WO2021071762A1 - Techniques pour la détection d'empreintes digitales et l'authentification d'utilisateur - Google Patents

Techniques pour la détection d'empreintes digitales et l'authentification d'utilisateur Download PDF

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Publication number
WO2021071762A1
WO2021071762A1 PCT/US2020/054198 US2020054198W WO2021071762A1 WO 2021071762 A1 WO2021071762 A1 WO 2021071762A1 US 2020054198 W US2020054198 W US 2020054198W WO 2021071762 A1 WO2021071762 A1 WO 2021071762A1
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WO
WIPO (PCT)
Prior art keywords
user
fingerprint
finger
array
touch sensor
Prior art date
Application number
PCT/US2020/054198
Other languages
English (en)
Inventor
John T. Apostolos
William Mouyos
James D. Logan
Original Assignee
AMI Research & Development, LLC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US16/595,017 external-priority patent/US11048786B2/en
Application filed by AMI Research & Development, LLC filed Critical AMI Research & Development, LLC
Priority to EP20874559.6A priority Critical patent/EP4042267A1/fr
Publication of WO2021071762A1 publication Critical patent/WO2021071762A1/fr

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
    • G06F3/041—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means
    • G06F3/044—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means by capacitive means

Definitions

  • This patent application relates to touchscreens and more particularly to techniques for detecting fingerprints and user authentication.
  • a typical touchscreen uses a projected capacitive grid structure where every electrode intersection can unambiguously be identified as a touch point or “cell”. As the user's finger slides up and down along the grid, the ridges and valleys of the finger also move across a small subset of these touch points.
  • - representing a fingerprint by prompting a user to swipe a finger along two or more paths on a sparse 2D touch array, detecting two or more one-dimensional (ID) time varying signal representative of ridge and valley detail from the sparse touch array for each swipe, and fusing the two or more ID signals together; - authenticating a user of a second device having a sparse ID touch sensor by detecting fingerprint information from the second device and forwarding the data for matching to a cloud processor or back to a first device with the sparse 2D touch array;
  • ID one-dimensional
  • detailed fingerprint information is obtained by operating a touch sensitive array in two modes.
  • touch sensitive elements of the array In a first mode, touch sensitive elements of the array to are scanned at a first rate to provide outputs sufficient to detect a position of the finger.
  • the touch sensitive elements of the array In a second mode, the touch sensitive elements of the array are scanned at a second rate higher than the first rate.
  • the second mode provides outputs from the array comprising a time-varying sequence of digital amplitude values that, over time, are representative of a ridge and valley detail of a rectangular portion of the fingerprint that passes adjacent the corresponding one of the touchscreen array elements as the person uses the touchscreen.
  • Kalman filtering can be used on the outputs of the array provided in the first to determine a likely position of the finger on subsequent scans.
  • the array may be a capacitive array comprising a set of parallel transmit electrodes located along a first axis in a first plane, and a set of parallel receive electrodes located along a second axis in a second plane, with the elements located adjacent where the transmit and receive electrodes cross.
  • the array may be a sparse array where a spacing between adjacent elements of the array is at least ten times greater than a ridge and valley spacing of the person’s fingerprint.
  • the outputs of the array obtained in the second mode may be matched against templates to authenticate the user.
  • the templates may each be two or more overlapping rectangular sub-templates. The sub-templates can be rotated independently of one another to improve the matching process.
  • Fig. l is a block diagram of a representative electronic system.
  • Figs. 2-1, 2-2, 2-3 and 2-4 illustrate a touch sensitive grid, a particular crosspoint, and the resulting signal produced by a ridge-valley detector as the finger moves past one of the crosspoints in the array.
  • Fig. 8 illustrates overlapping sub-templates.
  • Figs. 9A-9C are a swipe to unlock use case.
  • Fig. 11 is a logical flow for producing a set of fingerprint codes.
  • a finger or other conductive object may be used where the finger or conductive object causes an increase in measured capacitance at one or more electrodes, which may be arranged in a grid or other pattern.
  • a finger placed near an electrode of a capacitive sensor may introduce an additional capacitance to ground that increases the total capacitance between the electrode and ground.
  • the location of the finger can be determined based on the locations of one or more electrodes at which a change in measured capacitance is detected.
  • the grid 120 may consist of a 21 x 21 array, or a total of 421 crossovre points.
  • the A/D 320 can sample at 150,000 samples per second (sps)
  • gesture recognition 250 may only need to sample a smaller window adjacent the finger (say a 9 x 9 subset) of the entire 21 x 21 array.
  • a filtering algorithm such as a Kalman filter to a series of detected finger centroid locations.
  • This filtered information may then be used to provide a more accurate prediction of the next most likely positon of a moving finger in the middle of a swipe.
  • Amplitude data from two or more crossover points adjacent the current centroid may also be used to improve the estimate.
  • This filtered information may be used to better determine where the closest crossover points are likely to be on the next scan of the array, in turn improving the ability to accurately place the higher sampling rate periods B.
  • the Kalman filtering operation may be implemented in the touch coordinate detector 330.
  • Fig. 4 shows an example enrollment phase.
  • the process for obtaining a data set representing the enrolled, valid user may involve prompting a series of swipe inputs on the touch array 120. Each swipe results in a one-dimensional (ID) time-varying signal such signal 450 shown in Fig. 2-4.
  • the user may provide the series of swipes by following a deliberate pattern (such as the star pattern shown in Fig. 4 or other some other predetermined pattern), or the user may be prompted make a series of freeform swipe inputs anywhere they find comfortable.
  • time varying grayscale data shown in Fig. 2-4 may be maintained in the time domain signal; however in other instances this signal may be converted to a frequency domain representation to obtain phase information. It has been found that the phase information is also helpful in improving the fingerprint recognition process.
  • This fused data can then be used as the enrolled template against which the detected fingerprint data is matched during user authentication 370.
  • the authentication process 370 may be a “deep” learning process that continues to improve the representational surface / manifold with each subsequently detected swipe from a user who is already known to be authorized. For example, as the user engages in other operations with the device (such as interacting with an application 380 with finger swipes on the touch array) the new fingerprint data can be detected and fused with the existing data set.
  • a low-density sensor grid 120 without relying on finger motion to develop time-varying ID signals.
  • a user may simply tap the touchscreen and this event is still detected at one or more crossover points 502, 503, 504 closest to a centroid 501.
  • the three grayscale values resulting from this single tap plus the centroid X-Y information may then be used to provide at least a rough match via self-correlation against a previously enrolled data set. While detecting the 3 closest crossovers (or even the 9 closest crossovers) from a single tap is a very sparse sample of the fingerprint data, it may be sufficient to provide accurate authentication in some instances.
  • Self-correlating with a series of detected taps and associated centroids, collected as the user taps two or more places on the touchscreen while interacting with it, may provide further information for an improved user authentication 380. 5. Enrollment on touchscreen; detection on IoT device
  • Two approaches can be used to create a functional representation of, or an actual fingerprint image, which can then be registered as the reference against which subsequent data from user swipes can later be compared.

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Security & Cryptography (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Hardware Design (AREA)
  • Software Systems (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Image Input (AREA)
  • Collating Specific Patterns (AREA)
  • User Interface Of Digital Computer (AREA)

Abstract

Nous présentons plusieurs techniques uniques pour utiliser des réseaux de capteurs tactiles pour détecter des informations d'empreintes digitales et authentifier un utilisateur.
PCT/US2020/054198 2019-10-07 2020-10-05 Techniques pour la détection d'empreintes digitales et l'authentification d'utilisateur WO2021071762A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
EP20874559.6A EP4042267A1 (fr) 2019-10-07 2020-10-05 Techniques pour la détection d'empreintes digitales et l'authentification d'utilisateur

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US16/595,017 2019-10-07
US16/595,017 US11048786B2 (en) 2016-04-13 2019-10-07 Techniques for fingerprint detection and user authentication

Publications (1)

Publication Number Publication Date
WO2021071762A1 true WO2021071762A1 (fr) 2021-04-15

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Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2020/054198 WO2021071762A1 (fr) 2019-10-07 2020-10-05 Techniques pour la détection d'empreintes digitales et l'authentification d'utilisateur

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EP (1) EP4042267A1 (fr)
WO (1) WO2021071762A1 (fr)

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110261191A1 (en) * 2009-12-17 2011-10-27 Raytheon Company Textured pattern sensing and detection, and using a charge-scavenging photodiode array for the same
US20170032169A1 (en) * 2014-09-06 2017-02-02 Shenzhen Huiding Technology Co., Ltd. Swipe motion registration on a fingerprint sensor

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110261191A1 (en) * 2009-12-17 2011-10-27 Raytheon Company Textured pattern sensing and detection, and using a charge-scavenging photodiode array for the same
US20170032169A1 (en) * 2014-09-06 2017-02-02 Shenzhen Huiding Technology Co., Ltd. Swipe motion registration on a fingerprint sensor

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
A. LIBERT: "A lD Spectral Image Validation/Verification Metric for Fingerprints", NISTIR 7599, August 2009 (2009-08-01), pages 1 - 50, XP055817502 *

Also Published As

Publication number Publication date
EP4042267A1 (fr) 2022-08-17

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