WO2017117764A1 - Fingerprint imaging system and anti-fake method for fingerprint identification - Google Patents

Fingerprint imaging system and anti-fake method for fingerprint identification Download PDF

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Publication number
WO2017117764A1
WO2017117764A1 PCT/CN2016/070338 CN2016070338W WO2017117764A1 WO 2017117764 A1 WO2017117764 A1 WO 2017117764A1 CN 2016070338 W CN2016070338 W CN 2016070338W WO 2017117764 A1 WO2017117764 A1 WO 2017117764A1
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Prior art keywords
pulse wave
fingerprints
fingerprint
computed
computed pulse
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PCT/CN2016/070338
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French (fr)
Inventor
Ruixin LI
Hong Zhu
Yan LING
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Shanghai Oxi Technology Co., Ltd
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Application filed by Shanghai Oxi Technology Co., Ltd filed Critical Shanghai Oxi Technology Co., Ltd
Priority to PCT/CN2016/070338 priority Critical patent/WO2017117764A1/en
Publication of WO2017117764A1 publication Critical patent/WO2017117764A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/12—Fingerprints or palmprints
    • G06V40/1382—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger

Definitions

  • the present disclosure generally relates to fingerprint identification, and more particularly, to a fingerprint imaging system and an anti-fake method for fingerprint identification.
  • Fingerprint identification technology captures features of a fingerprint from a person via a fingerprint capturing apparatus and processes the features to form an image of the fingerprint. Thereafter, the image of the fingerprint is matched to a pre-stored fingerprint image so as to identify the captured fingerprint. Due to uniqueness of fingerprint and convenience of this technology, fingerprint identification has been widely used in many fields such as security inspections by police and customs, entrance guarding systems, personal computers, mobile phones, etc.
  • Embodiments of the present disclosure provide a fingerprint imaging system, which may include: a fingerprint capturing apparatus adapted to capture a set of fingerprints; and a processor configured to process the set of fingerprints captured by the fingerprint capturing apparatus after the set of fingerprints has been collected by the processor to obtain a computed pulse wave and match the computed pulse wave to a pre-stored pulse wave.
  • the processor may be further configured to convert each of the set of fingerprints into a gray scale image.
  • the processor may be further configured to compute multiple features of the computed pulse wave based on variation of the gray scale images and a capturing rate of the set of fingerprints, and construct the computed wave based on the multiple features of the computed pulse wave.
  • the processor is further configured to match two fingerprints, wherein one of the two fingerprints is obtained based on the set of fingerprints captured by the fingerprint capturing apparatus and the other of the two fingerprints is a pre-stored fingerprint.
  • Embodiments of the present disclosure further provide an anti-fake method for fingerprint identification, which may include: capturing a set of fingerprints; obtaining a computed pulse wave based on the set of fingerprints; and matching the computed pulse wave to a pre-stored pulse wave.
  • obtaining the computed pulse wave based on the set of fingerprints may include: converting each of the set of fingerprints into a gray scale image; and computing multiple features of the computed pulse wave based on variation of the gray scale images and a capturing rate of the set of fingerprints.
  • obtaining the computed pulse wave based on the set of fingerprints may further include: constructing the computed pulse wave based on the multiple features of the computed pulse wave.
  • the method may further include: matching a fingerprint obtained based on the captured set of fingerprints to a pre-stored fingerprint posterior to matching the computed pulse wave to the pre-stored pulse wave.
  • the method may further include: matching a fingerprint obtained based on the captured set of fingerprints to a pre-stored fingerprint prior to matching the computed pulse wave to the pre-stored pulse wave and posterior to obtaining the computed pulse wave based on the set of fingerprints.
  • the method may further include: matching a fingerprint obtained based on the captured set of fingerprints to a pre-stored fingerprint prior to obtaining the computed pulse wave based on the set of fingerprints and posterior to capturing the set of fingerprints.
  • the fingerprint identification fails, if failure of either matching the computed pulse wave to the pre-stored pulse wave or matching the fingerprint obtained based on the captured set of fingerprints to the pre-stored fingerprint is determined; and the fingerprint identification succeeds, if success of both matching the computed pulse wave to the pre-stored pulse wave and matching the fingerprint obtained based on the captured set of fingerprints to the pre-stored fingerprint are determined.
  • bogus fingerprints may be distinguished so as to enhance reliability of fingerprint identification.
  • FIG. 1 schematically illustrates a block diagram presenting a fingerprint imaging system according to one embodiment in the present disclosure
  • FIG. 2 schematically illustrates a flow diagram presenting an anti-fake method for fingerprint identification according to one embodiment in the present disclosure
  • FIG. 3 schematically illustrates a flow diagram presenting a method for obtaining the computed pulse wave based on the set of fingerprints according to one embodiment in the present disclosure.
  • FIG. 4 schematically illustrates a flow diagram presenting an anti-fake method for fingerprint identification according to another embodiment in the present disclosure.
  • FIG. 5 schematically illustrates a flow diagram presenting an anti-fake method for fingerprint identification according to another embodiment in the present disclosure.
  • Embodiments of the present disclosure provides a fingerprint imaging system, which may be configured for not only matching fingerprints but also matching pulse waves, and an anti-fake method for fingerprint identification via matching pulse waves. Therefore, bogus fingerprints may be distinguished so that reliability of fingerprint identification may be enhanced.
  • FIG. 1 schematically illustrates a block diagram presenting a fingerprint imaging system 100 according to one embodiment in the present disclosure.
  • the fingerprint imaging system 100 may include: a fingerprint capturing apparatus 101 adapted to capture a set of fingerprints; and a processor 103 configured to process the set of fingerprints captured by the fingerprint capturing apparatus 101 after the set of fingerprints has been collected by the processor 103 to obtain a computed pulse wave and match the computed pulse wave to a pre-stored pulse wave.
  • the pre-stored pulse wave may be stored in a non-transitory storage medium, where the non-transitory storage medium may be selected from a group including but being not limited to: a Read-Only Memory (ROM) , a Random Access Memory (RAM) , a flash memory, an Erasable Programmable ROM (EPROM) , an Electrically Erasable Programmable ROM (EEPROM) , a magnetic card, an optical card and any type of disk including a floppy disk, an optical disk, a Compact Disc-ROM (CD-ROM) and a magnetic-optical disk.
  • ROM Read-Only Memory
  • RAM Random Access Memory
  • EPROM Erasable Programmable ROM
  • EEPROM Electrically Erasable Programmable ROM
  • the fingerprint capturing apparatus 101 is adapted to capture at least 10 fingerprints in one second, where this capturing rate may guarantee a good accuracy of the computed pulse wave.
  • the fingerprint capturing apparatus 101 is adapted to start capturing fingerprints when a finger 105 is disposed on the fingerprint capturing apparatus 101, and the fingerprint capturing apparatus 101 is adapted to stop capturing fingerprints when the finger 105 loses contact with the fingerprint capturing apparatus 101.
  • the processor 103 is configured to process the set of fingerprints captured by the fingerprint capturing apparatus 101 may include: the processor 103 is configured to convert each of the set of fingerprints into a gray scale image.
  • gray scale of the gray scale image may be expressed using at least 8 bits ranging from 0 to 255, where 0 represents a color of black, 255 represents a color of white, and numbers in between represent colors of grey with different brightness. The smaller the number is the darker the color of grey is, and the larger the number is the lighter the color of grey is.
  • the processor 103 is configured to process the set of fingerprints captured by the fingerprint capturing apparatus 101 may further include: the processor 103 is configured to compute multiple features of the computed pulse wave based on variation of the gray scale images and a capturing rate of the set of fingerprints.
  • the multiple features may include but be not limited to: amplitudes of multiple points of the computed pulse wave, multiple slopes of the computed pulse wave and a pulse rate of the computed pulse wave.
  • the multiple points of the computed pulse wave may at least include multiple crests and multiple troughs of the computed pulse wave.
  • the multiple slopes of the computed pulse wave may at least include slopes of the multiple crests and slopes of the multiple troughs, where the slopes of the multiple crests and the slopes of the multiple troughs are zero.
  • the processor 103 is configured to process the set of fingerprints captured by the fingerprint capturing apparatus 101 may further include: the processor 103 is configured to construct the computed wave based on the multiple features of the computed pulse wave.
  • the processor 103 is configured to construct the computed wave based on the multiple features of the computed pulse wave. Specifically, the processor 103 is configured to construct the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave.
  • the processor 103 is configured to construct the computed wave based on the multiple features of the computed pulse wave. Specifically, the processor 103 is configured to construct the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave. Wherein, the processor 103 is configured to employ interpolation to construct the computed wave based on the multiple features of the computed pulse wave.
  • the processor 103 is configured to construct the computed wave based on the multiple features of the computed pulse wave. Specifically, the processor 103 is configured to construct the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave. Wherein, the processor 103 is configured to employ a reconstruction algorithm for constructing the computed wave based on the multiple features of the computed pulse wave.
  • the processor 103 is further configured to match two fingerprints, where one of the two fingerprints may be obtained based on the set of fingerprints captured by the fingerprint capturing apparatus 101 and the other of the two fingerprints may be a pre-stored fingerprint, which may be stored in the non-transitory storage medium.
  • the one of the two fingerprints obtained based on the set of fingerprints captured by the fingerprint capturing apparatus 101 may be an averaged fingerprint, where the averaged fingerprint may be obtained by averaging the set of fingerprints.
  • FIG. 2 schematically illustrates a flow diagram presenting an anti-fake method 200 for fingerprint identification according to one embodiment in the present disclosure.
  • the anti-fake method 200 may include:
  • step 201 capturing a set of fingerprints
  • step 203 obtaining a computed pulse wave based on the set of fingerprints.
  • step 205 matching the computed pulse wave to a pre-stored pulse wave.
  • the pre-stored pulse wave may be stored in a non-transitory storage medium, where the non-transitory storage medium may be selected from a group including but being not limited to: a Read-Only Memory (ROM) , a Random Access Memory (RAM) , a flash memory, an Erasable Programmable ROM (EPROM) , an Electrically Erasable Programmable ROM (EEPROM) , a magnetic card, an optical card and any type of disk including a floppy disk, an optical disk, a Compact Disc-ROM (CD-ROM) and a magnetic-optical disk.
  • ROM Read-Only Memory
  • RAM Random Access Memory
  • EPROM Erasable Programmable ROM
  • EEPROM Electrically Erasable Programmable ROM
  • the step 201 that capturing the set of fingerprints may include: capturing at least 10 fingerprints in one second, where this capturing rate may guarantee a good accuracy of the computed pulse wave.
  • capturing fingerprints may start when a finger is disposed on a fingerprint capturing apparatus and capturing fingerprints may end when the finger loses contact with the fingerprint capturing apparatus.
  • the anti-fake method 200 may further include:
  • step 207 matching a fingerprint obtained based on the set of fingerprints captured to a pre-stored fingerprint posterior to the step 205 that matching the computed pulse wave to the pre-stored pulse wave.
  • the pre-stored fingerprint may be stored in the non-transitory storage medium.
  • the one of the two fingerprints obtained based on the set of fingerprints captured may be an averaged fingerprint, where the averaged fingerprint may be obtained by averaging the set of fingerprints.
  • the fingerprint identification fails, if failure of either matching the computed pulse wave to the pre-stored pulse wave or matching the fingerprint obtained based on the captured set of fingerprints to the pre-stored fingerprint is determined; the fingerprint identification succeeds, if success of both matching the computed pulse wave to the pre-stored pulse wave and matching the fingerprint obtained based on the captured set of fingerprints to the pre-stored fingerprint are determined.
  • FIG. 3 schematically illustrates a flow diagram presenting a method 300 for obtaining the computed pulse wave based on the set of fingerprints according to one embodiment in the present disclosure.
  • the step 203 that obtaining the computed pulse wave based on the set of fingerprints may include:
  • step 301 converting each of the set of fingerprints into a gray scale image
  • step 303 computing multiple features of the computed pulse wave based on variation of the gray scale images and a capturing rate of the set of fingerprints.
  • gray scale of the gray scale image may be expressed using at least 8 bits ranging from 0 to 255, where 0 represents a color of black, 255 represents a color of white, and numbers in between represent colors of grey with different brightness. The smaller the number is the darker the color of grey is, and the larger the number is the lighter the color of grey is.
  • the multiple features may include but be not limited to: amplitudes of multiple points of the computed pulse wave, multiple slopes of the computed pulse wave and a pulse rate of the computed pulse wave.
  • the multiple points of the computed pulse wave may at least include multiple crests and multiple troughs of the computed pulse wave.
  • the multiple slopes of the computed pulse wave may at least include slopes of the multiple crests and slopes of the multiple troughs, where the slopes of the multiple crests and the slopes of the multiple troughs are zero.
  • the step 203 that obtaining the computed pulse wave based on the set of fingerprints may further include:
  • step 305 constructing the computed pulse wave based on the multiple features of the computed pulse wave.
  • the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave.
  • the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave, wherein interpolation may be employed to construct the computed wave based on the multiple features of the computed pulse wave.
  • the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave, wherein a reconstruction algorithm may be employed for constructing the computed wave based on the multiple features of the computed pulse wave.
  • FIG. 4 schematically illustrates a flow diagram presenting an anti-fake method 400 for fingerprint identification according to another embodiment in the present disclosure.
  • the anti-fake method 400 may include:
  • step 401 capturing a set of fingerprints
  • step 403 obtaining a computed pulse wave based on the set of fingerprints.
  • step 405 matching the computed pulse wave to a pre-stored pulse wave.
  • the pre-stored pulse wave may be stored in a non-transitory storage medium, where the non-transitory storage medium may be selected from a group including but being not limited to: a Read-Only Memory (ROM) , a Random Access Memory (RAM) , a flash memory, an Erasable Programmable ROM (EPROM) , an Electrically Erasable Programmable ROM (EEPROM) , a magnetic card, an optical card and any type of disk including a floppy disk, an optical disk, a Compact Disc-ROM (CD-ROM) and a magnetic-optical disk.
  • ROM Read-Only Memory
  • RAM Random Access Memory
  • EPROM Erasable Programmable ROM
  • EEPROM Electrically Erasable Programmable ROM
  • the step 401 that capturing the set of fingerprints may include: capturing at least 10 fingerprints in one second, where this capturing rate may guarantee a good accuracy of the computed pulse wave.
  • capturing fingerprints may start when a finger is disposed on a fingerprint capturing apparatus and capturing fingerprints may end when the finger loses contact with the fingerprint capturing apparatus.
  • the anti-fake method 400 may further include:
  • step 407 matching a fingerprint obtained based on the set of fingerprints to a pre-stored fingerprint prior to the step 405 that matching the computed pulse wave to the pre-stored pulse wave and posterior to the step 403 that obtaining the computed pulse wave based on the set of fingerprints.
  • the pre-stored fingerprint may be stored in the non-transitory storage medium.
  • the one of the two fingerprints obtained based on the set of fingerprints captured may be an averaged fingerprint, where the averaged fingerprint may be obtained by averaging the set of fingerprints.
  • the fingerprint identification fails, if failure of either matching the computed pulse wave to the pre-stored pulse wave or matching the fingerprint obtained based on the captured set of fingerprints to the pre-stored fingerprint is determined; the fingerprint identification succeeds, if success of both matching the computed pulse wave to the pre-stored pulse wave and matching the fingerprint obtained based on the captured set of fingerprints to the pre-stored fingerprint are determined.
  • the step 403 that obtaining the computed pulse wave based on the set of fingerprints may include:
  • step 301 converting each of the set of fingerprints into a gray scale image
  • step 303 computing multiple features of the computed pulse wave based on variation of the gray scale images and a capturing rate of the set of fingerprints.
  • gray scale of the gray scale image may be expressed using at least 8 bits ranging from 0 to 255, where 0 represents a color of black, 255 represents a color of white, and numbers in between represent colors of grey with different brightness. The smaller the number is the darker the color of grey is, and the larger the number is the lighter the color of grey is.
  • the multiple features may include but be not limited to: amplitudes of multiple points of the computed pulse wave, multiple slopes of the computed pulse wave and a pulse rate of the computed pulse wave.
  • the multiple points of the computed pulse wave may at least include multiple crests and multiple troughs of the computed pulse wave.
  • the multiple slopes of the computed pulse wave may at least include slopes of the multiple crests and slopes of the multiple troughs, where the slopes of the multiple crests and the slopes of the multiple troughs are zero.
  • the step 403 that obtaining the computed pulse wave based on the set of fingerprints may further include:
  • step 305 constructing the computed pulse wave based on the multiple features of the computed pulse wave.
  • the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave.
  • the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave, wherein interpolation may be employed to construct the computed wave based on the multiple features of the computed pulse wave.
  • the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave, wherein a reconstruction algorithm may be employed for constructing the computed wave based on the multiple features of the computed pulse wave.
  • FIG. 5 schematically illustrates a flow diagram presenting an anti-fake method 500 for fingerprint identification according to another embodiment in the present disclosure.
  • the anti-fake method 500 may include:
  • step 501 capturing a set of fingerprints
  • step 503 obtaining a computed pulse wave based on the set of fingerprints.
  • step 505 matching the computed pulse wave to a pre-stored pulse wave.
  • the pre-stored pulse wave may be stored in a non-transitory storage medium, where the non-transitory storage medium may be selected from a group including but being not limited to: a Read-Only Memory (ROM) , a Random Access Memory (RAM) , a flash memory, an Erasable Programmable ROM (EPROM) , an Electrically Erasable Programmable ROM (EEPROM) , a magnetic card, an optical card and any type of disk including a floppy disk, an optical disk, a Compact Disc-ROM (CD-ROM) and a magnetic-optical disk.
  • ROM Read-Only Memory
  • RAM Random Access Memory
  • EPROM Erasable Programmable ROM
  • EEPROM Electrically Erasable Programmable ROM
  • the step 501 that capturing the set of fingerprints may include: capturing at least 10 fingerprints in one second, where this capturing rate may guarantee a good accuracy of the computed pulse wave.
  • capturing fingerprints may start when a finger is disposed on a fingerprint capturing apparatus and capturing fingerprints may end when the finger loses contact with the fingerprint capturing apparatus.
  • the anti-fake method 500 may further include:
  • step 507 matching a fingerprint obtained based on the set of fingerprints captured to a pre-stored fingerprint prior to the step 503 that obtaining the computed pulse wave based on the set of fingerprints and posterior to the step 501 that capturing the set of fingerprints.
  • the pre-stored fingerprint may be stored in the non-transitory storage medium.
  • the one of the two fingerprints obtained based on the set of fingerprints captured may be an averaged fingerprint, where the averaged fingerprint may be obtained by averaging the set of fingerprints.
  • the fingerprint identification fails, if failure of either matching the computed pulse wave to the pre-stored pulse wave or matching the fingerprint obtained based on the captured set of fingerprints to the pre-stored fingerprint is determined; the fingerprint identification succeeds, if success of both matching the computed pulse wave to the pre-stored pulse wave and matching the fingerprint obtained based on the captured set of fingerprints to the pre-stored fingerprint are determined.
  • the step 503 that obtaining the computed pulse wave based on the set of fingerprints may include:
  • step 301 converting each of the set of fingerprints into a gray scale image
  • step 303 computing multiple features of the computed pulse wave based on variation of the gray scale images and a capturing rate of the set of fingerprints.
  • gray scale of the gray scale image may be expressed using at least 8 bits ranging from 0 to 255, where 0 represents a color of black, 255 represents a color of white, and numbers in between represent colors of grey with different brightness. The smaller the number is the darker the color of grey is, and the larger the number is the lighter the color of grey is.
  • the multiple features may include but be not limited to: amplitudes of multiple points of the computed pulse wave, multiple slopes of the computed pulse wave and a pulse rate of the computed pulse wave.
  • the multiple points of the computed pulse wave may at least include multiple crests and multiple troughs of the computed pulse wave.
  • the multiple slopes of the computed pulse wave may at least include slopes of the multiple crests and slopes of the multiple troughs, where the slopes of the multiple crests and the slopes of the multiple troughs are zero.
  • the step 503 that obtaining the computed pulse wave based on the set of fingerprints may further include:
  • step 305 constructing the computed pulse wave based on the multiple features of the computed pulse wave.
  • the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave.
  • the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave, wherein interpolation may be employed to construct the computed wave based on the multiple features of the computed pulse wave.
  • the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave, wherein a reconstruction algorithm may be employed for constructing the computed wave based on the multiple features of the computed pulse wave.

Abstract

Provided are a fingerprint imaging system and an anti-fake method for fingerprint identification. The system may include: a fingerprint capturing apparatus (101) adapted to capture a set of fingerprints; and a processor (103) configured to process the set of fingerprints captured by the fingerprint capturing apparatus after the set of fingerprints has been collected by the processor to obtain a computed pulse wave and match a computed pulse wave to a pre-stored pulse wave. The method may include: capturing a set of fingerprints; obtaining a computed pulse wave based on the set of fingerprints; and matching the computed pulse wave to a pre-stored pulse wave. Accordingly, bogus fingerprints may be distinguished so as to enhance reliability of fingerprint identification.

Description

FINGERPRINT IMAGING SYSTEM AND ANTI-FAKE METHOD FOR FINGERPRINT IDENTIFICATION TECHNICAL FIELD
 The present disclosure generally relates to fingerprint identification, and more particularly, to a fingerprint imaging system and an anti-fake method for fingerprint identification.
BACKGROUND
 Fingerprint identification technology captures features of a fingerprint from a person via a fingerprint capturing apparatus and processes the features to form an image of the fingerprint. Thereafter, the image of the fingerprint is matched to a pre-stored fingerprint image so as to identify the captured fingerprint. Due to uniqueness of fingerprint and convenience of this technology, fingerprint identification has been widely used in many fields such as security inspections by police and customs, entrance guarding systems, personal computers, mobile phones, etc.
SUMMARY
 Embodiments of the present disclosure provide a fingerprint imaging system, which may include: a fingerprint capturing apparatus adapted to capture a set of fingerprints； and a processor configured to process the set of fingerprints captured by the fingerprint capturing apparatus after the set of fingerprints has been collected by the processor to obtain a computed pulse wave and match the computed pulse wave to a pre-stored pulse wave.
 In some embodiments, the processor may be further configured to convert each of the set of fingerprints into a gray scale image.
 In some embodiments, the processor may be further configured to compute  multiple features of the computed pulse wave based on variation of the gray scale images and a capturing rate of the set of fingerprints, and construct the computed wave based on the multiple features of the computed pulse wave.
 In some embodiments, the processor is further configured to match two fingerprints, wherein one of the two fingerprints is obtained based on the set of fingerprints captured by the fingerprint capturing apparatus and the other of the two fingerprints is a pre-stored fingerprint.
 Embodiments of the present disclosure further provide an anti-fake method for fingerprint identification, which may include: capturing a set of fingerprints； obtaining a computed pulse wave based on the set of fingerprints； and matching the computed pulse wave to a pre-stored pulse wave.
 In some embodiments, obtaining the computed pulse wave based on the set of fingerprints may include: converting each of the set of fingerprints into a gray scale image； and computing multiple features of the computed pulse wave based on variation of the gray scale images and a capturing rate of the set of fingerprints.
 In some embodiments, obtaining the computed pulse wave based on the set of fingerprints may further include: constructing the computed pulse wave based on the multiple features of the computed pulse wave.
 In some embodiments, the method may further include: matching a fingerprint obtained based on the captured set of fingerprints to a pre-stored fingerprint posterior to matching the computed pulse wave to the pre-stored pulse wave.
 In some embodiments, the method may further include: matching a fingerprint obtained based on the captured set of fingerprints to a pre-stored fingerprint prior to matching the computed pulse wave to the pre-stored pulse wave and posterior to obtaining the computed pulse wave based on the set of fingerprints.
 In some embodiments, the method may further include: matching a  fingerprint obtained based on the captured set of fingerprints to a pre-stored fingerprint prior to obtaining the computed pulse wave based on the set of fingerprints and posterior to capturing the set of fingerprints.
 In some embodiments, the fingerprint identification fails, if failure of either matching the computed pulse wave to the pre-stored pulse wave or matching the fingerprint obtained based on the captured set of fingerprints to the pre-stored fingerprint is determined； and the fingerprint identification succeeds, if success of both matching the computed pulse wave to the pre-stored pulse wave and matching the fingerprint obtained based on the captured set of fingerprints to the pre-stored fingerprint are determined.
 Accordingly, embodiments of the present disclosure possess the following advantages: bogus fingerprints may be distinguished so as to enhance reliability of fingerprint identification.
BRIEF DESCRIPTION OF THE DRAWINGS
 FIG. 1 schematically illustrates a block diagram presenting a fingerprint imaging system according to one embodiment in the present disclosure；
 FIG. 2 schematically illustrates a flow diagram presenting an anti-fake method for fingerprint identification according to one embodiment in the present disclosure；
 FIG. 3 schematically illustrates a flow diagram presenting a method for obtaining the computed pulse wave based on the set of fingerprints according to one embodiment in the present disclosure.
 FIG. 4 schematically illustrates a flow diagram presenting an anti-fake method for fingerprint identification according to another embodiment in the present disclosure； and
 FIG. 5 schematically illustrates a flow diagram presenting an anti-fake method for fingerprint identification according to another embodiment in the present  disclosure.
DETAILED DESCRIPTION
 Embodiments of the present disclosure provides a fingerprint imaging system, which may be configured for not only matching fingerprints but also matching pulse waves, and an anti-fake method for fingerprint identification via matching pulse waves. Therefore, bogus fingerprints may be distinguished so that reliability of fingerprint identification may be enhanced.
 In order to clarify the objects, features and advantages of the present disclosure, the embodiments of the present disclosure will be described in detail in conjunction with the accompanying drawings.
 FIG. 1 schematically illustrates a block diagram presenting a fingerprint imaging system 100 according to one embodiment in the present disclosure.
 The fingerprint imaging system 100 may include: a fingerprint capturing apparatus 101 adapted to capture a set of fingerprints； and a processor 103 configured to process the set of fingerprints captured by the fingerprint capturing apparatus 101 after the set of fingerprints has been collected by the processor 103 to obtain a computed pulse wave and match the computed pulse wave to a pre-stored pulse wave. 
 Wherein, the pre-stored pulse wave may be stored in a non-transitory storage medium, where the non-transitory storage medium may be selected from a group including but being not limited to: a Read-Only Memory (ROM) , a Random Access Memory (RAM) , a flash memory, an Erasable Programmable ROM (EPROM) , an Electrically Erasable Programmable ROM (EEPROM) , a magnetic card, an optical card and any type of disk including a floppy disk, an optical disk, a Compact Disc-ROM (CD-ROM) and a magnetic-optical disk.
 Specifically, the fingerprint capturing apparatus 101 is adapted to capture at least 10 fingerprints in one second, where this capturing rate may guarantee a good accuracy of the computed pulse wave.
 Specifically, the fingerprint capturing apparatus 101 is adapted to start capturing fingerprints when a finger 105 is disposed on the fingerprint capturing apparatus 101, and the fingerprint capturing apparatus 101 is adapted to stop capturing fingerprints when the finger 105 loses contact with the fingerprint capturing apparatus 101.
 Specifically, the processor 103 is configured to process the set of fingerprints captured by the fingerprint capturing apparatus 101 may include: the processor 103 is configured to convert each of the set of fingerprints into a gray scale image.
 Wherein, gray scale of the gray scale image may be expressed using at least 8 bits ranging from 0 to 255, where 0 represents a color of black, 255 represents a color of white, and numbers in between represent colors of grey with different brightness. The smaller the number is the darker the color of grey is, and the larger the number is the lighter the color of grey is.
 Specifically, the processor 103 is configured to process the set of fingerprints captured by the fingerprint capturing apparatus 101 may further include: the processor 103 is configured to compute multiple features of the computed pulse wave based on variation of the gray scale images and a capturing rate of the set of fingerprints.
 Wherein, the multiple features may include but be not limited to: amplitudes of multiple points of the computed pulse wave, multiple slopes of the computed pulse wave and a pulse rate of the computed pulse wave. Wherein, the multiple points of the computed pulse wave may at least include multiple crests and multiple troughs of the computed pulse wave. Wherein, the multiple slopes of the computed pulse wave may at least include slopes of the multiple crests and slopes of the multiple troughs, where the slopes of the multiple crests and the slopes of the multiple troughs are zero.
 Specifically, the processor 103 is configured to process the set of  fingerprints captured by the fingerprint capturing apparatus 101 may further include: the processor 103 is configured to construct the computed wave based on the multiple features of the computed pulse wave.
 In some embodiments, the processor 103 is configured to construct the computed wave based on the multiple features of the computed pulse wave. Specifically, the processor 103 is configured to construct the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave.
 In some embodiments, the processor 103 is configured to construct the computed wave based on the multiple features of the computed pulse wave. Specifically, the processor 103 is configured to construct the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave. Wherein, the processor 103 is configured to employ interpolation to construct the computed wave based on the multiple features of the computed pulse wave.
 In some embodiments, the processor 103 is configured to construct the computed wave based on the multiple features of the computed pulse wave. Specifically, the processor 103 is configured to construct the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave. Wherein, the processor 103 is configured to employ a reconstruction algorithm for constructing the computed wave based on the multiple features of the computed pulse wave.
 Specifically, the processor 103 is further configured to match two fingerprints, where one of the two fingerprints may be obtained based on the set of fingerprints captured by the fingerprint capturing apparatus 101 and the other of the two fingerprints may be a pre-stored fingerprint, which may be stored in the non-transitory storage medium.
 In some embodiments, the one of the two fingerprints obtained based on the  set of fingerprints captured by the fingerprint capturing apparatus 101 may be an averaged fingerprint, where the averaged fingerprint may be obtained by averaging the set of fingerprints.
 The embodiments of the present disclosure also provide an anti-fake method for fingerprint identification. FIG. 2 schematically illustrates a flow diagram presenting an anti-fake method 200 for fingerprint identification according to one embodiment in the present disclosure. The anti-fake method 200 may include:
step 201: capturing a set of fingerprints；
step 203: obtaining a computed pulse wave based on the set of fingerprints； and
step 205: matching the computed pulse wave to a pre-stored pulse wave.
 Wherein, the pre-stored pulse wave may be stored in a non-transitory storage medium, where the non-transitory storage medium may be selected from a group including but being not limited to: a Read-Only Memory (ROM) , a Random Access Memory (RAM) , a flash memory, an Erasable Programmable ROM (EPROM) , an Electrically Erasable Programmable ROM (EEPROM) , a magnetic card, an optical card and any type of disk including a floppy disk, an optical disk, a Compact Disc-ROM (CD-ROM) and a magnetic-optical disk.
 Specifically, the step 201 that capturing the set of fingerprints may include: capturing at least 10 fingerprints in one second, where this capturing rate may guarantee a good accuracy of the computed pulse wave.
 Specifically, in the step 201, capturing fingerprints may start when a finger is disposed on a fingerprint capturing apparatus and capturing fingerprints may end when the finger loses contact with the fingerprint capturing apparatus.
 The anti-fake method 200 may further include:
step 207: matching a fingerprint obtained based on the set of fingerprints captured to a pre-stored fingerprint posterior to the step 205 that matching the computed pulse wave to the pre-stored pulse wave.
 Wherein, the pre-stored fingerprint may be stored in the non-transitory storage medium.
 In some embodiments, the one of the two fingerprints obtained based on the set of fingerprints captured may be an averaged fingerprint, where the averaged fingerprint may be obtained by averaging the set of fingerprints.
 Specifically, the fingerprint identification fails, if failure of either matching the computed pulse wave to the pre-stored pulse wave or matching the fingerprint obtained based on the captured set of fingerprints to the pre-stored fingerprint is determined； the fingerprint identification succeeds, if success of both matching the computed pulse wave to the pre-stored pulse wave and matching the fingerprint obtained based on the captured set of fingerprints to the pre-stored fingerprint are determined.
 FIG. 3 schematically illustrates a flow diagram presenting a method 300 for obtaining the computed pulse wave based on the set of fingerprints according to one embodiment in the present disclosure.
 Referring to FIG. 3, the step 203 that obtaining the computed pulse wave based on the set of fingerprints may include:
step 301: converting each of the set of fingerprints into a gray scale image； and
step 303: computing multiple features of the computed pulse wave based on variation of the gray scale images and a capturing rate of the set of fingerprints.
 Wherein, in the step 301, gray scale of the gray scale image may be expressed using at least 8 bits ranging from 0 to 255, where 0 represents a color of black, 255 represents a color of white, and numbers in between represent colors of grey with different brightness. The smaller the number is the darker the color of grey is, and the larger the number is the lighter the color of grey is.
 Wherein, in the step 303, the multiple features may include but be not limited to: amplitudes of multiple points of the computed pulse wave, multiple  slopes of the computed pulse wave and a pulse rate of the computed pulse wave. Wherein, the multiple points of the computed pulse wave may at least include multiple crests and multiple troughs of the computed pulse wave. Wherein, the multiple slopes of the computed pulse wave may at least include slopes of the multiple crests and slopes of the multiple troughs, where the slopes of the multiple crests and the slopes of the multiple troughs are zero.
 Referring to FIG. 3, the step 203 that obtaining the computed pulse wave based on the set of fingerprints may further include:
step 305: constructing the computed pulse wave based on the multiple features of the computed pulse wave.
 In some embodiments, the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave.
 In some embodiments, the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave, wherein interpolation may be employed to construct the computed wave based on the multiple features of the computed pulse wave.
 In some embodiments, the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave, wherein a reconstruction algorithm may be employed for constructing the computed wave based on the multiple features of the computed pulse wave.
 The embodiments of the present disclosure also provide an anti-fake method for fingerprint identification. FIG. 4 schematically illustrates a flow diagram presenting an anti-fake method 400 for fingerprint identification according to another embodiment in the present disclosure. The anti-fake method 400 may include:
step 401: capturing a set of fingerprints；
step 403: obtaining a computed pulse wave based on the set of fingerprints； and
step 405: matching the computed pulse wave to a pre-stored pulse wave.
 Wherein, the pre-stored pulse wave may be stored in a non-transitory storage medium, where the non-transitory storage medium may be selected from a group including but being not limited to: a Read-Only Memory (ROM) , a Random Access Memory (RAM) , a flash memory, an Erasable Programmable ROM (EPROM) , an Electrically Erasable Programmable ROM (EEPROM) , a magnetic card, an optical card and any type of disk including a floppy disk, an optical disk, a Compact Disc-ROM (CD-ROM) and a magnetic-optical disk.
 Specifically, the step 401 that capturing the set of fingerprints may include: capturing at least 10 fingerprints in one second, where this capturing rate may guarantee a good accuracy of the computed pulse wave.
 Specifically, in the step 401, capturing fingerprints may start when a finger is disposed on a fingerprint capturing apparatus and capturing fingerprints may end when the finger loses contact with the fingerprint capturing apparatus.
 The anti-fake method 400 may further include:
step 407: matching a fingerprint obtained based on the set of fingerprints to a pre-stored fingerprint prior to the step 405 that matching the computed pulse wave to the pre-stored pulse wave and posterior to the step 403 that obtaining the computed pulse wave based on the set of fingerprints.
 Wherein, the pre-stored fingerprint may be stored in the non-transitory storage medium.
 In some embodiments, the one of the two fingerprints obtained based on the set of fingerprints captured may be an averaged fingerprint, where the averaged fingerprint may be obtained by averaging the set of fingerprints.
 Specifically, the fingerprint identification fails, if failure of either matching the computed pulse wave to the pre-stored pulse wave or matching the fingerprint obtained based on the captured set of fingerprints to the pre-stored fingerprint is determined； the fingerprint identification succeeds, if success of both matching the computed pulse wave to the pre-stored pulse wave and matching the fingerprint obtained based on the captured set of fingerprints to the pre-stored fingerprint are determined.
 Referring to FIG. 3, the step 403 that obtaining the computed pulse wave based on the set of fingerprints may include:
step 301: converting each of the set of fingerprints into a gray scale image； and
step 303: computing multiple features of the computed pulse wave based on variation of the gray scale images and a capturing rate of the set of fingerprints.
 Wherein, in the step 301, gray scale of the gray scale image may be expressed using at least 8 bits ranging from 0 to 255, where 0 represents a color of black, 255 represents a color of white, and numbers in between represent colors of grey with different brightness. The smaller the number is the darker the color of grey is, and the larger the number is the lighter the color of grey is.
 Wherein, in the step 303, the multiple features may include but be not limited to: amplitudes of multiple points of the computed pulse wave, multiple slopes of the computed pulse wave and a pulse rate of the computed pulse wave. Wherein, the multiple points of the computed pulse wave may at least include multiple crests and multiple troughs of the computed pulse wave. Wherein, the multiple slopes of the computed pulse wave may at least include slopes of the multiple crests and slopes of the multiple troughs, where the slopes of the multiple crests and the slopes of the multiple troughs are zero.
 Referring to FIG. 3, the step 403 that obtaining the computed pulse wave based on the set of fingerprints may further include:
step 305: constructing the computed pulse wave based on the multiple features of the computed pulse wave.
 In some embodiments, the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave.
 In some embodiments, the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave, wherein interpolation may be employed to construct the computed wave based on the multiple features of the computed pulse wave.
 In some embodiments, the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave, wherein a reconstruction algorithm may be employed for constructing the computed wave based on the multiple features of the computed pulse wave.
 The embodiments of the present disclosure also provide an anti-fake method for fingerprint identification. FIG. 5 schematically illustrates a flow diagram presenting an anti-fake method 500 for fingerprint identification according to another embodiment in the present disclosure. The anti-fake method 500 may include:
step 501: capturing a set of fingerprints；
step 503: obtaining a computed pulse wave based on the set of fingerprints； and
step 505: matching the computed pulse wave to a pre-stored pulse wave.
 Wherein, the pre-stored pulse wave may be stored in a non-transitory storage medium, where the non-transitory storage medium may be selected from a group including but being not limited to: a Read-Only Memory (ROM) , a Random Access Memory (RAM) , a flash memory, an Erasable Programmable ROM (EPROM) , an Electrically Erasable Programmable ROM (EEPROM) , a magnetic card, an optical card and any type of disk including a floppy disk, an optical disk, a Compact Disc-ROM (CD-ROM) and a magnetic-optical disk.
 Specifically, the step 501 that capturing the set of fingerprints may include: capturing at least 10 fingerprints in one second, where this capturing rate may guarantee a good accuracy of the computed pulse wave.
 Specifically, in the step 501, capturing fingerprints may start when a finger is disposed on a fingerprint capturing apparatus and capturing fingerprints may end when the finger loses contact with the fingerprint capturing apparatus.
 The anti-fake method 500 may further include:
step 507: matching a fingerprint obtained based on the set of fingerprints captured to a pre-stored fingerprint prior to the step 503 that obtaining the computed pulse wave based on the set of fingerprints and posterior to the step 501 that capturing the set of fingerprints.
 Wherein, the pre-stored fingerprint may be stored in the non-transitory storage medium.
 In some embodiments, the one of the two fingerprints obtained based on the set of fingerprints captured may be an averaged fingerprint, where the averaged fingerprint may be obtained by averaging the set of fingerprints.
 Specifically, the fingerprint identification fails, if failure of either matching the computed pulse wave to the pre-stored pulse wave or matching the fingerprint  obtained based on the captured set of fingerprints to the pre-stored fingerprint is determined； the fingerprint identification succeeds, if success of both matching the computed pulse wave to the pre-stored pulse wave and matching the fingerprint obtained based on the captured set of fingerprints to the pre-stored fingerprint are determined.
 Referring to FIG. 3, the step 503 that obtaining the computed pulse wave based on the set of fingerprints may include:
step 301: converting each of the set of fingerprints into a gray scale image； and
step 303: computing multiple features of the computed pulse wave based on variation of the gray scale images and a capturing rate of the set of fingerprints.
 Wherein, in the step 301, gray scale of the gray scale image may be expressed using at least 8 bits ranging from 0 to 255, where 0 represents a color of black, 255 represents a color of white, and numbers in between represent colors of grey with different brightness. The smaller the number is the darker the color of grey is, and the larger the number is the lighter the color of grey is.
 Wherein, in the step 303, the multiple features may include but be not limited to: amplitudes of multiple points of the computed pulse wave, multiple slopes of the computed pulse wave and a pulse rate of the computed pulse wave. Wherein, the multiple points of the computed pulse wave may at least include multiple crests and multiple troughs of the computed pulse wave. Wherein, the multiple slopes of the computed pulse wave may at least include slopes of the multiple crests and slopes of the multiple troughs, where the slopes of the multiple crests and the slopes of the multiple troughs are zero.
 Referring to FIG. 3, the step 503 that obtaining the computed pulse wave based on the set of fingerprints may further include:
step 305: constructing the computed pulse wave based on the multiple features of the computed pulse wave.
 In some embodiments, the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave.
 In some embodiments, the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave, wherein interpolation may be employed to construct the computed wave based on the multiple features of the computed pulse wave.
 In some embodiments, the step 305 that constructing the computed wave based on the multiple features of the computed pulse wave may include: constructing the computed wave based on the amplitudes of multiple points of the computed pulse wave, the multiple slopes of the computed pulse wave and the pulse rate of the computed pulse wave, wherein a reconstruction algorithm may be employed for constructing the computed wave based on the multiple features of the computed pulse wave.
 Although the present disclosure has been disclosed above with reference to preferred embodiments thereof, it should be understood by those skilled in the art that various changes may be made without departing from the spirit or scope of the disclosure. Accordingly, the present disclosure is not limited to the embodiments disclosed.

Claims (20)

  1. A fingerprint imaging system, comprising:
    a fingerprint capturing apparatus adapted to capture a set of fingerprints； and
    a processor configured to process the set of fingerprints captured by the fingerprint capturing apparatus after the set of fingerprints has been collected by the processor to obtain a computed pulse wave and match the computed pulse wave to a pre-stored pulse wave.
  2. The fingerprint imaging system according to claim 1, wherein the fingerprint capturing apparatus is adapted to capture at least 10 fingerprints in one second.
  3. The fingerprint imaging system according to claim 1, wherein the fingerprint capturing apparatus is adapted to start capturing fingerprints when a finger is disposed on the fingerprint capturing apparatus, and the fingerprint capturing apparatus is adapted to stop capturing fingerprints when the finger loses contact with the fingerprint capturing apparatus.
  4. The fingerprint imaging system according to claim 1, wherein the processor is further configured to convert each of the set of fingerprints into a gray scale image.
  5. The fingerprint imaging system according to claim 4, wherein the processor is further configured to compute a plurality of features of the computed pulse wave based on variation of the gray scale images and a capturing rate of the set of fingerprints.
  6. The fingerprint imaging system according to claim 5, wherein the plurality of features of the computed pulse wave are selected from a group comprising: amplitudes of a plurality of points of the computed pulse wave, a plurality of slopes of the computed pulse wave and a pulse rate of the computed pulse wave.
  7. The fingerprint imaging system according to claim 5, wherein the processor is further configured to construct the computed wave based on the plurality of features of the computed pulse wave.
  8. The fingerprint imaging system according to claim 1, wherein the processor is further configured to match two fingerprints, wherein one of the two fingerprints is obtained based on the set of fingerprints captured by the fingerprint capturing apparatus and the other of the two fingerprints is a pre-stored fingerprint.
  9. The fingerprint imaging system according to claim 8, wherein the one of the two fingerprints obtained from the set of fingerprints captured by the fingerprint capturing apparatus is an averaged fingerprint, where the averaged fingerprint is obtained by averaging the set of fingerprints.
  10. An anti-fake method for fingerprint identification, comprising:
    capturing a set of fingerprints；
    obtaining a computed pulse wave based on the set of fingerprints； and
    matching the computed pulse wave to a pre-stored pulse wave.
  11. The method according to claim 10, wherein capturing the set of fingerprints comprises: capturing at least 10 fingerprints in one second.
  12. The method according to claim 10, wherein obtaining the computed pulse wave based on the set of fingerprints comprises:
    converting each of the set of fingerprints into a gray scale image； and
    computing a plurality of features of the computed pulse wave based on variation of the gray scale images and a capturing rate of the set of fingerprints.
  13. The method according to claim 12, wherein the plurality of features of the computed pulse wave are selected from a group comprising: amplitudes of a  plurality of points of the computed pulse wave, a plurality of slopes of the computed pulse wave and a pulse rate of the computed pulse wave.
  14. The method according to claim 12, wherein obtaining the computed pulse wave based on the set of fingerprints further comprises: constructing the computed pulse wave based on the plurality of features of the computed pulse wave.
  15. The method according to claim 10, further comprising:
    matching a fingerprint obtained based on the set of fingerprints to a pre-stored fingerprint posterior to matching the computed pulse wave to the pre-stored pulse wave.
  16. The method according to claim 10, further comprising:
    matching a fingerprint obtained based on the set of fingerprints to a pre-stored fingerprint prior to matching the computed pulse wave to the pre-stored pulse wave and posterior to obtaining the computed pulse wave based on the set of fingerprints.
  17. The method according to claim 10, further comprising:
    matching a fingerprint obtained based on the set of fingerprints to a pre-stored fingerprint prior to obtaining the computed pulse wave based on the set of fingerprints and posterior to capturing the set of fingerprints.
  18. The method according to any one of claims 15 to 17, wherein the fingerprint obtained based on the set of fingerprints is an averaged fingerprint, where the averaged fingerprint is obtained by averaging the set of fingerprints.
  19. The method according to any one of claims 15 to 17, wherein the fingerprint identification fails, if failure of either matching the computed pulse wave to the pre-stored pulse wave or matching the fingerprint obtained based on the set of fingerprints to the pre-stored fingerprint is determined.
  20. The method according to any one of claims 15 to 17, wherein the fingerprint identification succeeds, if success of both matching the computed pulse wave to the pre-stored pulse wave and matching the fingerprint obtained based on the set of fingerprints to the pre-stored fingerprint are determined.
PCT/CN2016/070338 2016-01-07 2016-01-07 Fingerprint imaging system and anti-fake method for fingerprint identification WO2017117764A1 (en)

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