CN103077459A - Method for carrying out living body authentication and payment by fusing multi-biometric features of user - Google Patents
Method for carrying out living body authentication and payment by fusing multi-biometric features of user Download PDFInfo
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Abstract
The invention relates to a method for carrying out identity authentication by multi-biometric features of a user on the basis of living body authentication, discloses a living body authentication and payment method fusing the multi-biometric features of the user, such as a fingerprint, a face, finger vein and a palm print, and aims to utilize a low-level feature and image matrix to carry out matrix processing and projection to obtain multi-biometric fused features by a user multi-biometric feature fusion technology, carrying out living body authentication on the extracted multi-biometric features and features stored in a database and judge whether to successfully carry out authentication by calculating authentication scores of the extracted multi-biometric features and the features stored in the database or not. The method is used for solving the problem of safety of a small-scale payment system which uses a shopping mall and a supermarket as carriers, sufficiently utilizes the advantages of diversity and complementarity of the multi-biometric features, effectively combines various identity authentication technologies and implements safe and reliable living body authentication and payment.
Description
Technical field
The present invention relates to the biometrics identification technology field, the living body authentication payment of especially merging based on multi-biological characteristic.
Background technology
At present, take the market, the supermarket as the small-sized payment system application in modern society of carrier very extensive, the general modes of payments is paid in cash, bank card payment (comprising credit card), and at present popular mobile payment.These methods of payment respectively have shortcoming.Such as, cash requirements small change, easily disease carrying germ; Bank card " recognizing thing does not recognize people ", if password loss or forget, with dangerous and make troubles.Also there is the drawback of " recognizing thing does not recognize people " in mobile payment, if Mobile payment terminal is lost, the people that can not guarantee payment is me.Therefore, these modes of payments can not satisfy the requirement of advanced information society.
Biometrics identification technology is with its distinctive security, and reliability and validity etc. more and more is subject to people's attention.Recognition of face and fingerprint recognition be the most frequently used and biometrics identification technology easily as two kinds, has been widely used in the fields such as identification.At present, the fingerprint payment has been used to the secure payment field, becomes replenishing or substituting of conventional payment mode.
Yet many times, only can not satisfy people's needs based on single biological characteristic individual identity identification system of fingerprint or people's face, this is because of recognition of face speed is fast but reliability is not high; And fingerprint recognition reliability height is counterfeit easily.Technology based on living body authentication causes concern at present.The multi-biological characteristic integration technology is a new research field that grows up in the situation of biological identification technology fast development, the multi-biological characteristic integration technology is the information processing technology that grows up nearly decades, it is that an integral body that permeates such as various biological characteristics such as fingerprint, people's face, palmmprint is carried out comprehensive analysis processing, overcome the drawback of classic method, utilize the complementarity of various biological characteristics, realize living body authentication, safer guarantee is provided.
The present invention proposes the method for payment that a kind of user's of fusion multi-biological characteristic carries out living body authentication, multi-biological characteristic is merged authentication apply to payment technical field, and the method safety, reliable is with a wide range of applications and social use value.
Summary of the invention
The technical problem to be solved in the present invention is: in order to overcome the shortcoming of conventional payment methods, provide a kind of user's of fusion multi-biological characteristic to carry out the method for payment of living body authentication, utilize graphical analysis and intelligent excavating technology that the user is carried out the living body authentication payment.
The present invention solves the technical scheme that its technical matters takes: a kind of user's of fusion multi-biological characteristic carries out the method for payment of living body authentication, by user's multi-biological characteristic being carried out graphical analysis and data mining mapping, extract the feature of robustness and carry out the authentication payment.
Described multi-biological characteristic comprises fingerprint, people's face, finger vena, palmmprint etc., and it is as follows that it utilizes graphical analysis and intelligent excavating technology to carry out the concrete steps of user's living body authentication payment:
A. biometric image pre-service: the emerging system that is made of fingerprint, people's face, finger vena, palmmprint carries out pre-service;
B. extract low-level image feature: extract invariant moment features, Gabor filter feature, Local Ternary Pattern (LTP) feature.
The concrete steps that described multi-biological characteristic merges are as follows:
A. low-level image feature-image array makes up: adopt multiple low-level image feature, make up low-level image feature-image array of each user;
B. obtain how biological fusion feature.Low-level image feature-image array is carried out matrix disposal and projection, obtain how biological fusion feature.
Described living body authentication is as follows with the payment concrete steps:
A. living body authentication: the multi-biological characteristic that extracts and the feature that is stored in the database are carried out living body authentication, by calculating both authentication marks, judge whether authentication success;
B. payment.If the multi-biological characteristic that the living body authentication step is extracted and the feature authentication success in the database, the expression user can pay by the identity living body authentication; Otherwise, then think failure.
The beneficial effect that fusion multi-biological characteristic of the present invention carries out the living body authentication method of payment is: by take the fingerprint, the multi-biological characteristic such as people's face, finger vena, palmmprint, merge these features and carry out the living body authentication payment, it will be more safe and reliable contrasting traditional method of payment based on single biological characteristic, can satisfy the various shopping payment environment such as supermarket, market.
Description of drawings:
The present invention is further described below in conjunction with drawings and Examples.
Fig. 1. research approach of the present invention and theoretical block diagram
Embodiment:
In conjunction with the accompanying drawings, the present invention is further detailed explanation.These accompanying drawings are the synoptic diagram of simplification, and basic structure of the present invention only is described in a schematic way, because only show the formation relevant with the present invention.
Fusion multi-biological characteristic as shown in Figure 1 carries out the method for living body authentication payment, mainly utilize graphical analysis and data mining technology that the system that is made of fingerprint, people's face, finger vena, palmmprint is carried out respectively pre-service, from pretreatment image, extract various low-level image features, then these features are merged, utilize at last the feature of fusion and the feature of database stores to carry out live body authentication and payment.
Multi-biological characteristic is merged in the present invention, and to carry out the concrete steps of living body authentication payment as follows:
One, the image low-level image feature extracts:Comprise the key steps such as biometric image pre-service, extraction low-level image feature.
(1) biometric image pre-service:The pre-service of multi-biological characteristic image is one of committed step before the feature extraction, because emerging system is made of fingerprint, people's face and finger vena, palmmprint etc., therefore need to carry out respectively pre-service to it.Pretreated key step comprises: area-of-interest (ROI) is cut apart, enhancing, normalization etc.
(2) extraction of low-level image feature:Extract respectively invariant moment features (hu is bending moment and zernike orthogonally-persistent square not), Garbor filter feature, Local Ternary Pattern (LTP) feature etc.
(a) invariant moment features: invariant moment features has rotation, yardstick and translation invariant feature, has the provincial characteristics ability of very strong Description Image.Not bending moment relatively commonly used as: hu is bending moment and zernike orthogonally-persistent square not.Its key step is as follows:
Step 1.According to hu 7 hu eigenwert of bending moment not of bending moment formulas Extraction not
I
Step 2.Select the not exponent number of bending moment of zernike
nAnd repeat number
m, extract
Value;
Step 3.To what extract
IWith
Be combined into invariant moment features.
(b) Gabor filter feature: Gabor filter has good set direction and frequency selective characteristic, can carry out time frequency analysis to image, extracts the texture value under different directions, the frequency.Its key step is as follows:
Step 1.Select rational direction and frequency f parameter, extract the G value under different directions and the different frequency;
Step 2.The G value of extracting is combined into Gabor filter feature.
(c) LTP feature: Local binary patter (LBP) is based on the texture image descriptor of image spatial domain Local Operator, and the coding with LBP is extended to three values (1,0,1) obtains local three binarization modes.Therefore, can be used for Description Image local grain situation.Its key step is as follows:
Step 1.To image block, this operator is to eight neighborhood point samplings of each pixel of block image first, and each sampled point and center pixel are done the computing of gray-scale value binaryzation;
Step 2.Calculate the LTP value.Here, sampled point and center pixel are made gray-scale value and are quantified as zero in very among a small circle at one, do being quantified as of gray-scale value+1 greater than this center pixel, are quantified as-1 less than what this center pixel was made gray-scale value;
Step 3.The LTP value of the block image that extracts is combined into the LTP feature of image.
Two, multi-biological characteristic merges:
(1) low-level image feature-image array makes up:Adopt multiple low-level image feature, make up low-level image feature-image array (q biological characteristic merges altogether) of each user.
Step 1.The ROI image unification of each biological characteristic is blocked into p size be the little image of n * n, q the individual local little image of the common p * q of biometric image.
Step 2.Each local little image is comprised respectively the analyses such as invariant moment features (hu is bending moment and zernike orthogonally-persistent square not), Garbor filter feature, LTP feature, and with the column vector of these features as low-level image feature-image array of each user.
Step 3.With the row vector of the local little image behind each piecemeal (q biological characteristic) as low-level image feature-image array of each user, add up each low-level image feature obtained in the previous step to the probability of its appearance, make up each user's low-level image feature and the feature-image array between the image, its size is p * q.
(2) obtain how biological fusion feature:At first, low-level image feature-image array being carried out diagonalization processes.Then, after diagonalizable matrix is carried out the row matrix Directional Decomposition.At last, project image onto in this feature space, obtain how biological fusion feature.Its key step is as follows:
Step 1.Diagonalization of matrix: be that m the low-level image feature-image array set of p * q is used for expression with size,
Represent low-level image feature-image array of each user, m is user's quantity.
Step 2.Image array resolution process: be that m diagonalizable matrix set of p * q is used with size
Represent,
Represent the low-level image feature-image array after each user's diagonalization, m is user's quantity.At first utilize 1D-NMF to be decomposed into size and be the matrix of p * d
LWith the size matrix that is d * q
HLong-pending, so that:
Here d is with reference to dimension,
LIt is matrix
XDecompose the basis matrix that obtains in image row direction,
HBe matrix of coefficients;
Step 3.Project image onto in this feature space, namely obtain the coefficient by this Feature Combination
Represented how biological fusion feature.
Three, living body authentication and payment:
(1) living body authentication:The multi-biological characteristic that extracts and the feature that is stored in the database are carried out living body authentication, by calculating both authentication marks, if mark surpasses certain threshold value, then think authentication success; Otherwise, failure.
Step 1.Off-line carries out pre-service, low-level image feature extraction as comprises the analyses such as invariant moment features (hu is bending moment and zernike orthogonally-persistent square not), Garbor filter feature, LTP feature multi-biological characteristic, and with these Fusion Features, and the numerical value of feature normalized to [0,1] in the scope, is stored in database;
Step 2.The online acquisition multi-biological characteristic, and carry out the processing such as low-level image feature extraction, multi-biological characteristic fusion, the biological characteristic that merges is carried out normalized, and the numerical value of input feature vector is normalized in [0,1] scope;
Step 3.Utilize the sorter such as support vector machine to come the input feature vector of online acquisition and the feature that is stored in the database are mated, and calculate their coupling mark, if mark surpasses certain threshold value, then think authentication success; Otherwise, failure.
(2) payment:If the feature authentication success in the multi-biological characteristic of said extracted and the database, the expression user can pay by the identity living body authentication; Otherwise, then think failure.
Take above-mentioned foundation desirable embodiment of the present invention as enlightenment, by above-mentioned description, the relevant staff can in the scope that does not depart from this invention technological thought, carry out various change and modification fully.The technical scope of this invention is not limited to the content of instructions, must determine its technical scope according to the claim scope.
Claims (4)
1. one kind merges the method for payment that user's multi-biological characteristic carries out living body authentication, it is characterized in that: by merging the multi-biological characteristics such as fingerprint, people's face, finger vena, palmmprint, utilize graphical analysis and intelligent excavating technology to carry out the payment of user's living body authentication.
2. a kind of user's of fusion multi-biological characteristic according to claim 1 carries out the method for payment of living body authentication, it is characterized in that: described multi-biological characteristic comprises fingerprint, people's face, finger vena, palmmprint etc., and it is as follows that it utilizes graphical analysis and intelligent excavating technology to carry out the concrete steps of user's living body authentication payment:
A. biometric image pre-service: the emerging system that is made of fingerprint, people's face, finger vena, palmmprint carries out pre-service;
B. extract low-level image feature: extract invariant moment features, Gabor filter feature, Local Ternary Pattern (LTP) feature.
3. the described described a kind of user's of fusion multi-biological characteristic carries out the method for payment of living body authentication according to claim 1, it is characterized in that: the concrete steps that described multi-biological characteristic merges are as follows:
A. low-level image feature-image array makes up: adopt multiple low-level image feature, make up low-level image feature-image array of each user;
B. obtain how biological fusion feature.Low-level image feature-image array is carried out matrix disposal and projection, obtain how biological fusion feature.
4. the 1 described described a kind of user's of fusion multi-biological characteristic carries out the method for payment of living body authentication as requested, it is characterized in that: described living body authentication is as follows with the payment concrete steps:
A. living body authentication: the multi-biological characteristic that extracts and the feature that is stored in the database are carried out living body authentication, by calculating both authentication marks, judge whether authentication success;
B. payment.If the multi-biological characteristic that the living body authentication step is extracted and the feature authentication success in the database, the expression user can pay by the identity living body authentication; Otherwise, then think failure.
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