Live finger detection

Information

  • Patent Grant
  • 8374407
  • Patent Number
    8,374,407
  • Date Filed
    Wednesday, January 28, 2009
    16 years ago
  • Date Issued
    Tuesday, February 12, 2013
    12 years ago
Abstract
A live finger detection system and method includes a drive plate configured to inject radio frequency signals into an object proximate the drive plate. The injected radio frequency energy causes the object to radiate an electric field. A pickup plate is configured to detect an intensity associated with the electric field radiated by the object. A sensor coupled to the pickup plate is configured to determine whether the object is a live finger based on the detected intensity of the electric field radiated by the object.
Description
BACKGROUND

The invention relates generally to systems and methods for determining whether a live human finger is being applied to a fingerprint sensor or other sensing device. In particular, the described systems and methods prevent unauthorized users from “spoofing” a fingerprint sensor by creating artificial fingers that replicate the fingerprint pattern of a valid user.


Fingerprint sensors are seeing increased usage in many devices, such as laptop computers, cell phones and other mobile devices, and security systems for the purpose of user authentication and password replacement. This increased usage of fingerprint sensors has raised concerns about the level of security provided by these sensors. One concern involves the creation of artificial fingers that replicate the fingerprint pattern of a valid user and are applied to the fingerprint sensor to gain unauthorized access to a device, building, and the like. These artificial fingers are often created using materials that are electrically and optically similar to live finger tissue. Materials commonly used to create artificial fingers include gelatins, rubbers, and glues.


Several techniques have been developed in an attempt to detect the electrical differences between live human fingers and artificial fingers created for the purpose of “spoofing” a fingerprint sensor. Most of these techniques try to differentiate live fingers from artificial fingers by attempting to detect small differences in internal electrical impedance values that are measured by electrically contacting the finger. For example, existing techniques measure the capacitance of an object and determine whether the object's capacitance is within a range associated with the biological characteristics of live finger tissue. Other similar techniques measure the resistance or electrical impedance of an object instead of the object's capacitance.


These existing techniques are used with limited success due to the wide variations in capacitance, resistance, and impedance of human tissue over large populations and demographics. These wide variations prevent the establishment of accurate boundaries for detecting live fingers without increasing the false rejection rate of the detection system. Additionally, the capacitance, resistance, and impedance of human tissue varies over time for a particular user and changes in response to environmental conditions. For example, the resistance of a user's finger changes in proportion to sweat gland activity in the user's finger. Additionally, dermatological conditions, diet, and exposure to certain chemicals can alter the capacitance, resistance, and impedance of human tissue.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 depicts a block diagram of an embodiment of a live finger detection system.



FIG. 2 depicts an embodiment of a live finger sensor.



FIG. 3 depicts a finger being applied to an embodiment of a live finger sensor.



FIG. 4 depicts a cross-sectional view of a finger being applied to an embodiment of a live finger sensor.



FIG. 5 depicts a finger being applied to another embodiment of a live finger sensor.



FIG. 6 depicts a finger being applied to yet another embodiment of a live finger sensor.



FIG. 7 depicts a finger being applied to a further embodiment of a live finger sensor.



FIGS. 8A and 8B depict additional embodiments of a live finger sensor including a fingerprint sensor.



FIG. 9 depicts a flow diagram of an example method for detecting a live human finger.



FIG. 10 depicts an example electric RF field intensity radiated from a real human finger.



FIG. 11 depicts an example electric RF field intensity radiated from an artificial finger.





Throughout the description, similar reference numbers may be used to identify similar elements.


DETAILED DESCRIPTION

The systems and methods described herein perform live finger detection using radiated RF (radio frequency) electric field patterns. The described systems and methods detect differences in the externally radiated electric field patterns created by live human fingers excited with RF energy as compared to artificial fingers. This approach more reliably detects live human fingers than the previous systems discussed. The systems and methods described herein are more reliable due to the relatively stable electric field patterns generated by live human fingers across a wide spectrum of population and demographics.


When describing the live finger detection systems and methods herein, the object being detected is often referred to as a “finger”. However, any reference to a “finger” herein includes both a live human finger as well as an artificial finger or any other object being presented for verification or other purposes. Although the described systems and methods refer to live finger detection, these systems and methods may be adapted to detect and/or validate other types of objects.



FIG. 1 depicts a block diagram of an embodiment of a live finger detection system 100. Live finger detection system 100 includes a live finger sensor 102 on which a user places their finger as part of the live finger detection process. Live finger sensor 102 is coupled to receive signals from a signal generator 104. Signal generator 104 generates signals used by live finger sensor 102 to inject RF electric fields into a finger placed on the live finger sensor. An RF sensor 106 receives signals from live finger sensor 102 indicating the strength of the RF fields detected near the finger by a detection portion of the live finger sensor 102, as discussed in greater detail below.


In particular embodiments of live finger detection system 100, a rate sensor 108 receives signals from live finger sensor 102. Rate sensor 108 processes the received signals to determine a speed with which a finger or other object is swiped across live finger sensor 102. A verification module 110 receives signals from RF sensor 106 and, optionally, from rate sensor 108. Verification module 110 uses those received signals along with knowledge of RF fields radiated by live human fingers to determine whether the object applied to live finger sensor 102 is a live human finger or an artificial finger. Verification module 110 then generates a verification signal indicating whether or not the object applied to live finger sensor 102 is verified as a live human finger.



FIG. 2 depicts an embodiment of live finger sensor 102. Live finger sensor 102 and its components can be of any size that accommodates a human finger or other object being sensed. Live finger sensor 102 includes a single drive plate 207 positioned within a drive plate area 206 and a pickup plate 212 located on a substrate 210. Drive plate area 206 identifies the approximate perimeter of the area that the finger contacts the live finger sensor. Drive plate 207 is a conductive plate disposed on substrate 210 and coupled to drive an electrical signal from a signal generator 104 into the body of the finger. In alternate embodiments, live finger sensor 102 includes an array of multiple drive plates positioned within drive plate area 206.


In response to the live finger sensor detecting an object placed upon it, drive plate 207 injects RF energy into that object (e.g., a live human finger or an artificial finger) contacting the drive plate. This RF energy causes electric RF fields to radiate outwardly from the surface of the object. As discussed below, the characteristics of the electric RF fields radiated from the object vary depending on whether the object is a live human finger, an artificial finger, or another type of object. Thus, a live human finger is detected by analyzing the characteristics of the electric RF fields radiated from the object. Although particular examples of drive plate 207 are illustrated and discussed herein, alternate embodiments may utilize any radio frequency energy source or other device capable of injecting RF energy into an object. In a particular embodiment, drive plate 207 is constructed from materials that are electrically more conductive than a finger, such as copper traces formed on a printed circuit board.


Pickup plate 212 is a conductive plate disposed on substrate 210. Pickup plate 212 detects the electric RF fields radiated from the object and is coupled to communicate information about the detected electric RF fields to RF sensor 106 (FIG. 1). In a particular embodiment, pickup plate 212 detects the intensity or amplitude of the electric RF fields proximate the pickup plate. Pickup plate 212 is typically positioned close to drive plate 207, but electrically insulated from the drive plate. Additionally, pickup plate 212 is generally positioned such that the pickup plate does not contact the object radiating the electric RF fields. Although particular examples of pickup plate 212 are illustrated and discussed herein, alternate embodiments may utilize any device or component capable of detecting the intensity, amplitude, or other characteristics of the electric RF fields radiated from the object. In a particular embodiment, finger tip 204 is aligned with the edge of pickup plate 207 and is less than 1 mm from pickup plate 211.


In the embodiment of FIG. 2, one side of drive plate 207 is formed with a contoured arc that generally corresponds to the curvature of a human finger tip. Similarly, pickup plate 212 is formed with a contoured arc that generally corresponds to the contoured arc formed in drive plate 207. Thus, pickup plate 212 is generally spaced an equal distance from a finger tip along the length of the pickup plate. In alternate embodiments, drive plate 207 and/or pickup plate 212 are rectilinear plates extending substantially parallel to the tip of a human finger.


The components shown in FIG. 2 are not necessarily drawn to scale. The ratio of the dimensions of drive plate 207 to the dimensions of pickup plate 212 may vary from the illustration in FIG. 2. In alternate embodiments, the size, shape, and positioning of drive plate 207 and pickup plate 212 may vary from the embodiment of FIG. 2. In a particular embodiment, pickup plate 212 is formed using a conductive material such as copper.


Substrate 210 provides a mounting and/or support mechanism for drive plate 207, pickup plate 212, and any number of other components and/or devices. Substrate 210 can be a rigid material or it can be flexible, depending on the particular application. Additionally, substrate 210 can be any thickness (and may have varying thickness) and can be manufactured from any material or combination of materials. In one embodiment, substrate 210 also includes a fingerprint sensor disposed thereon or otherwise contained within substrate 210. This embodiment is discussed in greater detail below. In particular embodiments, substrate 210 is formed using fiberglass filled epoxy for rigid substrates or formed using Kapton® polyimide film (available from DuPont) for flexible substrates.


In one embodiment of a live finger detection system, signal generator 104 applies a signal to drive plate 207 that is approximately 2.5 volts. This signal is also referred to as a “drive signal”. The spacing between drive plate 207 and pickup plate 212 varies based on the magnitude of the signal applied to the drive plate. In the example of a 2.5 volt signal applied to drive plate 207, the spacing between the drive plate and pickup plate 212 is less than one millimeter. In embodiments that apply a signal to drive plate 207 that is greater than 2.5 volts, a larger spacing between the drive plate and pickup plate 212 is possible.


A particular embodiment of live finger sensor 102 receives a signal from signal generator 104 that has a frequency in the range of 10-30 MHz. This signal is applied to drive plate 207. The signal from signal generator 104 may be received in bursts or in a continuous or pseudo-continuous manner. Higher frequency signals generally cause more electric RF fields to be radiated from the finger, thereby providing more RF fields for detection by pickup plate 212 and validation by verification module 110. In alternate embodiments, multi-frequency signals are provided from signal generator 104 to drive plate 207. For example, a multi-frequency signal can include two or more frequencies that are separated by at least one decade of frequency. Multiple-frequency signals generally provide more information, and thereby provide better discrimination between live human fingers and artificial fingers.


In one embodiment, pickup plate 212 detects the intensity or amplitude of the electric RF fields proximate the pickup plate. In other embodiments, one or more pickup plates (and related sensors) measure the phase of the electric RF fields proximate the pickup plate(s) as well as the amplitude of the electric RF fields. The addition of a phase measurement can enhance the ability of the system to distinguish between a live human finger and an artificial finger.



FIG. 3 depicts finger 202 being applied to an embodiment of a live finger sensor. Finger 202 includes a finger tip 204 and is positioned on substrate 210 such that the finger substantially covers drive plate 207. Thus, when signal generator 104 applies a drive signal to drive plate 207, various electric RF fields 208 radiate outwardly from the surface of finger 202. Electric RF fields 208 are shown in FIG. 3 as gradients that decrease in intensity as they radiate away from the surface of finger 202. Although FIG. 3 shows electric RF fields 208 radiating outwardly from the plane of substrate 210, finger 202 radiates electric RF fields outwardly from the finger in all three dimensions around the body of the finger. Pickup plate 212 senses the intensity of electric RF fields 208 and provides the sensed intensity to RF sensor 106 (FIG. 1). In a particular embodiment of the live finger sensor shown in FIG. 3, finger tip 204 is aligned with the edge of pickup plate 207 and is less then 1 mm from pickup plate 211.



FIG. 4 depicts a cross-sectional view of finger 202 being applied to an embodiment of a live finger sensor. As discussed above, the live finger sensor includes substrate 210 with drive plate 207 and pickup plate 212 disposed on the substrate. When signal generator 104 applies a drive signal to drive plate 207, electric RF fields 208 radiate outwardly from the surface of finger 202. Electric RF fields decrease in intensity as they radiate farther away from the surface of finger 202. As illustrated in FIG. 4, electric RF field 208 has the greatest intensity closest to the surface of finger 202, as indicated by reference numeral 208A. As the electric RF field radiates farther away from finger 202, the intensity decreases, as indicated by reference numeral 208B. The electric RF field continues radiating farther from finger 202 and further decreasing in intensity, as indicated by reference numeral 208C. As mentioned above with respect to FIG. 3, electric RF fields radiate outwardly from the surface of finger 202 in all three dimensions around the body of the finger. A two dimensional slice of the electric RF fields of 208A, 208B, and 208C are intercepted onto substrate 210 and picked up by plate 212.



FIG. 5 depicts finger 202 being applied to another embodiment of a live finger sensor. In the embodiment of FIG. 5, pickup plate 212 extends partially perpendicular from substrate 210. Pickup plate 212 has a contoured arc shape that substantially follows the contour of finger tip 204 as the pickup plate extends upwardly (as oriented in FIG. 5) from substrate 210. This configuration typically includes a mechanism to support pickup plate 212, such as a plastic housing or other arrangement to support the extension of the pickup plate from substrate 210.



FIG. 6 depicts finger 202 being applied to yet another embodiment of a live finger sensor. The embodiment of FIG. 6 includes multiple pickup plates 212, 214, and 216 disposed adjacent to finger tip 204. This embodiment allows the live finger detection system to simultaneously measure the electric RF field at multiple known distances from finger 202. In operation, all three pickup plates 212, 214, and 216 are sensed simultaneously, thereby permitting the measurement of differences in the intensity of the electric RF field between the three pickup plates.



FIG. 6 is particularly useful with fingerprint sensors that rely on static finger placement to capture a full fingerprint image in a single frame. In these types of fingerprint sensors, multiple pickup plates are positioned outside the fingerprint sensing area to measure radiated RF fields. The multiple pickup plates are typically positioned around the perimeter of the finger placement area.



FIG. 7 depicts finger 202 being applied to a further embodiment of a live finger sensor. The embodiment of FIG. 7 includes a pair of differential pickup plates 218 and 220 positioned adjacent to finger tip 204. Pickup plates 218 and 220 are configured to measure the electric RF fields radiated from finger 202. This configuration allows the live finger detection system to measure the difference in the electric RF field between pickup plates 218 and 220, and has the advantage of reducing common mode noise sources and far field noise sources. Typically, pickup plates 218 and 220 are placed in close proximity to one another to improve noise reduction. In a particular embodiment, pickup plates 218 and 220 are separated by approximately 50-100 micrometers. Pickup plates 218 and 220 are typically coupled to a differential receiver (not shown) that determines the difference in the electric RF field between the two pickup plates.



FIG. 8A and 8B depict additional embodiments of a live finger sensor that includes a fingerprint sensor 240. The embodiment of FIG. 8A includes drive plate 207 and pickup plate 212 disposed on substrate 210 in the manner discussed herein. Additionally, fingerprint sensor 240 is positioned on substrate 210. Fingerprint sensor 240 captures an image associated with a user's fingerprint. Fingerprint sensor 240 may be any type of fingerprint sensor, such as a swipe fingerprint sensor shown in FIG. 8A where a user's finger is swiped across the sensor from the position in 202A to 202 in the direction of arrow 230. A static fingerprint sensor (also referred to as a placement sensor) is shown in FIG. 8B where a full fingerprint image is captured in a single frame. Fingerprint sensor 240 can be used with any of the live finger sensor embodiments and alternate embodiments discussed herein. In one embodiment, pickup plate 207 and drive plate 212 are integrated onto the same substrate as fingerprint sensor 240 creating a larger multifunction sensor shown by the additional sensor area of 240a. In one implementation, fingerprint sensor 240 includes swiped imaging sensors consisting of two or more rows of imaging pixels. Such sensors calculate the speed of the finger passing over it by measuring the time it takes for unique fingerprint features to pass from one image line to the next. This information can also be used to normalize the speed of the finger tip as is passes from drive plate 207 to pickup plate 212.


As the finger is swiped in direction 230 from position 202A to 202 across the live finger sensor in FIG. 8A, the finger tip crosses drive plate 207, then crosses pickup plate 212, and eventually moves off the pickup plate. Electric RF field information is sampled by pickup plate 212 at a rate that is significantly faster than the rate at which the finger is swiped across the sensor. Based on the sampled RF field information, the live finger detection system creates a time-RF field intensity profile of the RF fields sensed (e.g., sampled) along the axis of the swipe. In a particular embodiment, the RF field samples are taken at intervals of approximately 100 microseconds to one millisecond, which is comparable to the sampling rate of many swipe fingerprint sensors. Additional details regarding evaluation of the RF field intensity profile are discussed below.


In an alternate embodiment of a live finger sensor, finger 202 is swiped across drive plate 207, but not swiped across pickup plate 212. In this alternate embodiment, pickup plate 212 is positioned in front of finger tip 204 and finger 202 is swiped away from the pickup plate as the finger is swiped across drive plate 207.


In another embodiment of a live finger sensor, two or more contact sensors are positioned along the axis of finger movement. This embodiment has the advantage of simultaneously capturing the entire electric RF field roll off profile outside the finger at the same time. In this embodiment, the array of pickup plates extends beyond the radiated field patterns projecting from the end of the finger.


Specific embodiments discussed herein include one or more pickup plates that detect the electric RF fields radiated from the tip of a finger or other object. As discussed herein, the electric RF fields radiated from the finger radiate outwardly in all directions from the surface of the finger. In alternate embodiments, one or more pickup plates are positioned to detect the electric RF fields radiated from either side of the finger, from the bottom of the finger, or from the top of the finger. Further embodiments utilize multiple pickup plates positioned to detect the electric RF fields radiated from multiple locations on the finger. For example, multiple pickup plates may detect the electric RF fields radiated from the tip of the finger as well as two sides of the finger.



FIG. 9 depicts a flow diagram of an example method 300 for detecting a live human finger. Initially, an object (such as a live finger or an artificial finger) is placed on the live finger sensor (block 302). A signal generator then generates a signal and communicates the signal to a drive plate, thereby causing the drive plate to inject RF energy into the object contacting the live finger sensor and causing electric RF fields to radiate outwardly from the surface of the object (block 304). Next, a pickup plate senses the intensity of an electric RF field radiated from the object (block 306). The pickup plate communicates the sensed electric RF field to an RF sensor (block 308). The RF sensor detects the intensity of the sensed electric RF field and communicates the detected intensity value to a verification module (block 310).


Procedure 300 continues by determining whether the sensed electric RF field is characteristic of a live human finger (block 312). If the sensed electric RF field is characteristic of a live human finger, the procedure generates a verification signal indicating that a live human finger is detected (block 314). If the sensed electric RF field is not characteristic of a live human finger, the procedure generates a signal indicating that the object is not a live human finger (block 316).


As mentioned herein, the characteristics of the electric RF fields radiated from a live finger are different from the fields radiated from an artificial finger or other type of object. Thus, a live human finger is detected and verified by analyzing the characteristics of the electric RF fields radiated from the object applied to the live finger sensor 102. Although a live finger and an artificial finger may have similar electrical impedance characteristics, the fields radiated from live fingers and artificial fingers are significantly different when using the systems and methods described herein.


For example, many materials used to manufacture artificial fingers are uniform conductors of electric fields whereas a live finger is not a uniform conductor of electric fields. Live fingers have an inherent multilayer structure that radiates electric fields based on the combined effects of both the dermal and the sub-dermal layers of the live finger tissue. This multilayer structure of live fingers is common to all fingers across large populations, demographics, dermatological conditions, and so forth. Since this multilayer structure is common to all fingers, the electric RF field characteristics of live fingers are stable over a wide range of users.


There is a significant difference in the electrical field intensity radiated from a real finger compared to that of an artificial one given the same level of excitation. This is primarily due to the multilayer nature of the skin that encloses a real finger which consists of three major layers: epidermal, dermal and subcutaneous. This layering causes an uneven distribution of electric field within the body of a real finger. Since the dermal and subcutaneous layers are more conductive, a significant portion of the field is constrained within those layers. In contrast, artificial fingers made from gelatin, rubber, glue, and other impedance mimicking materials have very uniform conductance with the electric field distributing evenly throughout the artificial finger.



FIG. 10 depicts an example electric RF field intensity 400 radiated from a real human finger. FIG. 11 depicts an example electric RF field intensity 410 radiated from an artificial finger. As shown in FIGS. 10 and 11, the amplitude of the electric RF field intensity radiated by the artificial finger is greater than the amplitude of the electric RF field intensity radiated by the real human finger. This difference in amplitude is useful in distinguishing a real human finger from an artificial finger.


In both real human fingers and artificial fingers, the roll-off of the intensity of the radiated electric RF field follows a function defined as:






Intensity
=

A
kD






Where A is the amplitude of the electric RF field on the surface of the finger and D is the distance from the tip or edge of the finger to the pickup plate(s). The constant k is the mean decay value derived from a database of a large population of fingers. The amplitude A of an artificial finger is significantly greater than the amplitude of a real human finger. Thus, discriminating thresholds can be set for pickup plate(s) having a known distance from the tip or edge of the finger. These thresholds are set based on a large database of diverse fingers where statistical mean, median, standard deviation and similar calculations are used to set these values. As a result, this technique is effective over a wide range of demographic finger variations.


In a particular embodiment, the amplitude of the electric RF field (and other characteristics of the electric RF field) are stored in a storage device (not shown) during an enrollment process by each user. This enrollment process captures the user's fingerprint image and stores that fingerprint image data for future reference when validating the fingerprint. At the same time, this embodiment injects RF energy into the user's finger and measures the characteristics of the resulting electric RF field radiated from the finger. These characteristics of the resulting electric RF field are stored along with the fingerprint image data associated with the user, and are later used to verify that a live human finger is being applied to the live finger sensor.


Embodiments of the system and method described herein facilitate determination of whether a live human finger or an artificial finger is being applied to a sensor. Additionally, some embodiments may be used in conjunction with one or more conventional fingerprint sensing systems and methods. For example, one embodiment may be used as an improvement of existing fingerprint detection and/or sensing systems.


Although the components and modules illustrated herein are shown and described in a particular arrangement, the arrangement of components and modules may be altered to perform live finger sensing in a different manner. In other embodiments, one or more additional components or modules may be added to the described systems, and one or more components or modules may be removed from the described systems. Alternate embodiments may combine two or more of the described components or modules into a single component or module.


Although specific embodiments of the invention have been described and illustrated, the invention is not to be limited to the specific forms or arrangements of parts so described and illustrated. The scope of the invention is to be defined by the claims appended hereto and their equivalents.

Claims
  • 1. A detection apparatus comprising: a plurality of drive plates configured to transmit radio frequency energy to a respective one of a plurality of drive plate contact points formed by an array of the plurality of drive plates;a pickup plate, separated from each respective drive plate contact point by an injection gap, each respective drive plate and the pickup plate configured to transform the radio frequency energy into an electromagnetic field extending between the respective drive plate and the pickup plate extending across the respective injection gap, and the pickup plate configured to receive a modified electromagnetic field, modified by passing through an object spanning the respective injection gap; anda sensor coupled to the pickup plate and configured to determine whether the object is a live finger based on the detected intensity of the electromagnetic field passing through the object and received at the pickup plate.
  • 2. The detection apparatus of claim 1, wherein the object is in physical contact with the respective drive plate when the electromagnetic field passes through the object.
  • 3. The detection apparatus of claim 1, wherein the pickup plate is positioned approximately one millimeter from the respective drive plate.
  • 4. The detection apparatus of claim 1, wherein one side of each respective drive plate is formed with a contoured arc that substantially corresponds to the shape of a human finger tip.
  • 5. The detection apparatus of claim 1, wherein the pickup plate is formed with a contoured arc that substantially corresponds to the shape of a human finger tip.
  • 6. The detection apparatus of claim 1, wherein the pickup plate is positioned proximate the object without contacting the object.
  • 7. The detection apparatus of claim 1, wherein the respective drive plate is disposed on a substrate and the pickup plate extends substantially perpendicular to the substrate.
  • 8. The detection apparatus of claim 7, wherein the substrate is a printed circuit board.
  • 9. The detection apparatus of claim 7, wherein the substrate is a flexible substrate.
  • 10. The detection apparatus of claim 1, wherein the respective drive plate receives a drive signal from a signal generator, the drive signal having a frequency in the range of 10-30 MHz.
  • 11. The detection apparatus of claim 1, wherein the respective drive plate receives a drive signal from a signal generator, the drive signal having a magnitude of approximately 2.5 volts.
  • 12. The detection apparatus of claim 1, wherein the sensor includes a verification module configured to analyze the electromagnetic field passed through the object to determine whether characteristics of the electromagnetic field passed through the object are associated with a live finger.
  • 13. The detection apparatus of claim 12, wherein the verification module is further configured to retrieve and compare electromagnetic field characteristics associated with a known user's fingerprint.
  • 14. The detection apparatus of claim 1, wherein the object comprises a finger and further comprising a fingerprint sensor configured to read a fingerprint pattern associated with the finger, and wherein live finger detection and fingerprint sensing are performed at the same time.
  • 15. A detection apparatus comprising: a plurality of drive plates disposed on a substrate and configured to transmit radio frequency energy to a plurality of drive plate contact points formed by an array of the plurality of drive plates;a first pickup plate disposed on the substrate separated from each respective drive plate contact point by an injection gap, each respective drive plate and the pickup plate configured to transform the radio frequency energy into an electromagnetic field extending between the respective drive plate contact point and the first pickup plate extending across the respective injection gap, and the pickup plate and configured to receive a modified electromagnetic field, modified by passing through an object spanning the respective injection gap;a second pickup plate disposed on the substrate separated from each respective drive plate contact point by an injection gap, each respective drive plate and the pickup plate configured to transform the radio frequency energy into an electromagnetic field extending between the respective drive plate and the second pickup plate extending across the respective injection gap, and the pickup plate and configured to receive a modified electromagnetic field modified by passing through the object spanning the respective injection gap; anda sensor coupled to the first pickup plate and the second pickup plate, the sensor configured to determine whether the object is a live finger based on the detected first and second intensities of the electromagnetic field passing through the object and received at the pickup plate.
  • 16. The detection apparatus of claim 15, further comprising a differential receiver coupled to the first pickup plate and the second pickup plate, the differential receiver configured to determine a difference between the first intensity and the second intensity.
  • 17. The detection apparatus of claim 15, wherein the sensor includes a verification module configured to analyze the first intensity and the second intensity to determine whether at least one characteristic of the electromagnetic field passing through the object is associated with a live finger.
  • 18. The detection apparatus of claim 15, wherein the object comprises a finger and further comprising a fingerprint sensor configured to read a fingerprint pattern associated with the finger, wherein live finger detection and fingerprint sensing are performed at the same time.
  • 19. An apparatus comprising: a plurality of radio frequency energy sources configured to transmit radio frequency energy to a respective one of a plurality of drive plate contact points in an array of drive plate contact points; andat least one pickup plate separated from each respective radio frequency energy source at each drive plate contact point by an injection gap, each respective radio frequency energy source and the respective pickup plate configured to transform the radio frequency energy into an electromagnetic field extending between the respective radio frequency energy source and pickup plate extending across the respective injection gap, and the pickup plate configured to receive a modified electromagnetic field, modified by passing through an object spanning the respective injection gap a live finger sensor proximate at least one injection gap, the live finger sensor configured to detect a characteristic associated with the electromagnetic field passing through the object and to determine whether the object is a live finger based on the at least one characteristic of the electromagnetic field passing through the object.
  • 20. The apparatus of claim 19, wherein the radio frequency energy source is a drive plate.
  • 21. The apparatus of claim 19, wherein the live finger sensor includes a pickup plate proximate the radio frequency energy source and an RF sensor coupled to the pickup plate.
  • 22. The apparatus of claim 21, further comprising a verification module coupled to the RF sensor and configured to analyze the electromagnetic field passing through the object to determine whether the at least one characteristic of the electromagnetic field passing through the object is associated with a live finger.
  • 23. The apparatus of claim 19, wherein the live finger sensor includes a first pickup plate configured to detect a first intensity associated with the electromagnetic field, and a second pickup plate configured to detect a second intensity associated with the electromagnetic field.
  • 24. The apparatus of claim 19, wherein the object comprises a finger and further comprising a fingerprint sensor configured to read a fingerprint pattern associated with the object, wherein live finger detection and fingerprint sensing are performed at the same time.
  • 25. A method comprising: injecting a radio frequency signal into a plurality of drive plates configured to transmit radio frequency energy to a respective one of a plurality of drive plate contact points in an array of drive plate contact points;detecting with a pickup plate, separated from each respective drive plate contact point by an injection gap, each respective drive plate and the pickup plate configured to transform the radio frequency energy into an electromagnetic field extending between the respective drive plate and the pickup plate across the respective injection gap, and the pickup plate configured to receive a modified-electromagnetic field, modified by passing through an object spanning the respective injection gap; anddetermining with a sensor coupled to the pickup plate whether the object is a live finger based on at least one characteristic of the electromagnetic field passing through the object and received at the pickup plate.
  • 26. The method of claim 25, wherein an intensity of the electromagnetic field is detected at a predetermined distance from a surface of the object.
  • 27. The method of claim 25, further comprising generating a signal indicating whether the object is a live finger.
  • 28. The method of claim 25, wherein the radio frequency signal has a frequency in the range of 10-30 MHz.
  • 29. A non-transitory machine readable medium storing instructions that, when executed by a computing device, cause the computing device to perform a method, the method comprising: injecting a radio frequency signal into a plurality of drive plates configured to transmit radio frequency energy to a respective one of a plurality of drive plate contact points in an array of drive plate contact points;detecting from a pickup plate, separated from each respective drive plate contact point by an injection gap, each respective drive plate and the pickup plate configured to transform the radio frequency energy into an electromagnetic field extending between the respective drive plate and the pickup plate extending across the respective injection gap, a modified electromagnetic field, modified by passing through an object spanning the respective pixel gap; anddetermining whether the object is a live finger based on at least one characteristic of the electromagnetic field passing through the object received from a sensor coupled to the pickup plate.
US Referenced Citations (380)
Number Name Date Kind
4151512 Riganati et al. Apr 1979 A
4225850 Chang et al. Sep 1980 A
4310827 Asi Jan 1982 A
4353056 Tsikos Oct 1982 A
4405829 Rivest et al. Sep 1983 A
4525859 Bowles et al. Jun 1985 A
4550221 Mabusth Oct 1985 A
4580790 Doose Apr 1986 A
4582985 Loftberg Apr 1986 A
4758622 Gosselin Jul 1988 A
4817183 Sparrow Mar 1989 A
5076566 Kriegel Dec 1991 A
5109427 Yang Apr 1992 A
5140642 Hsu et al. Aug 1992 A
5305017 Gerpheide Apr 1994 A
5319323 Fong Jun 1994 A
5325442 Knapp Jun 1994 A
5420936 Fitzpatrick et al. May 1995 A
5422807 Mitra et al. Jun 1995 A
5456256 Schneider et al. Oct 1995 A
5543591 Gillespie et al. Aug 1996 A
5569901 Bridgelall et al. Oct 1996 A
5623552 Lane Apr 1997 A
5627316 De Winter et al. May 1997 A
5650842 Maase et al. Jul 1997 A
5717777 Wong et al. Feb 1998 A
5781651 Hsiao et al. Jul 1998 A
5801681 Sayag Sep 1998 A
5818956 Tuli Oct 1998 A
5838306 O'Connor Nov 1998 A
5848176 Hara et al. Dec 1998 A
5850450 Schweitzer et al. Dec 1998 A
5852670 Setlak et al. Dec 1998 A
5864296 Upton Jan 1999 A
5887343 Salatino et al. Mar 1999 A
5892824 Beatson et al. Apr 1999 A
5903225 Schmitt et al. May 1999 A
5915757 Tsuyama et al. Jun 1999 A
5920384 Borza Jul 1999 A
5920640 Salatino et al. Jul 1999 A
5940526 Setlak et al. Aug 1999 A
5963679 Setlak Oct 1999 A
5999637 Toyoda et al. Dec 1999 A
6002815 Immega et al. Dec 1999 A
6016355 Dickinson et al. Jan 2000 A
6052475 Upton Apr 2000 A
6067368 Setlak et al. May 2000 A
6073343 Petrick et al. Jun 2000 A
6076566 Lowe Jun 2000 A
6088585 Schmitt et al. Jul 2000 A
6098175 Lee Aug 2000 A
6118318 Fifield et al. Sep 2000 A
6134340 Hsu et al. Oct 2000 A
6157722 Lerner et al. Dec 2000 A
6161213 Lofstrom Dec 2000 A
6175407 Santor Jan 2001 B1
6182076 Yu et al. Jan 2001 B1
6182892 Angelo et al. Feb 2001 B1
6185318 Jain et al. Feb 2001 B1
6234031 Suga May 2001 B1
6241288 Bergenek et al. Jun 2001 B1
6259108 Antonelli et al. Jul 2001 B1
6289114 Mainguet Sep 2001 B1
6292272 Okauchi et al. Sep 2001 B1
6317508 Kramer et al. Nov 2001 B1
6320394 Tartagni Nov 2001 B1
6325285 Baratelli Dec 2001 B1
6332193 Glass et al. Dec 2001 B1
6333989 Borza Dec 2001 B1
6337919 Duton Jan 2002 B1
6346739 Lepert et al. Feb 2002 B1
6347040 Fries et al. Feb 2002 B1
6357663 Takahashi et al. Mar 2002 B1
6360004 Akizuki Mar 2002 B1
6362633 Tartagni Mar 2002 B1
6392636 Ferrari et al. May 2002 B1
6399994 Shobu Jun 2002 B2
6400836 Senior Jun 2002 B2
6408087 Kramer Jun 2002 B1
6473072 Comiskey et al. Oct 2002 B1
6509501 Eicken et al. Jan 2003 B2
6525547 Hayes Feb 2003 B2
6525932 Ohnishi et al. Feb 2003 B1
6539101 Black Mar 2003 B1
6580816 Kramer et al. Jun 2003 B2
6597289 Sabatini Jul 2003 B2
6628812 Setlak et al. Sep 2003 B1
6631201 Dickinson et al. Oct 2003 B1
6643389 Raynal et al. Nov 2003 B1
6672174 Deconde et al. Jan 2004 B2
6710461 Chou et al. Mar 2004 B2
6738050 Comiskey et al. May 2004 B2
6741729 Bjorn et al. May 2004 B2
6757002 Oross et al. Jun 2004 B1
6766040 Catalano et al. Jul 2004 B1
6785407 Tschudi et al. Aug 2004 B1
6836230 Le Pailleur et al. Dec 2004 B2
6838905 Doyle Jan 2005 B1
6873356 Kanbe et al. Mar 2005 B1
6886104 McClurg et al. Apr 2005 B1
6897002 Teraoka et al. May 2005 B2
6898299 Brooks May 2005 B1
6924496 Manansala Aug 2005 B2
6937748 Schneider et al. Aug 2005 B1
6941001 Bolle et al. Sep 2005 B1
6941810 Okada Sep 2005 B2
6950540 Higuchi Sep 2005 B2
6959874 Bardwell Nov 2005 B2
6963626 Shaeffer et al. Nov 2005 B1
6970584 O'Gorman et al. Nov 2005 B2
6980672 Saito et al. Dec 2005 B2
6983882 Cassone Jan 2006 B2
7013030 Wong et al. Mar 2006 B2
7020591 Wei et al. Mar 2006 B1
7030860 Hsu et al. Apr 2006 B1
7031670 May Apr 2006 B2
7035443 Wong Apr 2006 B2
7042535 Katoh et al. May 2006 B2
7043061 Hamid et al. May 2006 B2
7043644 DeBruine May 2006 B2
7046230 Zadesky et al. May 2006 B2
7064743 Nishikawa Jun 2006 B2
7099496 Benkley Aug 2006 B2
7110574 Haruki et al. Sep 2006 B2
7110577 Tschud Sep 2006 B1
7113622 Hamid Sep 2006 B2
7126389 McRae et al. Oct 2006 B1
7129926 Mathiassen et al. Oct 2006 B2
7136514 Wong Nov 2006 B1
7146024 Benkley Dec 2006 B2
7146026 Russon et al. Dec 2006 B2
7146029 Manansala Dec 2006 B2
7184581 Johansen et al. Feb 2007 B2
7190816 Mitsuyu et al. Mar 2007 B2
7194392 Tuken et al. Mar 2007 B2
7197168 Russo Mar 2007 B2
7200250 Chou Apr 2007 B2
7251351 Mathiassen et al. Jul 2007 B2
7258279 Schneider et al. Aug 2007 B2
7260246 Fujii Aug 2007 B2
7263212 Kawabe Aug 2007 B2
7263213 Rowe Aug 2007 B2
7289649 Walley et al. Oct 2007 B1
7290323 Deconde et al. Nov 2007 B2
7308121 Mathiassen et al. Dec 2007 B2
7308122 McClurg et al. Dec 2007 B2
7321672 Sasaki et al. Jan 2008 B2
7356169 Hamid Apr 2008 B2
7360688 Harris Apr 2008 B1
7369685 DeLean May 2008 B2
7379569 Chikazawa et al. May 2008 B2
7408135 Fujieda Aug 2008 B2
7409876 Ganapathi et al. Aug 2008 B2
7412083 Takahashi Aug 2008 B2
7424618 Roy et al. Sep 2008 B2
7447339 Mimura et al. Nov 2008 B2
7447911 Chou et al. Nov 2008 B2
7460697 Erhart et al. Dec 2008 B2
7463756 Benkley Dec 2008 B2
7505611 Fyke Mar 2009 B2
7505613 Russo Mar 2009 B2
7565548 Fiske et al. Jul 2009 B2
7574022 Russo Aug 2009 B2
7596832 Hsieh et al. Oct 2009 B2
7643950 Getzin et al. Jan 2010 B1
7646897 Fyke Jan 2010 B2
7681232 Nordentoft et al. Mar 2010 B2
7689013 Shinzaki Mar 2010 B2
7706581 Drews et al. Apr 2010 B2
7733697 Picca et al. Jun 2010 B2
7751601 Benkley Jul 2010 B2
7843438 Onoda Nov 2010 B2
7848798 Martinsen et al. Dec 2010 B2
7899216 Watanabe et al. Mar 2011 B2
7953258 Dean et al. May 2011 B2
8005276 Dean et al. Aug 2011 B2
8031916 Abiko et al. Oct 2011 B2
8077935 Geoffroy et al. Dec 2011 B2
8107212 Nelson et al. Jan 2012 B2
8116540 Dean et al. Feb 2012 B2
8131026 Benkley et al. Mar 2012 B2
8165355 Benkley et al. Apr 2012 B2
8175345 Gardner May 2012 B2
8204281 Satya et al. Jun 2012 B2
8224044 Benkley Jul 2012 B2
8229184 Benkley Jul 2012 B2
20010026636 Mainget Oct 2001 A1
20010030644 Allport Oct 2001 A1
20010036299 Senior Nov 2001 A1
20010043728 Kramer et al. Nov 2001 A1
20020025062 Black Feb 2002 A1
20020061125 Fujii May 2002 A1
20020064892 Lepert et al. May 2002 A1
20020067845 Griffis Jun 2002 A1
20020073046 David Jun 2002 A1
20020089044 Simmons et al. Jul 2002 A1
20020089410 Janiak et al. Jul 2002 A1
20020096731 Wu et al. Jul 2002 A1
20020122026 Bergstrom Sep 2002 A1
20020126516 Jeon Sep 2002 A1
20020133725 Roy et al. Sep 2002 A1
20020152048 Hayes Oct 2002 A1
20020181749 Matsumoto et al. Dec 2002 A1
20030002717 Hamid Jan 2003 A1
20030002719 Hamid et al. Jan 2003 A1
20030021495 Cheng Jan 2003 A1
20030035570 Benkley Feb 2003 A1
20030063782 Acharya et al. Apr 2003 A1
20030068072 Hamid Apr 2003 A1
20030076301 Tsuk et al. Apr 2003 A1
20030076303 Huppi Apr 2003 A1
20030095096 Robbin et al. May 2003 A1
20030095690 Su et al. May 2003 A1
20030102874 Lane et al. Jun 2003 A1
20030123714 O'Gorman et al. Jul 2003 A1
20030123715 Uchida Jul 2003 A1
20030141959 Keogh et al. Jul 2003 A1
20030147015 Katoh et al. Aug 2003 A1
20030161510 Fuji Aug 2003 A1
20030161512 Mathiassen et al. Aug 2003 A1
20030169228 Mathiassen et al. Sep 2003 A1
20030174871 Yoshioka et al. Sep 2003 A1
20030186157 Teraoka et al. Oct 2003 A1
20030209293 Sako et al. Nov 2003 A1
20030224553 Manansala Dec 2003 A1
20040012773 Puttkammer Jan 2004 A1
20040017934 Kocher Jan 2004 A1
20040022001 Chu et al. Feb 2004 A1
20040042642 Bolle et al. Mar 2004 A1
20040050930 Rowe Mar 2004 A1
20040066613 Leitao Apr 2004 A1
20040076313 Bronstein et al. Apr 2004 A1
20040081339 Benkley Apr 2004 A1
20040096086 Miyasaka et al. May 2004 A1
20040113956 Bellwood et al. Jun 2004 A1
20040120400 Linzer Jun 2004 A1
20040125993 Zhao et al. Jul 2004 A1
20040129787 Saito Jul 2004 A1
20040136612 Meister et al. Jul 2004 A1
20040155752 Radke Aug 2004 A1
20040172339 Snelgrove et al. Sep 2004 A1
20040179718 Chou Sep 2004 A1
20040184641 Nagasaka et al. Sep 2004 A1
20040190761 Lee Sep 2004 A1
20040208346 Baharav et al. Oct 2004 A1
20040208347 Baharav et al. Oct 2004 A1
20040208348 Baharav et al. Oct 2004 A1
20040213441 Tschudi Oct 2004 A1
20040215689 Dooley et al. Oct 2004 A1
20040228505 Sugimoto Nov 2004 A1
20040228508 Shigeta Nov 2004 A1
20040240712 Rowe et al. Dec 2004 A1
20040252867 Lan et al. Dec 2004 A1
20050036665 Higuchi Feb 2005 A1
20050047485 Khayrallah et al. Mar 2005 A1
20050100196 Scott et al. May 2005 A1
20050100938 Hofmann et al. May 2005 A1
20050109835 Jacoby et al. May 2005 A1
20050110103 Setlak May 2005 A1
20050111708 Chou May 2005 A1
20050123176 Ishil et al. Jun 2005 A1
20050129291 Boshra Jun 2005 A1
20050136200 Durell et al. Jun 2005 A1
20050139656 Arnouse Jun 2005 A1
20050139685 Kozlay Jun 2005 A1
20050162402 Watanachote Jul 2005 A1
20050169503 Howell et al. Aug 2005 A1
20050174015 Scott et al. Aug 2005 A1
20050210271 Chou et al. Sep 2005 A1
20050219200 Weng Oct 2005 A1
20050220329 Payne et al. Oct 2005 A1
20050231213 Chou et al. Oct 2005 A1
20050238212 Du et al. Oct 2005 A1
20050244038 Benkley Nov 2005 A1
20050244039 Geoffroy et al. Nov 2005 A1
20050247559 Frey et al. Nov 2005 A1
20050249386 Juh Nov 2005 A1
20050258952 Utter et al. Nov 2005 A1
20050269402 Spitzer et al. Dec 2005 A1
20060006224 Modi Jan 2006 A1
20060055500 Burke et al. Mar 2006 A1
20060066572 Yumoto et al. Mar 2006 A1
20060078176 Abiko et al. Apr 2006 A1
20060083411 Benkley Apr 2006 A1
20060110537 Huang et al. May 2006 A1
20060140461 Kim et al. Jun 2006 A1
20060144953 Takao Jul 2006 A1
20060170528 Fukushige et al. Aug 2006 A1
20060187200 Martin Aug 2006 A1
20060210082 Devadas et al. Sep 2006 A1
20060214512 Iwata Sep 2006 A1
20060239514 Watanabe et al. Oct 2006 A1
20060249008 Luther Nov 2006 A1
20060259873 Mister Nov 2006 A1
20060261174 Zellner et al. Nov 2006 A1
20060267385 Steenwyk et al. Nov 2006 A1
20060271793 Devadas et al. Nov 2006 A1
20060287963 Steeves et al. Dec 2006 A1
20070031011 Erhart et al. Feb 2007 A1
20070036400 Watanabe et al. Feb 2007 A1
20070057763 Blattner et al. Mar 2007 A1
20070067828 Bychkov Mar 2007 A1
20070076926 Schneider et al. Apr 2007 A1
20070076951 Tanaka et al. Apr 2007 A1
20070086634 Setlak et al. Apr 2007 A1
20070090312 Stallinga et al. Apr 2007 A1
20070138299 Mitra Jun 2007 A1
20070160269 Kuo Jul 2007 A1
20070180261 Akkermans et al. Aug 2007 A1
20070196002 Choi et al. Aug 2007 A1
20070198141 Moore Aug 2007 A1
20070198435 Siegal et al. Aug 2007 A1
20070228154 Tran Oct 2007 A1
20070237366 Maletsky Oct 2007 A1
20070248249 Stoianov Oct 2007 A1
20080002867 Mathiassen et al. Jan 2008 A1
20080013805 Sengupta et al. Jan 2008 A1
20080019578 Saito et al. Jan 2008 A1
20080049987 Champagne et al. Feb 2008 A1
20080049989 Iseri et al. Feb 2008 A1
20080063245 Benkley et al. Mar 2008 A1
20080069412 Champagne et al. Mar 2008 A1
20080126260 Cox et al. May 2008 A1
20080169345 Keane et al. Jul 2008 A1
20080170695 Adler et al. Jul 2008 A1
20080175450 Scott et al. Jul 2008 A1
20080178008 Takahashi et al. Jul 2008 A1
20080179112 Qin et al. Jul 2008 A1
20080185429 Saville Aug 2008 A1
20080201265 Hewton Aug 2008 A1
20080205714 Benkley et al. Aug 2008 A1
20080219521 Benkley et al. Sep 2008 A1
20080222049 Loomis et al. Sep 2008 A1
20080223925 Saito et al. Sep 2008 A1
20080226132 Gardner Sep 2008 A1
20080240523 Benkley et al. Oct 2008 A1
20080244277 Orsini et al. Oct 2008 A1
20080267462 Nelson et al. Oct 2008 A1
20080279373 Erhart et al. Nov 2008 A1
20080317290 Tazoe Dec 2008 A1
20090130369 Huang et al. May 2009 A1
20090153297 Gardner Jun 2009 A1
20090154779 Satyan et al. Jun 2009 A1
20090155456 Benkley et al. Jun 2009 A1
20090169071 Bond et al. Jul 2009 A1
20090174974 Huang et al. Jul 2009 A1
20090237135 Ramaraju et al. Sep 2009 A1
20090252384 Dean et al. Oct 2009 A1
20090252385 Dean et al. Oct 2009 A1
20090252386 Dean et al. Oct 2009 A1
20090279742 Abiko Nov 2009 A1
20090319435 Little et al. Dec 2009 A1
20090324028 Russo Dec 2009 A1
20100026451 Erhart et al. Feb 2010 A1
20100045705 Vertegaal et al. Feb 2010 A1
20100083000 Kesanupalli et al. Apr 2010 A1
20100119124 Satyan May 2010 A1
20100123675 Ippel May 2010 A1
20100127366 Bond et al. May 2010 A1
20100176823 Thompson et al. Jul 2010 A1
20100176892 Thompson et al. Jul 2010 A1
20100177940 Thompson et al. Jul 2010 A1
20100180136 Thompson et al. Jul 2010 A1
20100208953 Gardner et al. Aug 2010 A1
20100244166 Shibuta et al. Sep 2010 A1
20100272329 Benkley Oct 2010 A1
20100284565 Benkley et al. Nov 2010 A1
20110002461 Erhart et al. Jan 2011 A1
20110018556 Le et al. Jan 2011 A1
20110090047 Patel Apr 2011 A1
20110102567 Erhart May 2011 A1
20110102569 Erhart May 2011 A1
20110175703 Benkley Jul 2011 A1
20110176307 Benkley Jul 2011 A1
20110182486 Valfridsson et al. Jul 2011 A1
20110214924 Perezselsky et al. Sep 2011 A1
20110267298 Erhart et al. Nov 2011 A1
20110298711 Dean et al. Dec 2011 A1
20110304001 Erhart et al. Dec 2011 A1
20120044639 Garcia Feb 2012 A1
Foreign Referenced Citations (65)
Number Date Country
2213813 Oct 1973 DE
0929028 Jan 1998 EP
0905646 Mar 1999 EP
0973123 Jan 2000 EP
1018697 Jul 2000 EP
1139301 Oct 2001 EP
1531419 May 2005 EP
1533759 May 2005 EP
1538548 Jun 2005 EP
1624399 Feb 2006 EP
1775674 Apr 2007 EP
1939788 Jul 2008 EP
2343677 Jul 2011 EP
2343679 Jul 2011 EP
2331613 May 1999 GB
2480919 Dec 2011 GB
01094418 Apr 1989 JP
04158434 Jun 1992 JP
2005011002 Jan 2005 JP
2005242856 Sep 2005 JP
2007305097 Nov 2007 JP
200606745 Feb 2006 TW
200620140 Jun 2006 TW
200629167 Aug 2006 TW
WO 9003620 Apr 1990 WO
WO 9858342 Dec 1998 WO
WO 9928701 Jun 1999 WO
WO 9943258 Sep 1999 WO
WO 0122349 Mar 2001 WO
WO 0194902 Dec 2001 WO
WO 0194902 Dec 2001 WO
WO 0195304 Dec 2001 WO
WO 0211066 Feb 2002 WO
WO 0247018 Jun 2002 WO
WO 0247018 Jun 2002 WO
WO 02061668 Aug 2002 WO
WO 02077907 Oct 2002 WO
WO 03063054 Jul 2003 WO
WO 03075210 Sep 2003 WO
WO 2004066194 Aug 2004 WO
WO 2004066693 Aug 2004 WO
WO 20050104012 Nov 2005 WO
WO 2005106774 Nov 2005 WO
WO 2005106774 Nov 2005 WO
WO 2006040724 Apr 2006 WO
WO 2006041780 Apr 2006 WO
WO 2007011607 Jan 2007 WO
WO 2008033264 Mar 2008 WO
WO 2008033264 Mar 2008 WO
WO 2008033265 Jun 2008 WO
WO 2008033265 Jun 2008 WO
WO 2008137287 Nov 2008 WO
WO 2009002599 Dec 2008 WO
WO 2009002599 Dec 2008 WO
WO 2009029257 Jun 2009 WO
WO 2009079219 Jun 2009 WO
WO 2009079221 Jun 2009 WO
WO 2009079257 Jun 2009 WO
WO 2009079262 Jun 2009 WO
WO 2010034036 Mar 2010 WO
WO 2010036445 Apr 2010 WO
WO 2010143597 Dec 2010 WO
WO 2011088248 Jan 2011 WO
WO2011088252 Jan 2011 WO
WO 2011053797 May 2011 WO
Non-Patent Literature Citations (16)
Entry
Matsumoto et al., Impact of Artificial “Gummy” Fingers on Fingerprint Systems, SPIE 4677 (2002), reprinted from cryptome.org.
Maltoni, “Handbook of Fingerprint Recognition”, XP002355942 Springer, New York, USA, Jun. 2003 pp. 65-69.
Vermasan, et al., “A500 dpi AC Capacitive Hybrid Flip-Chip CMOS ASIC/Sensor Module for Fingerprint, Navigation, and Pointer Detection With On-Chip Data Processing”, IEEE Journal of Solid State Circuits, vol. 38, No. 12, Dec. 2003, pp. 2288-2294.
Ratha, et al. “Adaptive Flow Orientation Based Feature Extraction in Fingerprint Images,” Pattern Recognition, vol. 28 No. 11, 1657-1672, Nov. 1995.
Ratha, et al., “A Real Time Matching System for Large Fingerprint Databases,” IEEE, Aug. 1996.
Suh, et al., “Design and Implementation of the AEGIS Single-Chip Secure Processor Using Physical Random Functions”, Computer Architecture, 2005, ISCA '05, Proceedings, 32nd International Symposium, Jun. 2005 (MIT Technical Report CSAIL CSG-TR-843, 2004.
Rivest, et al., “A Method for Obtaining Digital Signatures and Public-Key Cryptosystems”, Communication of the ACM, vol. 21 (2), pp. 120-126. (1978).
Gassend, et al., “Controlled Physical Random Functions”, In Proceedings of the 18th Annual Computer Security Conference, Las Vegas, Nevada, Dec. 12, 2002.
Hiltgen, et al., “Secure Internet Banking Authentication”, IEEE Security and Privacy, IEEE Computer Society, New York, NY, US, Mar. 1, 2006, pp. 24-31, XP007908655, ISSN: 1540-7993.
Hegt, “Analysis of Current and Future Phishing Attacks on Internet Banking Services”, Mater Thesis. Techische Universiteit Eindhoven—Department of Mathematics and Computer Science May 31, 2008, pp. 1-149, XP002630374, Retrieved from the Internet: URL:http://alexandria.tue.nl/extral/afstversl/wsk-i/hgt2008.pdf [retrieved on Mar. 29, 2011] *pp. 127-134, paragraph 6.2*.
Wikipedia (Mar. 2003). “Integrated Circuit,” http://en.wikipedia.org/wiki/integrated—circuit. Revision as of Mar. 23, 2003.
Wikipedia (Dec. 2006). “Integrated circuit” Revision as of Dec. 10, 2006. http://en.widipedia.org/wiki/Integrated—circuit.
BELLAGIODESIGNS.COM (Internet Archive Wayback Machine, www.bellagiodesigns.com date: Oct. 29, 2005).
Closed Loop Systems, The Free Dictionary, http://www.thefreedictionary.com/closed-loop+system (downloaded Dec. 1, 2011).
Feedback: Electronic Engineering, Wikipedia, p. 5 http://en.wikipedia.org/wiki/Feedback#Electronic—engineering (downloaded Dec. 1, 2011).
Galy et al. (Jul. 2007) “A full fingerprint verification system for a single-line sweep sensor.” IEEE Sensors J., vol. 7 No. 7, pp. 1054-1065.
Related Publications (1)
Number Date Country
20100189314 A1 Jul 2010 US