CN117391708B - Mobile payment identity authentication method and system based on organism sign - Google Patents
Mobile payment identity authentication method and system based on organism sign Download PDFInfo
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
- G06Q20/401—Transaction verification
- G06Q20/4014—Identity check for transactions
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
- G06Q20/401—Transaction verification
- G06Q20/4014—Identity check for transactions
- G06Q20/40145—Biometric identity checks
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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
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Abstract
The invention discloses a mobile payment identity authentication method and a system based on organism sign, which relate to the field of electronic authentication and comprise the following steps: user identity input is carried out, and user fingerprint input is carried out; when mobile payment is carried out, a first instruction is sent out, and verification fingerprints of users are obtained; a second instruction is sent to a user, an instruction video of the second instruction completed by the whole hand of the user is obtained, and the instruction video is analyzed; acquiring an infrared thermal imaging image of the whole hand of a user, and analyzing whether the infrared thermal imaging image is abnormal or not; comparing the correction lines of the verification fingerprint with the reference fingerprint; if the verification fingerprint is successfully compared with the reference fingerprint, the user identity associated with the reference fingerprint is called, and a payment password in the user identity is input to complete mobile payment. Through setting up instruction issue module, video verification module and infrared verification module, avoid the fingerprint of user to be stolen, cause unnecessary economic loss, simultaneously, also can strengthen the security of mobile payment.
Description
Technical Field
The invention relates to the technical field of electronic authentication, in particular to a mobile payment identity authentication method and system based on biological sign.
Background
In recent years, along with the development of information system construction in China, various new payment modes are layered in the payment industry, wherein mobile payment is one of the payment modes, and mobile payment is also called mobile phone payment, namely a service mode that users can use mobile terminals (mobile phones) which are widely popularized at present to carry out financial payment on consumed goods or services. The mobile payment at the current stage mainly comprises near field payment and remote payment, wherein the near field payment is to purchase articles and the like in a mobile phone card swiping mode; remote payment is a way to realize payment by sending payment instructions (e.g., internet banking, telephone banking, etc.) through a mobile phone.
Mobile payment is often performed using biometric authentication, such as fingerprint authentication, for convenience and rapidity. However, the fingerprint is easy to forge, and once the fake fingerprint passes verification, payment is completed, the fake fingerprint can cause economic loss, and the payment security is affected.
Disclosure of Invention
In order to solve the technical problems, the technical scheme provides a mobile payment identity authentication method and system based on biological sign, which solves the problems that fingerprints proposed in the background art are easy to forge, and the forged fingerprints can cause economic loss once payment is completed through verification, so that the payment safety is affected.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a mobile payment identity authentication method based on biological sign, comprising:
user identity input is carried out, wherein the user identity comprises age, gender, name and payment password, user fingerprint input is carried out, reference fingerprints are obtained, and the reference fingerprints of the user are associated with the user identity;
when mobile payment is carried out, a first instruction is sent, the first instruction designates a hand and a finger of a fingerprint for verification, and a verification fingerprint of a user is obtained;
generating a second instruction set, randomly selecting a second instruction from the second instruction set, sending the second instruction to a user, acquiring an instruction video of the second instruction completed by the whole hand of the user, analyzing the instruction video, judging whether the hand of the user participating in mobile payment is real or not, if not, interrupting the mobile payment, and switching the payment mode into password payment;
the hand of the fingerprint for verification, the hand for completing the second instruction and the hand of the user participating in mobile payment are the same hand;
if yes, acquiring an infrared thermal imaging image of the whole hand of the user, analyzing whether the infrared thermal imaging image is abnormal, if yes, interrupting mobile payment, and switching a payment mode into password payment;
if not, carrying out image enhancement on the image of the verification fingerprint to obtain a fingerprint pretreatment image;
extracting characteristics of the fingerprint pretreatment image to obtain lines of the verification fingerprint;
extracting reference features of the reference fingerprint, searching for verification features consistent with the reference features in the lines of the verification fingerprint, interrupting mobile payment if the verification features are not found, switching a payment mode into password payment, and carrying out position correction on the lines of the verification fingerprint according to the position relation between the verification features and the reference features if the verification features are found, so as to obtain corrected lines of the verification fingerprint;
comparing the correction lines of the verification fingerprints with the reference fingerprints, if the comparison is inconsistent, interrupting mobile payment, and switching the payment mode into password payment;
if the verification fingerprint is successfully compared with the reference fingerprint, the user identity associated with the reference fingerprint is called, and a payment password in the user identity is input to complete mobile payment.
Preferably, the user fingerprint input comprises the following steps:
inputting fingerprints of five fingers of the left hand of the user;
inputting fingerprints of five fingers of the right hand of the user;
and summarizing to obtain reference fingerprints, and corresponding the reference fingerprints to the hands and fingers of the user one by one.
Preferably, the generating the second instruction set includes the steps of:
acquiring at least one regular instruction action for verification;
acquiring instruction images of conventional instruction actions under different visual angles, and summarizing at least one instruction image of the same conventional instruction action to obtain an instruction image set;
the instruction image sets are in one-to-one correspondence with the conventional instruction actions;
and summarizing the conventional instruction actions and the instruction image sets corresponding to the conventional instruction actions to obtain a second instruction set.
Preferably, the analyzing the instruction video judges whether the hand of the user participating in the mobile payment actually comprises the following steps:
image frame interception is carried out in the instruction video, and at least one fragment image is obtained;
identifying a contour consistent with the chromaticity of the hand in the segment image to obtain a contour of the hand;
amplifying an image of the outline of the hand, wherein the amplification ratio is a first preset ratio, and the first preset ratio is larger than one;
obtaining at least one amplified image, wherein the amplified images are sequentially arranged, and the amplified images arranged at the back in the adjacent amplified images are amplified by the amplified images arranged at the front;
comparing the amplified image with the instruction image in the instruction image set of the second instruction set, and if the instruction image consistent with the amplified image exists, enabling the user to participate in mobile payment;
if not, the image of the outline of the hand is reduced to a second preset proportion, and the second preset proportion is smaller than one;
obtaining at least one reduced image, wherein the reduced images are sequentially arranged, and the reduced images arranged at the back in the adjacent reduced images are reduced by the reduced images arranged at the front;
comparing the reduced image with the instruction image in the instruction image set of the second instruction set, and if the instruction image consistent with the reduced image exists, enabling the user to participate in mobile payment to be true;
if not, the hands of the user participating in the mobile payment are not authentic.
Preferably, the analyzing whether the infrared thermal imaging image has an abnormality comprises the steps of:
acquiring an infrared thermal imaging image of the whole hand of a user, judging whether the whole hand of the user has a situation that the local chromaticity is inconsistent with the hue of the rest part, and if so, judging that the infrared thermal imaging image is abnormal;
if not, invoking the reference users with the ages and the sexes consistent with each other in the same time and the same area;
acquiring a reference infrared thermal imaging image of the whole hand of a reference user, and calculating the average chromaticity of the reference infrared thermal imaging image;
calculating the average chromaticity of the infrared thermal imaging image, and judging whether the difference between the average chromaticity of the infrared thermal imaging image and the average chromaticity of the reference infrared thermal imaging image is within a preset range;
if yes, the infrared thermal imaging image is free of abnormality;
if not, the infrared thermal imaging image is abnormal.
Preferably, the image enhancement of the image of the verification fingerprint to obtain a fingerprint preprocessing image includes the following steps:
RGB modeling is conducted on the image of the verification fingerprint, and the pixel value of each pixel point is obtained;
the pixel value of each pixel point is amplified in the same proportion, and the amplification proportion is a third preset proportion;
and obtaining a fingerprint preprocessing image according to the amplified pixel value.
Preferably, in the fingerprint verification process, searching for verification features consistent with the reference features includes the following steps:
acquiring reference features of reference fingerprints, wherein the reference features are local parts of the reference fingerprints acquired in advance;
dividing the grids of the reference features to obtain at least one reference slice;
grid division is carried out on the grains of the verification fingerprint, and at least one grain slice is obtained;
the two grid division sizes are consistent;
judging whether a first texture slice consistent with the reference slice exists for each reference slice, if not, not finding verification features;
if yes, summarizing the first grain slices, and judging whether the first grain slices are consistent with the reference features;
if yes, the comparison is consistent, and if not, the comparison is inconsistent.
Preferably, the step of correcting the position of the fingerprint verification line to obtain the corrected fingerprint verification line includes the following steps:
rotating the center of the verification feature by a given angle to ensure that the rotated verification feature coincides with the reference feature in a translation way;
and (3) verifying the fingerprint lines, namely rotating the given angle with the center of the verification feature to obtain the verification fingerprint correction lines.
Preferably, the comparing the correction line of the verification fingerprint with the reference fingerprint includes the following steps:
establishing a first coordinate system in the center by using the reference feature, wherein the included angle between the coordinate axis and the reference feature is a preset angle;
acquiring a reference coordinate of each point in a first coordinate system in a line of the reference fingerprint;
establishing a second coordinate system in the center by using the verification feature, wherein the included angle between the coordinate axis and the verification feature is a preset angle;
acquiring verification coordinates of each point in a second coordinate system in the correction lines of the verification fingerprints;
for each verification coordinate, judging whether a reference coordinate consistent with the verification coordinate exists or not;
if yes, the comparison is consistent, and if not, the comparison is inconsistent.
The mobile payment identity authentication system based on the biological sign is used for realizing the mobile payment identity authentication method based on the biological sign, and comprises the following steps:
the information input module is used for inputting user identities and inputting user fingerprints to obtain reference fingerprints;
the instruction sending module sends out a first instruction and a second instruction to a user;
the video verification module analyzes the instruction video and judges whether the hand of the user participating in the mobile payment is real or not;
the infrared verification module is used for analyzing whether the infrared thermal imaging image is abnormal or not;
the fingerprint verification module is used for comparing the verification fingerprint with a reference fingerprint;
and the payment module is used for calling the user identity related to the reference fingerprint, inputting the payment password in the user identity and completing mobile payment.
Compared with the prior art, the invention has the beneficial effects that:
through setting up instruction and sending out module, video verification module and infrared verification module, carry out a lot of to user's hand and check, judge whether the user has the suspicion of forging the fingerprint to can get rid of the possibility that the user forged the fingerprint when paying, avoid the fingerprint of user to be stolen, cause unnecessary economic loss, simultaneously, also can strengthen the security of mobile payment.
Drawings
FIG. 1 is a schematic flow chart of a mobile payment identity authentication method based on biological sign of the invention;
FIG. 2 is a flow chart of generating a second instruction set according to the present invention;
FIG. 3 is a schematic flow chart of the invention for analyzing the instruction video to determine whether the user participates in mobile payment;
FIG. 4 is a schematic diagram of a flow chart for analyzing whether an infrared thermal imaging image has an abnormality or not according to the present invention;
FIG. 5 is a schematic diagram of a process for image enhancement of an image of a verification fingerprint to obtain a fingerprint preprocessing image in accordance with the present invention;
FIG. 6 is a schematic diagram of a process for searching verification features consistent with reference features in verifying the fingerprint lines according to the present invention;
FIG. 7 is a schematic diagram of a process for correcting the texture of a verification fingerprint according to the present invention;
FIG. 8 is a schematic diagram of a comparison process of a corrected fingerprint of a verification fingerprint with a reference fingerprint according to the present invention.
Detailed Description
The following description is presented to enable one of ordinary skill in the art to make and use the invention. The preferred embodiments in the following description are by way of example only and other obvious variations will occur to those skilled in the art.
Referring to fig. 1, a mobile payment identity authentication method based on biological characteristics includes:
user identity input is carried out, wherein the user identity comprises age, gender, name and payment password, user fingerprint input is carried out, reference fingerprints are obtained, and the reference fingerprints of the user are associated with the user identity;
when mobile payment is carried out, a first instruction is sent, the first instruction designates a hand and a finger of a fingerprint for verification, and a verification fingerprint of a user is obtained;
generating a second instruction set, randomly selecting a second instruction from the second instruction set, sending the second instruction to a user, acquiring an instruction video of the second instruction completed by the whole hand of the user, analyzing the instruction video, judging whether the hand of the user participating in mobile payment is real or not, if not, interrupting the mobile payment, and switching the payment mode into password payment;
the hand of the fingerprint for verification, the hand for completing the second instruction and the hand of the user participating in mobile payment are the same hand;
if yes, acquiring an infrared thermal imaging image of the whole hand of the user, analyzing whether the infrared thermal imaging image is abnormal, if yes, interrupting mobile payment, and switching a payment mode into password payment;
if not, carrying out image enhancement on the image of the verification fingerprint to obtain a fingerprint pretreatment image;
extracting characteristics of the fingerprint pretreatment image to obtain lines of the verification fingerprint;
extracting reference features of the reference fingerprint, searching for verification features consistent with the reference features in the lines of the verification fingerprint, interrupting mobile payment if the verification features are not found, switching a payment mode into password payment, and carrying out position correction on the lines of the verification fingerprint according to the position relation between the verification features and the reference features if the verification features are found, so as to obtain corrected lines of the verification fingerprint;
comparing the correction lines of the verification fingerprints with the reference fingerprints, if the comparison is inconsistent, interrupting mobile payment, and switching the payment mode into password payment;
if the verification fingerprint is successfully compared with the reference fingerprint, the user identity associated with the reference fingerprint is called, and a payment password in the user identity is input to complete mobile payment.
The user fingerprint input method comprises the following steps:
inputting fingerprints of five fingers of the left hand of the user;
inputting fingerprints of five fingers of the right hand of the user;
summarizing to obtain reference fingerprints, and enabling the reference fingerprints to be in one-to-one correspondence with hands and fingers of a user;
when the user pays to acquire the fingerprint, the user can acquire the fingerprint of any finger of any hand of the user for verification, and the difficulty of counterfeiting the fingerprint can be increased.
Referring to FIG. 2, generating the second instruction set includes the steps of:
acquiring at least one regular instruction action for verification;
acquiring instruction images of conventional instruction actions under different visual angles, and summarizing at least one instruction image of the same conventional instruction action to obtain an instruction image set;
the instruction image sets are in one-to-one correspondence with the conventional instruction actions;
summarizing the conventional instruction actions and instruction image sets corresponding to the conventional instruction actions to obtain a second instruction set;
a normal instruction action is generated for action verification, but since the angle of the acquired video image is unknown, instruction images of the normal instruction action under different viewing angles are acquired.
Referring to fig. 3, the instruction video is analyzed to determine whether the hand of the user participating in the mobile payment actually comprises the following steps:
image frame interception is carried out in the instruction video, and at least one fragment image is obtained;
identifying a contour consistent with the chromaticity of the hand in the segment image to obtain a contour of the hand;
amplifying an image of the outline of the hand, wherein the amplification ratio is a first preset ratio, and the first preset ratio is larger than one;
obtaining at least one amplified image, wherein the amplified images are sequentially arranged, and the amplified images arranged at the back in the adjacent amplified images are amplified by the amplified images arranged at the front;
comparing the amplified image with the instruction image in the instruction image set of the second instruction set, and if the instruction image consistent with the amplified image exists, enabling the user to participate in mobile payment;
if not, the image of the outline of the hand is reduced to a second preset proportion, and the second preset proportion is smaller than one;
obtaining at least one reduced image, wherein the reduced images are sequentially arranged, and the reduced images arranged at the back in the adjacent reduced images are reduced by the reduced images arranged at the front;
comparing the reduced image with the instruction image in the instruction image set of the second instruction set, and if the instruction image consistent with the reduced image exists, enabling the user to participate in mobile payment to be true;
if not, the hands of the user participating in the mobile payment are not real;
the reason for judging whether the hand of the user participating in mobile payment is real is that a counterfeiter can use the artificial limb to carry out fingerprint verification, and the finger on the artificial limb has a fake fingerprint, but the artificial limb hand is inconvenient to move and difficult to finish a verification instruction, so that the condition of using the artificial limb to verify the fingerprint can be eliminated in the step;
during verification, because the distances between the video camera and the hand are different, the sizes of the images of the outline of the hand and the instruction image are different, and are larger or smaller, so that the images are required to be amplified or reduced, comparison is carried out, the first preset proportion and the second preset proportion are used for controlling the amplitude of the amplification and the reduction, and in order to improve the test precision, the first preset proportion and the second preset proportion can be set to be very close to one.
Referring to fig. 4, analyzing whether an infrared thermographic image is abnormal includes the steps of:
acquiring an infrared thermal imaging image of the whole hand of a user, judging whether the whole hand of the user has a situation that the local chromaticity is inconsistent with the hue of the rest part, and if so, judging that the infrared thermal imaging image is abnormal;
if not, invoking the reference users with the ages and the sexes consistent with each other in the same time and the same area;
acquiring a reference infrared thermal imaging image of the whole hand of a reference user, and calculating the average chromaticity of the reference infrared thermal imaging image;
calculating the average chromaticity of the infrared thermal imaging image, and judging whether the difference between the average chromaticity of the infrared thermal imaging image and the average chromaticity of the reference infrared thermal imaging image is within a preset range;
if yes, the infrared thermal imaging image is free of abnormality;
if not, the infrared thermal imaging image is abnormal;
the reason for analyzing whether an infrared thermal imaging image is abnormal is as follows: the counterfeiter can use the own hand to carry out fingerprint verification, but the finger is stuck with the counterfeited fingerprint, so that the video verification can be passed, but the stuck fingerprint is made of different materials from the hand, so that the thermal imaging of the part stuck with the fingerprint is obviously different from the rest part during thermal imaging, and the situation that the finger is stuck with the counterfeited fingerprint can be eliminated;
but the counterfeiter can also set the leather sheath on the hand, and the finger of the leather sheath is provided with the counterfeit fingerprint, so that the whole hand can not have obvious difference due to the effect of the leather sheath, therefore, the standard user consistent with the age and sex of the user is called in the same time and the same area, and the standard infrared thermal imaging image of the hand of the standard user is used for comparing with the hand infrared thermal imaging image of the user, so that the condition of the leather sheath of the hand can be eliminated.
Referring to fig. 5, image enhancement is performed on an image of a verification fingerprint, and obtaining a fingerprint preprocessing image includes the steps of:
RGB modeling is conducted on the image of the verification fingerprint, and the pixel value of each pixel point is obtained;
the pixel value of each pixel point is amplified in the same proportion, and the amplification proportion is a third preset proportion;
and obtaining a fingerprint preprocessing image according to the amplified pixel value.
Referring to fig. 6, in verifying the fingerprint's texture, finding verification features that are consistent with the reference features includes the steps of:
acquiring reference features of reference fingerprints, wherein the reference features are local parts of the reference fingerprints acquired in advance;
dividing the grids of the reference features to obtain at least one reference slice;
grid division is carried out on the grains of the verification fingerprint, and at least one grain slice is obtained;
the two grid division sizes are consistent;
judging whether a first texture slice consistent with the reference slice exists for each reference slice, if not, not finding verification features;
if yes, summarizing the first grain slices, and judging whether the first grain slices are consistent with the reference features;
if yes, the comparison is consistent, and if not, the comparison is inconsistent.
Referring to fig. 7, the method for correcting the position of the fingerprint verification line includes the following steps:
the center of the verification feature is rotated by a given angle, so that the rotated verification feature and the reference feature are overlapped in a translation way, namely, the verification feature and the reference feature can be overlapped through the translation;
the fingerprint verification method comprises the steps that the fingerprint verification is conducted through the given angle through rotation of the center of the verification feature, the correction fingerprint verification is obtained, and if the correction fingerprint verification is consistent with the reference fingerprint, the correction fingerprint verification and the reference fingerprint can be overlapped in a translational mode.
Referring to fig. 8, the comparison of the corrected fingerprint of the verification fingerprint with the reference fingerprint includes the steps of:
establishing a first coordinate system in the center by using the reference feature, wherein the included angle between the coordinate axis and the reference feature is a preset angle;
acquiring a reference coordinate of each point in a first coordinate system in a line of the reference fingerprint;
establishing a second coordinate system in the center by using the verification feature, wherein the included angle between the coordinate axis and the verification feature is a preset angle;
acquiring verification coordinates of each point in a second coordinate system in the correction lines of the verification fingerprints;
for each verification coordinate, judging whether a reference coordinate consistent with the verification coordinate exists or not;
if yes, the comparison is consistent, if not, the comparison is inconsistent;
if the correction line of the verification fingerprint is consistent with the reference fingerprint, in the same coordinate mode, if the line of the reference fingerprint passes through the position, the correction line of the verification fingerprint also passes through the position, namely, the reference coordinates of points of the line of the reference fingerprint are identical to the verification coordinates of corresponding points on the correction line of the verification fingerprint.
The mobile payment identity authentication system based on the biological sign is used for realizing the mobile payment identity authentication method based on the biological sign, and comprises the following steps:
the information input module is used for inputting user identities and inputting user fingerprints to obtain reference fingerprints;
the instruction sending module sends out a first instruction and a second instruction to a user;
the video verification module analyzes the instruction video and judges whether the hand of the user participating in the mobile payment is real or not;
the infrared verification module is used for analyzing whether the infrared thermal imaging image is abnormal or not;
the fingerprint verification module is used for comparing the verification fingerprint with a reference fingerprint;
and the payment module is used for calling the user identity related to the reference fingerprint, inputting the payment password in the user identity and completing mobile payment.
The mobile payment identity authentication system based on organism sign has the following working processes:
step one: the information input module is used for inputting user identities, wherein the user identities comprise ages, sexes, names and payment passwords, inputting user fingerprints to obtain reference fingerprints, and associating the reference fingerprints of the user with the user identities;
step two: when mobile payment is carried out, the instruction sending module sends a first instruction, the first instruction designates the hand and the finger of the fingerprint for verification, and the verification fingerprint of the user is obtained;
step three: generating a second instruction set, randomly selecting a second instruction from the second instruction set, sending the second instruction to a user by an instruction sending module, acquiring an instruction video of the second instruction completed by the whole hand of the user by a video verification module, analyzing the instruction video, judging whether the hand of the user participating in mobile payment is real or not, if not, interrupting the mobile payment, and switching a payment mode into password payment;
step four: if yes, the infrared verification module acquires an infrared thermal imaging image of the whole hand of the user, analyzes whether the infrared thermal imaging image is abnormal, if yes, mobile payment is interrupted, and the payment mode is switched to be password payment;
step five: if not, the fingerprint verification module performs image enhancement on the image of the verification fingerprint to obtain a fingerprint pretreatment image, extracts the characteristics of the fingerprint pretreatment image to obtain the texture of the verification fingerprint, extracts the reference characteristics of the reference fingerprint, searches for the verification characteristics consistent with the reference characteristics in the texture of the verification fingerprint, if the verification characteristics are not found, interrupts mobile payment, switches the payment mode to be password payment, if the verification characteristics are found, performs position correction on the texture of the verification fingerprint according to the position relation between the verification characteristics and the reference characteristics to obtain the correction texture of the verification fingerprint, compares the correction texture of the verification fingerprint with the reference fingerprint, and if the comparison is inconsistent, interrupts mobile payment, and switches the payment mode to be password payment;
step nine: if the verification fingerprint is successfully compared with the reference fingerprint, the payment module invokes the user identity associated with the reference fingerprint, inputs the payment password in the user identity and completes mobile payment.
Still further, the present disclosure provides a storage medium having a computer readable program stored thereon, wherein the computer readable program when invoked performs the mobile payment identity authentication method based on biological features.
It is understood that the storage medium may be a magnetic medium, e.g., floppy disk, hard disk, magnetic tape; optical media such as DVD; or a semiconductor medium such as a solid state disk SolidStateDisk, SSD, etc.
In summary, the invention has the advantages that: through setting up instruction and sending out module, video verification module and infrared verification module, carry out a lot of to user's hand and check, judge whether the user has the suspicion of forging the fingerprint to can get rid of the possibility that the user forged the fingerprint when paying, avoid the fingerprint of user to be stolen, cause unnecessary economic loss, simultaneously, also can strengthen the security of mobile payment.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made therein without departing from the spirit and scope of the invention, which is defined by the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (10)
1. A mobile payment identity authentication method based on biological sign, comprising:
user identity input is carried out, wherein the user identity comprises age, gender, name and payment password, user fingerprint input is carried out, reference fingerprints are obtained, and the reference fingerprints of the user are associated with the user identity;
when mobile payment is carried out, a first instruction is sent, the first instruction designates a hand and a finger of a fingerprint for verification, and a verification fingerprint of a user is obtained;
generating a second instruction set, randomly selecting a second instruction from the second instruction set, sending the second instruction to a user, acquiring an instruction video of the second instruction completed by the whole hand of the user, analyzing the instruction video, judging whether the hand of the user participating in mobile payment is real or not, if not, interrupting the mobile payment, and switching the payment mode into password payment;
the hand of the fingerprint for verification, the hand for completing the second instruction and the hand of the user participating in mobile payment are the same hand;
if yes, acquiring an infrared thermal imaging image of the whole hand of the user, analyzing whether the infrared thermal imaging image is abnormal, if yes, interrupting mobile payment, and switching a payment mode into password payment;
if not, carrying out image enhancement on the image of the verification fingerprint to obtain a fingerprint pretreatment image;
extracting characteristics of the fingerprint pretreatment image to obtain lines of the verification fingerprint;
extracting reference features of the reference fingerprint, searching for verification features consistent with the reference features in the lines of the verification fingerprint, interrupting mobile payment if the verification features are not found, switching a payment mode into password payment, and carrying out position correction on the lines of the verification fingerprint according to the position relation between the verification features and the reference features if the verification features are found, so as to obtain corrected lines of the verification fingerprint;
comparing the correction lines of the verification fingerprints with the reference fingerprints, if the comparison is inconsistent, interrupting mobile payment, and switching the payment mode into password payment;
if the verification fingerprint is successfully compared with the reference fingerprint, the user identity associated with the reference fingerprint is called, and a payment password in the user identity is input to complete mobile payment.
2. The mobile payment identity authentication method based on biological sign according to claim 1, wherein the user fingerprint input comprises the following steps:
inputting fingerprints of five fingers of the left hand of the user;
inputting fingerprints of five fingers of the right hand of the user;
and summarizing to obtain reference fingerprints, and corresponding the reference fingerprints to the hands and fingers of the user one by one.
3. The method of biometric-based mobile payment identity authentication of claim 2, wherein the generating the second set of instructions comprises the steps of:
acquiring at least one regular instruction action for verification;
acquiring instruction images of conventional instruction actions under different visual angles, and summarizing at least one instruction image of the same conventional instruction action to obtain an instruction image set;
the instruction image sets are in one-to-one correspondence with the conventional instruction actions;
and summarizing the conventional instruction actions and the instruction image sets corresponding to the conventional instruction actions to obtain a second instruction set.
4. The method for authenticating identity of mobile payment based on physical sign of claim 3, wherein the analyzing the instruction video to determine whether the hand of the user participating in the mobile payment is truly comprises the steps of:
image frame interception is carried out in the instruction video, and at least one fragment image is obtained;
identifying a contour consistent with the chromaticity of the hand in the segment image to obtain a contour of the hand;
amplifying an image of the outline of the hand, wherein the amplification ratio is a first preset ratio, and the first preset ratio is larger than one;
obtaining at least one amplified image, wherein the amplified images are sequentially arranged, and the amplified images arranged at the back in the adjacent amplified images are amplified by the amplified images arranged at the front;
comparing the amplified image with the instruction image in the instruction image set of the second instruction set, and if the instruction image consistent with the amplified image exists, enabling the user to participate in mobile payment;
if not, the image of the outline of the hand is reduced to a second preset proportion, and the second preset proportion is smaller than one;
obtaining at least one reduced image, wherein the reduced images are sequentially arranged, and the reduced images arranged at the back in the adjacent reduced images are reduced by the reduced images arranged at the front;
comparing the reduced image with the instruction image in the instruction image set of the second instruction set, and if the instruction image consistent with the reduced image exists, enabling the user to participate in mobile payment to be true;
if not, the hands of the user participating in the mobile payment are not authentic.
5. The method for authenticating a mobile payment based on biometric features of claim 4, wherein the analyzing the infrared thermal imaging image for anomalies comprises the steps of:
acquiring an infrared thermal imaging image of the whole hand of a user, judging whether the whole hand of the user has a situation that the local chromaticity is inconsistent with the hue of the rest part, and if so, judging that the infrared thermal imaging image is abnormal;
if not, invoking the reference users with the ages and the sexes consistent with each other in the same time and the same area;
acquiring a reference infrared thermal imaging image of the whole hand of a reference user, and calculating the average chromaticity of the reference infrared thermal imaging image;
calculating the average chromaticity of the infrared thermal imaging image, and judging whether the difference between the average chromaticity of the infrared thermal imaging image and the average chromaticity of the reference infrared thermal imaging image is within a preset range;
if yes, the infrared thermal imaging image is free of abnormality;
if not, the infrared thermal imaging image is abnormal.
6. The mobile payment identity authentication method based on biological sign of claim 5, wherein the image enhancement of the image of the verification fingerprint to obtain the fingerprint preprocessing image comprises the following steps:
RGB modeling is conducted on the image of the verification fingerprint, and the pixel value of each pixel point is obtained;
the pixel value of each pixel point is amplified in the same proportion, and the amplification proportion is a third preset proportion;
and obtaining a fingerprint preprocessing image according to the amplified pixel value.
7. The mobile payment identity authentication method based on biological sign according to claim 6, wherein searching for verification features consistent with the reference features in the fingerprint pattern comprises the steps of:
acquiring reference features of reference fingerprints, wherein the reference features are local parts of the reference fingerprints acquired in advance;
dividing the grids of the reference features to obtain at least one reference slice;
grid division is carried out on the grains of the verification fingerprint, and at least one grain slice is obtained;
the two grid division sizes are consistent;
judging whether a first texture slice consistent with the reference slice exists for each reference slice, if not, not finding verification features;
if yes, summarizing the first grain slices, and judging whether the first grain slices are consistent with the reference features;
if yes, the comparison is consistent, and if not, the comparison is inconsistent.
8. The mobile payment identity authentication method based on biological sign of claim 7, wherein the performing the position correction on the fingerprint line to obtain the corrected fingerprint line of the verification fingerprint comprises the following steps:
rotating the center of the verification feature by a given angle to ensure that the rotated verification feature coincides with the reference feature in a translation way;
and (3) verifying the fingerprint lines, namely rotating the given angle with the center of the verification feature to obtain the verification fingerprint correction lines.
9. The mobile payment identity authentication method based on biological sign of claim 8, wherein the comparing the corrected fingerprint of the verification fingerprint with the reference fingerprint comprises the steps of:
establishing a first coordinate system in the center by using the reference feature, wherein the included angle between the coordinate axis and the reference feature is a preset angle;
acquiring a reference coordinate of each point in a first coordinate system in a line of the reference fingerprint;
establishing a second coordinate system in the center by using the verification feature, wherein the included angle between the coordinate axis and the verification feature is a preset angle;
acquiring verification coordinates of each point in a second coordinate system in the correction lines of the verification fingerprints;
for each verification coordinate, judging whether a reference coordinate consistent with the verification coordinate exists or not;
if yes, the comparison is consistent, and if not, the comparison is inconsistent.
10. A mobile payment identity authentication system based on biological sign for implementing the mobile payment identity authentication method based on biological sign as claimed in any one of claims 1 to 9, comprising:
the information input module is used for inputting user identities and inputting user fingerprints to obtain reference fingerprints;
the instruction sending module sends out a first instruction and a second instruction to a user;
the video verification module analyzes the instruction video and judges whether the hand of the user participating in the mobile payment is real or not;
the infrared verification module is used for analyzing whether the infrared thermal imaging image is abnormal or not;
the fingerprint verification module is used for comparing the verification fingerprint with a reference fingerprint;
and the payment module is used for calling the user identity related to the reference fingerprint, inputting the payment password in the user identity and completing mobile payment.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101814167B1 (en) * | 2017-05-19 | 2018-01-03 | 주식회사 올아이티탑 | Electronic payment system using face and finger recognition and method for processing thereof |
| CN113139811A (en) * | 2021-04-26 | 2021-07-20 | 中国工商银行股份有限公司 | Compound authentication payment method and device and server |
| CN113378640A (en) * | 2021-05-12 | 2021-09-10 | 巽腾(广东)科技有限公司 | Palm biological recognition-based identity authentication method, device, equipment and medium |
| WO2022022365A1 (en) * | 2020-07-31 | 2022-02-03 | 华为技术有限公司 | Image matching method applied to fingerprint recognition and related device |
| CN117173754A (en) * | 2023-08-21 | 2023-12-05 | 盛视科技股份有限公司 | Non-contact gesture vein recognition method and recognition terminal |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9218522B2 (en) * | 2013-09-17 | 2015-12-22 | Gingy Technology Inc. | Method for determining fingerprint authenticity and device for the same |
| US10339362B2 (en) * | 2016-12-08 | 2019-07-02 | Veridium Ip Limited | Systems and methods for performing fingerprint based user authentication using imagery captured using mobile devices |
-
2023
- 2023-12-12 CN CN202311695839.7A patent/CN117391708B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101814167B1 (en) * | 2017-05-19 | 2018-01-03 | 주식회사 올아이티탑 | Electronic payment system using face and finger recognition and method for processing thereof |
| WO2022022365A1 (en) * | 2020-07-31 | 2022-02-03 | 华为技术有限公司 | Image matching method applied to fingerprint recognition and related device |
| CN113139811A (en) * | 2021-04-26 | 2021-07-20 | 中国工商银行股份有限公司 | Compound authentication payment method and device and server |
| CN113378640A (en) * | 2021-05-12 | 2021-09-10 | 巽腾(广东)科技有限公司 | Palm biological recognition-based identity authentication method, device, equipment and medium |
| CN117173754A (en) * | 2023-08-21 | 2023-12-05 | 盛视科技股份有限公司 | Non-contact gesture vein recognition method and recognition terminal |
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