FIG. 5 is a flow diagram of an exemplary video analysis process performed by the video detection subsystem of the EAS marker shield detection system according to the principles of the present invention;

FIG. 6 is a flow chart of an exemplary radio frequency identification ("RFID") detection process performed by the RFID detection subsystem of the EAS marker shield detection system according to the principles of the present invention;

FIG. 7 is a flowchart of an exemplary top level operation process performed by an EAS marker shield detection system according to the principles of the present invention;

FIG. 8 is a graph illustrating exemplary comparative amplitudes of a shopping cart and a foil-lined bag as a function of distance from a metal detector transmitter antenna; and

FIG. 9 is a graph illustrating an exemplary relationship between metal detector output amplitude and distance of an object from a metal detector transmitter antenna for several types of metal objects.

Detailed Description

Before describing in detail exemplary embodiments that are in accordance with the present invention, it is noted that the embodiments reside primarily in combinations of apparatus components and processing steps related to implementing a system and method for identifying items that are likely to be used as foil-lined containers and identifying items entering a detection zone that may trigger a false alarm to distinguish a true alarm state from a false alarm state. Accordingly, the system and method components have been represented where appropriate by conventional symbols in the drawings, showing only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the disclosure with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein.

As used herein, relational terms, such as "first" and "second," "top" and "bottom," and the like, may be used solely to distinguish one entity or element from another entity or element without necessarily requiring or implying any physical or logical relationship or order between such entities or elements. In addition, the terms "EAS marker," "EAS tag," and "EAS marker" may be used interchangeably herein to refer to a device capable of being detected by an EAS detector.

One embodiment of the present invention advantageously provides a method and system for detecting EAS marker shielding using a metal detection sensor, an RFID sensor, and a video sensor. An EAS detection system designed to detect EAS tags attached to protected articles and a metal detector for sensing the presence of a metal shielding material that may be used to shield the EAS tag from detection by the EAS detection system are used in conjunction with one or more of an RFID reader, a video sensor, and a video analysis system. RFID readers are designed to read RFID tags attached to items known to contain metal that may falsely alarm a metal detection system. One or more video sensors and a video analysis system determine various aspects of the environment surrounding other detection systems to improve detection performance.

By using a video analysis system, the reliability of positively detecting merchandise that may contain EAS marker shielding (e.g., bags, backpacks, etc.) in the vicinity of the detection system is greatly improved. The video analytics system may detect the presence, location, and movement of objects within the detection zone, and also classify these objects to determine their type, both to improve detection of metal in the environment and to identify other known metal objects that may cause false alarms, such as metal shopping carts, wheelchairs, smaller metal objects adjacent to the metal detection system, and so forth.

Referring now to the drawings, in which like reference numbers refer to like elements, there is shown in FIG. 1 the configuration of an exemplary electronic article surveillance ("EAS") marker shield detection system 10 located, for example, at an entrance to a facility. The EAS marker shield detection system 10 includes a pair of pedestals 12a, 12b (collectively pedestals 12) on opposite sides of an entrance 14. The antennas for each of the EAS subsystem, RFID subsystem, and metal detection subsystem may be incorporated in pedestals 12a and 12b located a known distance apart. Video sensors 16 (only one shown) may be positioned in any manner that provides a clear view of portal 14 (e.g., in a suspended manner). The video sensor 16 and the antenna located in the base 12 are communicatively connected to a control system 18 that controls the operation of the EAS marker shield detection system 10.

FIG. 2 illustrates an alternative configuration of the EAS tag shielding detection system 10. As in fig. 1, the EAS antenna, RFID antenna, and metal detection antenna are shown incorporated into two pedestals 12a, 12b on opposite sides of the portal 14, however, in this configuration, video sensors 16a, 16b (collectively referred to as video sensors 16) are also integrated into the pedestals 12. The configurations shown in fig. 1 and 2 illustrate possible configurations of hardware and are intended to limit the scope of the present invention. There are many other configurations that can implement the present invention.

Referring now to FIG. 3, the EAS tag shielding detection system 10 may include an EAS detection subsystem 20 and a metal detection subsystem 22. The EAS detection subsystem 20 detects the presence of an active EAS tag on an item within an interrogation or detection zone near the EAS antenna 24. Likewise, metal detection subsystem 22 detects the presence of a particular metal within a detection zone near metal detection antenna 26. Although not explicitly shown, metal detection antenna 26 is typically configured as a pair of antennas, with a transmit antenna located in one base 12a and a receive antenna located in a second base 12 b. Typically, when the subsystems operate at different radio frequencies, a separate antenna or antenna pair receives the signal for each subsystem; however, it is possible that these subsystems may use the same antenna or antenna pair. In an alternative embodiment, the metal detection system 22 may be configured separately without the integrated EAS subsystem 20.

The system 10 also includes an RFID subsystem 28 coupled to an RFID antenna 30 and a video analysis subsystem 32 coupled to the at least one video sensor 16. The RFID subsystem 28 collects information from active RFID tags within an interrogation or detection zone near the RFID antenna 30. The video analysis subsystem 32 collects video images from the video sensor 16 and identifies certain objects within the video images according to known video analysis techniques. In other embodiments, only one of the RFID subsystem 28 and the video analysis subsystem 32 may be configured with the metal detection subsystem 22.

In addition to detecting objects for metal detection, the video sensor 16 and video analysis subsystem 32 may also be used to collect other data. Such uses include, but are not limited to, measuring the number of customers passing through the passageway, monitoring shopping cart usage, capturing video of alarm events, and the like.

Likewise, the RFID antenna 30 and RFID subsystem 28 may be used to collect other RFID tag data in addition to improving the performance of the metal detection subsystem 22. The RFID subsystem 28 is connected to an RFID false alarm item database 34 that contains a list of tag codes for items known to cause false alarms.

The EAS marker shield detection system 10 also includes an alarm/notification subsystem 36 for generating an alarm or notification in response to positive detection of EAS marker shielding or other defined triggering event (such as detection of an active EAS tag within the interrogation zone).

The various subsystems (i.e., EAS detection subsystem 20, metal detection subsystem 22, RFID subsystem 28, video analysis subsystem 32, and alarm/notification subsystem 36) are connected to an EAS marker shield detection system controller 18 for controlling the overall operation of the EAS marker shield detection system 10. The EAS marker shield detection system controller 18 is also connected to a system database 38, which may contain a plurality of logs, such as an object amplitude and distance log 40 and an alarm/notification condition log 42. The object amplitude and distance log 40 details the signal amplitudes received from the metal detection subsystem 22 for a variety of metals as a function of distance from the metal detection antenna 24. The alarm/notification condition log 42 includes instructions for responding to different alarm conditions. It should be noted that although RFID false alarm item database 34 is described as a separate entity from system database 38, both databases may be physically provided as separate devices.

Referring now to fig. 4-6, exemplary operational flow diagrams describing the operation of the various subsystems are provided. FIG. 7 depicts the top level operation of EAS tag detection system 10. In FIG. 4, a simplified exemplary operational flow diagram depicts steps performed by the metal detection subsystem 22. The metal detection subsystem 22 typically operates during the metal detection phase (step S102) until metal is detected within the detection zone (step S104). When metal is detected, the metal detection subsystem 22 reports this information (including the amplitude and phase of the detected signal) to the EAS marker shield detection system controller 18 for further processing (S106). In alternative configurations, the system may use only amplitude or only phase.

In fig. 5, an exemplary operational flow diagram depicts steps performed by the video analysis subsystem 32. The video analysis subsystem 32 typically operates during the video acquisition phase (step S108) until an object is detected within the detection zone (step S110). When an object has been detected, the video analysis subsystem 32 attempts to classify the object into a known class (step S112). In this exemplary case, the video analysis subsystem 32 is designed to classify objects into three categories: shopping carts, people carrying bags, and people not carrying bags. In alternative configurations, the detected objects may be categorized into other categories, such as (but not limited to) wheelchairs, strollers, other carried items, and the like. Object classification can be accomplished by a variety of pattern classification algorithms known to those skilled in the art, such as template (template) matching, principal component analysis, and the like.

The output of the classification step (step S112) may include the possible classes of objects and the confidence weights resulting from the classification. To illustrate, a high confidence number (e.g., close to 1) indicates that the probability that the classification result obtained by the algorithm is correct is very high. A low confidence number (e.g., close to 0) indicates that the probability that the classification result is correct is very low.

In addition to object classification, the video analysis subsystem also provides as output a measurement of the object's position and a measurement tolerance. Accordingly, if the object is classified as a cart (step S114), the relative position of the cart is measured (step S116) and relevant information is reported to the EAS marker shield detection system controller 18 for further processing (step S118). To illustrate, the location number 150 may represent an object 150cm from a reference point at the base of the transmitter. Tolerance 10 may indicate that the video analysis subsystem estimates the uncertainty of the location number to be +/-10 cm.

Returning to decision block S114, if the video analysis subsystem 32 determines that the object is a person, a carry object detection process is performed (step S120) to determine whether the person carries a bag. If the person carries the bag (step S122), the position of the bag is measured (step S124) and relevant information (e.g., category, confidence, bag position tolerance, and direction of movement (whether an object enters or exits the facility)) is reported to the EAS tag shielding detection system controller 18 for further processing (step S126). If the person does not carry a bag (step S122), the actual position of the person is measured (step S128) and relevant information (e.g., confidence, position and position tolerances, and direction of movement) is reported to the EAS marker shield detection system controller 18 for further processing (step S130).

Referring to fig. 6, an exemplary simplified flow chart of the operation of RFID subsystem 28 is provided. Retailers may place RFID tags on items known to cause false alarms, thereby enhancing the operation of the EAS marker shield detection system 10. The RFID subsystem 28 generally operates in an RFID tag detection phase (step S132) until an RFID tag is detected within the detection zone (step S314). When an RFID tag is detected, RFID subsystem 28 reads the RFID tag, which compares the tag code to a log of error alert items in RFID error alert item database 34 (step 136). Typical types of items on the false alarm log include storage devices such as shopping carts and products known to alarm metal detection systems. Examples of products from supermarkets include roast chicken, boxes of infant formula, etc. kept warm in foil-lined bags. If the detected tag is in the RFID false alarm item database 34 (step S138), the RFID subsystem 28 reports the item and its category to the EAS marker shield detection system controller 18 for further processing (step S140). If the detected tag is not in the RFID false alarm item database (step S138), the RFID subsystem 28 reports the item to the EAS tag shielding detection system controller 18 and reports a determination that the item is not in the RFID false alarm item database 34 for further processing (step S142).

Referring now to FIG. 7, an exemplary operational flow diagram of the top level operation of the EAS tag shielding detection system 10 is provided. The input from metal detection subsystem 22 (connector a in fig. 4), the input from video analysis subsystem 32 (connector B in fig. 5), and the input from RFID subsystem 28 (connector C in fig. 6) are synthesized and analyzed to provide improved metal detection performance. In this embodiment, the metal detector amplitude (step S144) and object position, tolerance and direction of motion data (step S146) from the metal detection subsystem 22 are mapped and compared to the object amplitude and distance database (step S148) to output possible object classes and confidence weights. The object class and confidence weights from the video analysis subsystem 32 (step S150) and the input from the RFID subsystem 28 (step S152) are combined with the possible object class and confidence weights resulting from the comparison with the signal amplitude of the metal detection subsystem 22 to calculate a combined system estimate for the object class and confidence (step S154). Many different methods known to those skilled in the art can be used to calculate the composite object class and confidence estimates, including (but not limited to) linear system methods, neural network methods, and fuzzy logic methods. For example, a simple linear system mapping result may be employed, which may then be compared to simple fixed thresholds for various categories of objects stored in the alarm/notification status log 42 (step S156). The linear system mapping and fixed threshold database are for illustration purposes only, but other more adaptive methods from machine learning known to those skilled in the art may be employed to configure an adaptive system capable of learning from the environment and adapting to changes in the retail environment.

The EAS marker shield detection system controller 18 sends instructions to the alarm/notification subsystem 36 based on the corresponding actions found in the alarm/notification status log 42. For example, the alarm/notification subsystem 36 may initiate an audible or visual alarm, alert or email security personnel or other personnel, call law enforcement, and the like. In some cases, the alarm/notification subsystem 36 may only alarm when an object is moving from outside into the store. This criteria will help to detect the person bringing the foil-lined bag into the store, so that security personnel can be notified to observe the customer and collect evidence of shoplifting.

Referring now to FIG. 8, a graph is provided showing the amplitude of two metal objects in metal detection subsystem 22 as a function of distance from metal detection transmit antenna 26 a. The object 44 is located with the transmitter antenna 26a (T)_X) Distance X₁A foil-lined pouch. The object 46 is located at T_XAntenna 26a distance X₂A metal shopping cart. Further, a set of curves 48, 50 showing the difference between the output amplitudes of the metal detection circuit is shown in FIG. 8Relationship with object distance T_XThe distance of the antenna 26a varies. The top curve 48 shows typical amplitude as a function of distance from the shopping cart (which is a large metal object). The lower curve 50 shows that the typical amplitude varies with the distance of the foil-lined bag (which is a much smaller metal object than the shopping cart). The graph shows that the metal detection circuit alone cannot distinguish the position from T_XAntenna 26a distance X₁Foil lining bag and the position of T_XAntenna 26a distance X₂Because the response signals from both objects exhibit the same amplitude.

A graphical representation of how the present invention improves detection differentiation between items is shown in fig. 9. The relationship between the metal detector output amplitude and the distance of the object from the antenna is shown for several different classes of metal objects. Curve 48 is a typical response curve for a shopping cart, curve 52 represents a wheelchair, curve 54 represents a large foil-lined bag, curve 56 represents a medium size foil-lined bag, and curve 58 represents a small foil-lined bag. Since the video analysis subsystem 32 provides for a target object distance T_XThe estimation of the distance of the antenna 26a and the metal detection subsystem 22 of the present invention provides the amplitude of the response of the detection circuit, so these two outputs can be combined with other information to make a better decision as to the category of metal objects detected in the system 10. By better classifying the object according to this additional information, better decisions can be discerned. For example, in FIG. 9, the amplitude and estimated distance are combined to generate an estimate of the class of the object and a confidence weight for estimating the confidence that the classification estimate is correct.

Referring again to fig. 7, the output of each of these various subsystems (i.e., EAS detection subsystem 20, metal detection subsystem 22, RFID subsystem 28, video analysis subsystem 32, and alarm/notification subsystem 36) is combined with confidence weights from each subsystem to make an overall decision for alarming or notifying a foil bag within a detection zone. The method for making this decision can be implemented by many different methods including linear techniques or neural network methods. The method shown in fig. 7 enables a simple weighted summation of the outputs of each subsystem and compares the weighted sum to a stored threshold. Many other suitable methods derived from pattern recognition and machine learning known to those skilled in the art may also be used to determine the best results. In addition, adaptive learning techniques may be employed to adapt the system to conditions within the installation environment.

The present invention can be realized in hardware, software, or a combination of hardware and software. Any kind of computing system, or other apparatus adapted for carrying out the methods described herein, is suited to perform the functions described herein.

A typical combination of hardware and software could be a computer system having one or more processing elements and a computer program stored on a storage medium that, when being loaded and executed, controls the computer system such that it carries out the methods described herein. The present invention can also be embedded in a computer program product, which comprises all the features enabling the implementation of the methods described herein, and which-when loaded in a computing system-is able to carry out these methods. Storage medium refers to any volatile or non-volatile memory device.

Computer program or application in the context of the present invention refers to any expression, in any language, code or notation, of a set of instructions intended to cause a system having an information processing capability to perform a particular function either directly or after either or both of the following: a) conversion to another language, code or notation; b) reproduced in different physical forms.

In addition, unless mention was made above to the contrary, it should be noted that all of the accompanying drawings are not to scale. It will be evident that the invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof, and accordingly, reference should be had to the following claims, rather than to the foregoing specification, as indicating the scope of the invention.

Claims (20)

1. A system for detecting electronic article surveillance marker shielding, the system comprising:

an electronic article surveillance subsystem operative to detect electronic article surveillance markers within a detection zone;

a metal detection subsystem comprising at least one transmit antenna, the metal detection subsystem operative to detect metal objects within the detection zone;

a video analysis subsystem operative to capture at least one video image of the metal object; and

a system controller communicably connected to the electronic article surveillance subsystem, the metal detection subsystem, and the video analysis subsystem, the system controller operative to:

determining a first possible classification for the metal object;

calculating a confidence weight for the first possible classification;

identifying the metallic object as an electronic article surveillance marker shield according to the first possible classification and corresponding confidence weight; and is

An alarm is generated.

2. The system of claim 1, wherein the video analysis subsystem is further operative to determine a direction of movement of the metallic object, the system controller generating an alarm only in response to the video analysis subsystem determining that the direction of movement is toward the monitored facility.

3. The system of claim 1, wherein:

the metal detection subsystem further determines an amplitude of the response signal;

the video analysis subsystem further measures a distance between the metal object and the transmitting antenna; and

the system controller determines the first possible classification for the metal object by correlating the amplitude of the response signal and the distance between the metal object and the transmitting antenna with data corresponding to a predefined object class.

4. A system according to claim 3, wherein the predefined object categories include at least two of carts, people carrying bags, people not carrying bags, wheelchairs, strollers, and carried objects.

5. The system of claim 3, wherein the video analysis subsystem is further operative to:

providing a tolerance value for the distance measurement; and

calculating a confidence weight for the first possible classification using the tolerance value.

6. The system of claim 1, wherein the step of generating an alarm comprises at least one of sounding an audible alarm, initiating a visual alarm, and sending an alarm notification.

7. The system of claim 1, further comprising:

a radio frequency identification subsystem communicably connected to the system controller, the radio frequency identification subsystem operative to:

detecting a radio frequency identification tag within the detection zone;

receiving a tag code from the radio frequency identification tag;

comparing the tag code to a list of false alarm item codes; and

in response to determining that the tag code is included in the list of false alarm item codes, not identifying the metallic object as electronic article surveillance marker shielding.

8. The system of claim 3, wherein the video analysis subsystem is further operative to:

determining a second possible classification of the object from the predefined object class using video object recognition techniques; and

a confidence weight is calculated for the second possible classification.

9. The system of claim 8, wherein the system controller is further operative to:

synthesizing the first possible object classification and corresponding confidence weight with the second possible object classification and corresponding confidence weight to compute a system object classification and corresponding system confidence weight; and

identifying the metal object according to the system object classification and the corresponding system confidence weight.

10. The system of claim 9, further comprising:

a radio frequency identification subsystem communicably connected to the system controller, the radio frequency identification subsystem operative to:

detecting a radio frequency identification tag within the detection zone;

receiving a tag code from the radio frequency identification tag;

comparing the tag code to a list of false alarm item codes; and

in response to determining that the tag code is included in the list of false alarm item codes, not identifying the metallic object as electronic article surveillance marker shielding.

11. A system for detecting electronic article surveillance marker shielding, the system comprising:

an electronic article surveillance subsystem operative to detect electronic article surveillance markers within the detection zone;

a metal detection subsystem operative to detect metal objects within the detection zone;

a radio frequency identification subsystem operative to:

detecting a radio frequency identification tag within the detection zone;

receiving a tag code from the radio frequency identification tag; and

determining whether the tag code is included in a list of false alarm item codes;

a system controller communicably connected to the electronic article surveillance subsystem, the metal detection subsystem, and the radio frequency identification subsystem, the system controller operative to:

generating an alarm in response to the metal detection subsystem detecting a metal object within the detection zone and the radio frequency identification subsystem determining that the tag code is not included in the list of false alarm item codes; and

in response to the metal detection subsystem detecting a metal object within the detection zone and the radio frequency identification subsystem determining that the tag code is included in the list of false alarm item codes, not identifying the metal object as electronic article surveillance marker shielding.

12. The system of claim 11, wherein the generating an alert comprises: at least one of causing an audible alarm to occur, initiating a visual alarm, and sending an alarm notification.

13. A method for detecting electronic article surveillance marker shielding, the method comprising:

providing an electronic article surveillance subsystem to detect electronic article surveillance markers within a detection zone;

detecting a metal object within the detection zone;

shooting a video image of the metal object;

determining a first possible classification for the metal object;

calculating a confidence weight for the first possible classification;

identifying the metal object as an electronic article surveillance marker shield according to the first possible classification and the corresponding confidence weighting; and

an alarm is generated.

14. The method of claim 13, further comprising:

sending a metal detection signal;

determining an amplitude of a response signal to the metal detection signal;

measuring a distance between the metal object and a transmitting antenna; and

determining the first possible classification for the metal object by correlating the amplitude of the response signal and the distance between the metal object and the transmitting antenna with data corresponding to a predefined object class.

15. A method according to claim 14, wherein the predefined object categories include at least two of carts, people carrying bags, people not carrying bags, wheelchairs, strollers, and carried objects.

16. The method of claim 14, further comprising:

providing a tolerance value for the distance measurement; and

calculating a confidence weight for the first possible classification using the tolerance value.

17. The method of claim 13, wherein the step of generating an alarm comprises at least one of sounding an audible alarm, initiating a visual alarm, and sending an alarm notification.

18. The method of claim 13, further comprising:

detecting a radio frequency identification tag within the detection zone;

receiving a tag code from the radio frequency identification tag;

comparing the tag code to a list of false alarm item codes; and

in response to determining that the tag code is included in the list of false alarm item codes, not identifying the object as electronic article surveillance marker shielding.

19. The method of claim 14, further comprising:

determining a second possible classification of the metal object from the predefined object class using video object recognition techniques;

calculating a confidence weight for the second possible classification;

synthesizing the first possible object classification and corresponding confidence weight with the second possible object classification and corresponding confidence weight to compute a system object classification and corresponding system confidence weight; and

identifying the metal object according to the system object classification and the corresponding system confidence weight.

20. The method of claim 19, further comprising:

detecting a radio frequency identification tag within the detection zone;

receiving a tag code from the radio frequency identification tag;

comparing the tag code to a list of false alarm item codes; and

in response to determining that the tag code is included in the list of false alarm item codes, not identifying the metallic object as electronic article surveillance marker shielding.