CN103605963A - Fingerprint identification method - Google Patents

Abstract

The invention discloses a fingerprint identification method. A modified fingerprint partitioning algorithm is provided in order to overcome the defects of a variance method used for carrying out fingerprint partitioning, an appropriate Log Gabor filter is built to achieve the reinforcement of a fingerprint image, and finally a node relationship representation method under a curvilinear coordinate system is provided. The modified fingerprint partitioning algorithm is provided in order to overcome the defects of the variance method used for carrying out fingerprint partitioning, and the fingerprint partitioning algorithm makes full use of the advantages of a simple algorithm and high calculation speed of the variance method, overcomes the defect that the variance method is easily affected by noise, and obtains a more accurate fingerprint portioning image. The appropriate Log Gabor filter is built to achieve the reinforcement of the fingerprint image, and the node relationship representation method under the curvilinear coordinate system can be effectively matched with deformed fingerprints. The system distinguishes the identification of each person by utilizing the characteristics such as uniqueness and forgery difficulty of the fingerprints, and has the advantages that allograph is avoided and paper is not used.

Description

A kind of fingerprint identification method

Technical field

The invention belongs to fingerprint identification technology field, relate in particular to a kind of fingerprint identification method.

Background technology

People be unable to do without identity identification and authentication in a networked society existence and life, and especially, in the digital times of 21 century, people are usually the card of bagful, the password of full head.Traditional identification and authentication method are based on identify label article (as magnetic card, certificate etc.) and identify label knowledge (as username and password etc.).Yet there are many shortcomings in traditional identity identifying method: identify label article exist easily losss, easily stolen, easy forgery, easily the problem, the problems such as identification information exists and easily misremembers, easily forgets, easily attacks, easy leakage such as falsely use.These shortcomings have been brought inconvenience and a lot of safety problem to people's life.Therefore, must find convenient, more safe and reliable identity identifying method.

Living things feature recognition and authentication techniques are behavior (as gait, the person's handwriting etc.) features according to the inherent physiology of the mankind (as fingerprint, people's face, iris etc.) or the custom formation day after tomorrow, use computing machine or embedded system to carry out automatic identification and authentication, having overcome above traditional identification and many shortcomings of authentication method, is a kind of promising important authentication means.

With respect to other identity recognizing technology, fingerprint recognition is a kind of more preferably identity identifying technology.Reason is as follows:

L) everyone fingerprint is unique, does not have identical fingerprint between two people.

2) everyone fingerprint is quite fixed, and is difficult to change.For example, fingerprint can be not with advancing age or the variation of healthy degree and changing.

3) be convenient to obtain sample fingerprint, be easy to develop recognition system, practical.Oneself has the sample fingerprint storehouse of standard at present, has facilitated the software development of recognition system, and in addition, the hardware components that completes fingerprint sampling functions in recognition system is also more easily realized.

4) people's ten finger fingerprints are neither identical, therefore can utilize easily a plurality of fingerprints to form multiple password, improve the security of system.Meanwhile, do not increase the burden of system.

5) template of using in fingerprint recognition is not initial fingerprint image, but the key feature extracting in fingerprint image, so memory space is little.In addition, the fingerprint image of input is extracted after key feature, can greatly reduce the burden of Internet Transmission, be convenient to realize strange land and confirm, support the network function of computing machine.

From above analysis, can see, fingerprint identification technology not only has many original information security advantages with respect to other recognition technologies, the more important thing is and also has very high practicality and feasibility.In the various identity identifying methods based on biological characteristic, the market share that fingerprint recognition is occupied is also maximum, also very convenient while identifying.Fingerprint identification technology not only may be used on, in the middle of employee's work attendance, also can being applied to various fields, as: the fingerprint gate lock in mass consumption field, fingerprint bin, automobile one touch type are without key startup system etc.; The application of fingerprint recognition on the electronic equipments such as the fingerprint U disk of IT consumer field and PC/PDA/ mobile phone; And the internal staff of financial field authenticates, saves authenticated client, and fingerprint recognition pays etc.

Current, the company and the scientific research institution that are engaged in auto Fingerprint Identification System research abroad have family more than 200, and wherein there are Identix, Intel, IBM etc. in representative company.Overseas utilization advanced person's fingerprint identification technology is also applied to attendance checking system also relatively early, at present external fingerprint attendance machine is to the future development of hommization more, some is not only with voice system and friendly operating system, simultaneously all right and radio-frequency card is used, and has more improved the accuracy of identification.External scientist studies representative having to fingerprint identification technology:

D.Marr adopts the take the fingerprint profile of line of edge windows technology, makes effective decomposition of fingerprint image be achieved; The Choon woo of Korea S has proposed the algorithm of printenv density Estimation Rapid matching; The people such as India ArigitBishnu have proposed based on crestal line motor point sequences match algorithm etc.

The fingerprint identification technology research starting of China falls behind than western countries, but speed of development is very fast, and has obtained great successes.Prominent domestic Tsing-Hua University of institution of higher learning has just started the research to fingerprint identification technology in the eighties in last century, the crime fingerprint recognition system that it is developed is applied to Beijing Municipal Bureau of Public Security.Automatic mode identification National Key Laboratory of the Chinese Academy of Sciences is devoted to the subject study of biological characteristics identity recognizing technology always, and power has a certain impact in this field.Domestic scientist's the achievement in research that represents has:

Palpus Wen Bo, the Xia Hongbin of Southern Yangtze University proposed the optimum threshold method of a kind of being called as " golden cut algorithm ", and it is by the effective combination of Gaussian function in histogram technology and high number, respond well; The people such as Zhang Xiong of soft project key lab of Wuhan University propose to adopt the corresponding feature of crooked information extraction of fingerprint; The algorithm for recognizing fingerprint of people's exploitations such as the Tian Jie of the Chinese Academy of Sciences is obtained marvelous results in world match.

Although fingerprint identification technology both domestic and external had a great development in recent years, current fingerprint identification technology and product also exist some problems, such as: because technical merit is irregular, some product refuses to recognize rate, misclassification rate is higher; Adopt the product of optical fingerprint collector also to have residual fingerprint, avoid the problems such as high light direct projection, and the fingerprint cover die forgery problem of customer relationship.The appearance explanation fingerprint identification technology of these problems also has certain defect at hardware with in to the collection of fingerprint, processing scheduling algorithm.Traditional fingerprint segmentation algorithm is easily subject to the impact of noise, can not obtain fingerprint segmentation figure accurately; In fingerprint collecting process, be pressed, the impact of the various factors such as skin, acquisition instrument, be easy to cause fingerprint image to degenerate; Deformed fingerprint image coupling.Fingerprint obtain be one from three-dimensional to two-dimentional distortion transfer process, contact points different during fingerprint collecting can produce different deformation.For deformation fingerprint, existing matching process has certain robustness, but the deformation quantity that can allow is very limited, and to containing the image compared with large deformation, these methods cannot be mated.

Summary of the invention

For current fingerprint identification technology and product, also exist some problems, the object of the embodiment of the present invention is to provide a kind of fingerprint identification method.

The embodiment of the present invention is to realize like this, a kind of fingerprint identification method, the method is first by the calculating to the number of pixels of the gray variance of fingerprint gray level image, variance gradient, gradient-norm and low gray shade scale, introduce the linear combination feature of variance and gradient-norm, according to the relation of this feature and average, choose suitable thresholding, tentatively distinguish foreground area and the background area of fingerprint, in recycling mathematical morphology, aftertreatment is cut apart in open and close computing, thereby obtains accurately complete fingerprint foreground area; Utilize Log Gabor wave filter to realize the enhancing of fingerprint image.

Further, on linear frequency yardstick, the transport function of Log Gabor function is defined as:

$G\left(\mathrm{\ω}\right)=\exp \left(\frac{-{\left(\ln (\mathrm{\ω}/{\mathrm{\ω}}_0)\right)}^2}{2{\left(\ln \left(\mathrm{\κ}/{\mathrm{\ω}}_0\right)\right)}^2}\right)$

In formula, ω ₀for the centre frequency of wave filter, in order to guarantee the constant shape of wave filter, for different ω ₀should select κ to make κ/ω ₀remain unchanged;

At frequency field structure Log Gabor wave filter, it comprises two parts: the radial component G that controls filter bandwidht _rand control the angle component G that filter direction is selected (r) _θ(θ), the Log Gabor filter function G (r, θ) of the two product complete, corresponding polar coordinates expression formula is as follows respectively:

$G_r\left(r\right)=\exp (-\frac{{\left(\ln (r/f_0)\right)}^2}{2\·{\left(\ln {\mathrm{\σ}}_f\right)}^2})$

$G_{\mathrm{\θ}}\left(\mathrm{\θ}\right)=\exp (-\frac{{(\mathrm{\θ}-{\mathrm{\θ}}_0)}^2}{2\·{{\mathrm{\σ}}_{\mathrm{\θ}}}^2})$

G(r,θ)＝G _r(r)·G _θ(θ)

In formula, r represents radial coordinate, and θ represents angle coordinate, f ₀centered by frequency, θ ₀for filter direction, σ _ffor determining radial bandwidth, B _f=2 (2/ln2) ^1/2| ln σ _f|, σ _θdetermine angle bandwidth, B _θ=2 (2/ln2) ^1/2σ _θ.

Further, the flow process that strengthens algorithm is: (l) first by fingerprint image piecemeal and extract the local spectrum information of each piecemeal by windowing Fourier transform; (2) frequency spectrum then conversion being obtained carries out filtering with corresponding Log Gabor wave filter; (3) then with inverse Fourier transform, filtered spectrum information is become to spatial information; (4) last extracting ridges combine the image that is enhanced from filtering image.

Further, the method further comprises:

By the calculating to the number of pixels of the gray variance of fingerprint gray level image, variance gradient, gradient-norm and low gray shade scale;

Introduce the linear combination feature of variance and gradient-norm, according to the relation of this feature and average, choose suitable thresholding, tentatively distinguish foreground area and the background area of fingerprint;

Utilize open and close computing in mathematical morphology to cut apart aftertreatment, thereby obtain accurately complete fingerprint foreground area.

Further, the suitable LogGabor filtered method of structure that the method provides further comprises:

By fingerprint image piecemeal and extract the local spectrum information of each piecemeal by windowing Fourier transform;

The frequency spectrum that conversion is obtained carries out filtering with corresponding Log Gabor wave filter;

With inverse Fourier transform, filtered spectrum information is become to spatial information;

Extracting ridges combine the image that is enhanced from filtering image.

Further, the method further comprises

Node relationships method for expressing under curvilinear coordinate system, the method comprises:

Take each node sets up curvilinear coordinate system based on the field of direction as the former heart;

X-axis is by carrying out track and extract along crestal line and valley line, and Y-axis is extracted along the direction vertical with crestal line, based on the field of direction, can calculate the coordinate of other node in this coordinate system;

Based on these curvilinear coordinate systems, can extract coordinate and the b coordinate in the coordinate system of a of the coordinate relation between every couple of node a and b: a in the coordinate system of b;

Carry out node pairing judgement, unpaired can mate deformation fingerprint;

If Y-axis identifies length with periodicity, so a pair of coordinate can reflect two internodal streakline numbers, insensitive to the variation of streakline spacing and curvature variation, has deformation unchangeability.

First fingerprint recognition gordian technique provided by the invention carries out the shortcoming of fingerprint segmentation for variance method, a kind of improved fingerprint segmentation algorithm has been proposed, then propose the suitable Log Gabor wave filter of structure and realize the enhancing of fingerprint image, finally proposed the node relationships method for expressing under curvilinear coordinate system.

For variance method, carry out the shortcoming of fingerprint segmentation, a kind of improved fingerprint segmentation algorithm has been proposed, the advantage that algorithm is simple, computing velocity is fast that this method takes full advantage of variance method, but overcome its easily deficiency affected by noise, obtained fingerprint segmentation figure more accurately; Propose the suitable Log Gabor wave filter of structure and realize the enhancing of fingerprint image; Node relationships method for expressing under curvilinear coordinate system mates the fingerprint of deformation effectively.

Utilize people's fingerprint to carry out individual identification and typing, and mate with the personal information pre-depositing, deposit database in, False Rate≤0.0001%; Fingerprint applying light can be identified typing, recognition speed≤0.8 second; User can directly check attendance record in attendance recorder, or finger print information fingerprint being read in USB flash disk copies PC to, can carry out statistical study according to the time of employee's typing fingerprint, number of times, and then forms electronic report forms; Single fingerprint record machine fingerprint capacity is more than 6000 pieces.

This system utilize fingerprint uniqueness, be difficult to the identity that the characteristics such as forgery are distinguished everyone, having cannot allograph, the advantage such as with no paper.

Accompanying drawing explanation

Fig. 1 is the research structure process flow diagram of the fingerprint recognition gordian technique that provides of prior art;

Fig. 2 is the research process flow diagram of the fingerprint recognition gordian technique that provides of the embodiment of the present invention;

Fig. 3 is the Log Gabor filtered method process flow diagram that structure is suitable.

Embodiment

In order to make object of the present invention, technical scheme and advantage clearer, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein, only in order to explain the present invention, is not intended to limit the present invention.

Fig. 1 shows the research method of the fingerprint recognition gordian technique that the invention process case provides, and the method comprises:

In step S101, for variance method, carry out the shortcoming of fingerprint segmentation, a kind of improved fingerprint segmentation algorithm has been proposed;

In step S102, the enhancing that the suitable Log Gabor wave filter of structure is realized fingerprint image is proposed;

In step S103, the node relationships method for expressing under curvilinear coordinate system has been proposed.

Fig. 2 shows the improved fingerprint segmentation algorithm that the invention process case provides, and the method comprises:

In step S1011, by the calculating to the number of pixels of the gray variance of fingerprint gray level image, variance gradient, gradient-norm and low gray shade scale;

In step S1012, introduce the linear combination feature of variance and gradient-norm, according to the relation of this feature and average, choose suitable thresholding, tentatively distinguish foreground area and the background area of fingerprint;

In step S1013, utilize open and close computing in mathematical morphology to cut apart aftertreatment, thereby obtain accurately complete fingerprint foreground area.

Fig. 3 shows the suitable Log Gabor filtered method of structure that the invention process case provides, and the method comprises:

In step S1021, by fingerprint image piecemeal and extract the local spectrum information of each piecemeal by windowing Fourier transform;

In step S1022, the frequency spectrum that conversion is obtained carries out filtering with corresponding Log Gabor wave filter;

In step S1023, with inverse Fourier transform, filtered spectrum information is become to spatial information;

In step S1024, extracting ridges combine the image that is enhanced from filtering image.

Fig. 3 shows the node relationships method for expressing under curvilinear coordinate system that the invention process case provides, and the method comprises:

In step S1031, take each node based on the field of direction, to set up curvilinear coordinate system as the former heart; X-axis is by carrying out track and extract along crestal line and valley line, and Y-axis is extracted along the direction vertical with crestal line, based on the field of direction, can calculate the coordinate of other node in this coordinate system.

In step S1032, based on these curvilinear coordinate systems, can extract coordinate and the b coordinate in the coordinate system of a of the coordinate relation between every couple of node a and b: a in the coordinate system of b;

In step S1033, carry out node pairing judgement, unpaired can mate deformation fingerprint.

If Y-axis identifies length with periodicity, so a pair of coordinate can reflect two internodal streakline numbers, insensitive to the variation of streakline spacing and curvature variation, has good deformation unchangeability.

The present invention is directed to the shortcoming that variance method carries out fingerprint segmentation, proposed a kind of improved fingerprint segmentation algorithm.

This method is first by the calculating to the number of pixels of the gray variance of fingerprint gray level image, variance gradient, gradient-norm and low gray shade scale, introduce the linear combination feature of variance and gradient-norm, according to the relation of this feature and average, choose suitable thresholding, tentatively distinguish foreground area and the background area of fingerprint, in recycling mathematical morphology, aftertreatment is cut apart in open and close computing, thereby obtains accurately complete fingerprint foreground area.

Propose the suitable LogGabor wave filter of structure and realize the enhancing of fingerprint image.

On linear frequency yardstick, the biography of LogGabor function

delivery function is defined as:

In formula, ω ₀centre frequency for wave filter.In order to guarantee the constant shape of wave filter, for different ω ₀should select κ to make κ/ω ₀remain unchanged.

Due to the singularity of Log Gabor function at initial point place, we can not directly construct the analytical expression of Log Gabor function in spatial domain, so the structure of wave filter should carry out in frequency domain.At frequency field structure Log Gabor wave filter, it comprises two parts: the radial component G that controls filter bandwidht _rand control the angle component G that filter direction is selected (r) _θ(θ), the Log Gabor filter function G (r, θ) of the two product complete, corresponding polar coordinates expression formula is as follows respectively:

$G_r\left(r\right)=\exp (-\frac{{\left(\ln (r/f_0)\right)}^2}{2\·{\left(\ln {\mathrm{\σ}}_f\right)}^2})$

$G_{\mathrm{\θ}}\left(\mathrm{\θ}\right)=\exp (-\frac{{(\mathrm{\θ}-{\mathrm{\θ}}_0)}^2}{2\·{{\mathrm{\σ}}_{\mathrm{\θ}}}^2})$

G(r,θ)＝G _r(r)·G _θ(θ)

In formula, r represents radial coordinate, and θ represents angle coordinate, f ₀centered by frequency, θ ₀for filter direction, σ _ffor determining radial bandwidth, B _f=2 (2/ln2) ^1/2| ln σ _f|, σ _θdetermine angle bandwidth, B _θ=2 (2/ln2) ^1/2σ _θ.

From the definition of wave filter, can find out, the performance of Log Gabor wave filter depends on four parameter: f ₀, θ ₀, σ _fand σ _θ.Wherein, the Fingerprint Image Enhancement of Log Gabor filtering is mainly by directional selectivity and the frequency f of Log Gabor wave filter ₀and θ ₀correspond respectively to local ridge frequency and the streakline direction of fingerprint image, σ _fand σ _θmainly select based on experience value.

The Fingerprint Image Enhancement based on Log Gabor filtering that the present invention adopts, it is mainly by directional selectivity and the frequency selectivity of Log Gabor wave filter, due to the singularity of logarithmic function at initial point place, can not in spatial domain, construct the analytic expression of Log Gabor function, therefore image filtering carries out in frequency domain, this just requires an original image correspondingly to transform in frequency domain.Spatial domain generally adopts Fourier transform to the conversion of frequency domain, in order to reduce calculated amount, has adopted windowing Fourier transform herein.Its flow process that strengthens algorithm is: (l) first by fingerprint image piecemeal and extract the local spectrum information of each piecemeal by windowing Fourier transform; (2) frequency spectrum then conversion being obtained carries out filtering with corresponding Log Gabor wave filter; (3) then with inverse Fourier transform, filtered spectrum information is become to spatial information; (4) last extracting ridges combine the image that is enhanced from filtering image.

Node relationships method for expressing under curvilinear coordinate system has been proposed.

The method be take each node and based on the field of direction, is set up curvilinear coordinate system as the former heart, and X-axis is by carrying out track and extract along crestal line and valley line, and Y-axis is extracted along the direction vertical with crestal line, based on the field of direction, can calculate the coordinate of other node in this coordinate system.Based on these curvilinear coordinate systems, can extract coordinate and the b coordinate in the coordinate system of a of the coordinate relation between every couple of node a and b: a in the coordinate system of b.If Y-axis identifies length with periodicity, so a pair of coordinate can reflect two internodal streakline numbers, insensitive to the variation of streakline spacing and curvature variation, has good deformation unchangeability.

The foregoing is only preferred embodiment of the present invention, not in order to limit the present invention, all any modifications of doing within the spirit and principles in the present invention, be equal to and replace and improvement etc., within all should being included in protection scope of the present invention.

Claims (6)

1. a fingerprint identification method, it is characterized in that, the method is first by the calculating to the number of pixels of the gray variance of fingerprint gray level image, variance gradient, gradient-norm and low gray shade scale, introduce the linear combination feature of variance and gradient-norm, according to the relation of this feature and average, choose suitable thresholding, tentatively distinguish foreground area and the background area of fingerprint, in recycling mathematical morphology, aftertreatment is cut apart in open and close computing, thereby obtains accurately complete fingerprint foreground area; Utilize Log Gabor wave filter to realize the enhancing of fingerprint image.

2. fingerprint identification method as claimed in claim 1, is characterized in that, on linear frequency yardstick, the transport function of Log Gabor function is defined as:

$G\left(\mathrm{\ω}\right)=\exp \left(\frac{-{\left(\ln (\mathrm{\ω}/{\mathrm{\ω}}_0)\right)}^2}{2{\left(\ln \left(\mathrm{\κ}/{\mathrm{\ω}}_0\right)\right)}^2}\right)$

In formula, ω ₀for the centre frequency of wave filter, in order to guarantee the constant shape of wave filter, for different ω ₀should select κ to make κ/ω ₀remain unchanged;

At frequency field structure Log Gabor wave filter, it comprises two parts: the radial component G that controls filter bandwidht _rand control the angle component G that filter direction is selected (r) _θ(θ), the Log Gabor filter function G (r, θ) of the two product complete, corresponding polar coordinates expression formula is as follows respectively:

$G_r\left(r\right)=\exp (-\frac{{\left(\ln (r/f_0)\right)}^2}{2\·{\left(\ln {\mathrm{\σ}}_f\right)}^2})$

$G_{\mathrm{\θ}}\left(\mathrm{\θ}\right)=\exp (-\frac{{(\mathrm{\θ}-{\mathrm{\θ}}_0)}^2}{2\·{{\mathrm{\σ}}_{\mathrm{\θ}}}^2})$

G(r,θ)＝G _r(r)·G _θ(θ)

In formula, r represents radial coordinate, and θ represents angle coordinate, f ₀centered by frequency, θ ₀for filter direction, σ _ffor determining radial bandwidth, B _f=2 (2/ln2) ^1/2| ln σ _f|, σ _θdetermine angle bandwidth, B _θ=2 (2/ln2) ^1/2σ _θ.

3. fingerprint identification method as claimed in claim 1, is characterized in that, the flow process that strengthens algorithm is: (l) first by fingerprint image piecemeal and extract the local spectrum information of each piecemeal by windowing Fourier transform; (2) frequency spectrum then conversion being obtained carries out filtering with corresponding Log Gabor wave filter; (3) then with inverse Fourier transform, filtered spectrum information is become to spatial information; (4) last extracting ridges combine the image that is enhanced from filtering image.

4. fingerprint identification method as claimed in claim 1, is characterized in that, the method further comprises:

By the calculating to the number of pixels of the gray variance of fingerprint gray level image, variance gradient, gradient-norm and low gray shade scale;

Introduce the linear combination feature of variance and gradient-norm, according to the relation of this feature and average, choose suitable thresholding, tentatively distinguish foreground area and the background area of fingerprint;

Utilize open and close computing in mathematical morphology to cut apart aftertreatment, thereby obtain accurately complete fingerprint foreground area.

5. fingerprint identification method as claimed in claim 1, is characterized in that, the suitable Log Gabor filtered method of structure that the method provides further comprises:

By fingerprint image piecemeal and extract the local spectrum information of each piecemeal by windowing Fourier transform;

The frequency spectrum that conversion is obtained carries out filtering with corresponding Log Gabor wave filter;

With inverse Fourier transform, filtered spectrum information is become to spatial information;

Extracting ridges combine the image that is enhanced from filtering image.

6. fingerprint identification method as claimed in claim 1, is characterized in that, the method further comprises

Node relationships method for expressing under curvilinear coordinate system, the method comprises:

Take each node sets up curvilinear coordinate system based on the field of direction as the former heart;

X-axis is by carrying out track and extract along crestal line and valley line, and Y-axis is extracted along the direction vertical with crestal line, based on the field of direction, can calculate the coordinate of other node in this coordinate system;

Based on these curvilinear coordinate systems, can extract coordinate and the b coordinate in the coordinate system of a of the coordinate relation between every couple of node a and b: a in the coordinate system of b;

Carry out node pairing judgement, unpaired can mate deformation fingerprint;

If Y-axis identifies length with periodicity, so a pair of coordinate can reflect two internodal streakline numbers, insensitive to the variation of streakline spacing and curvature variation, has deformation unchangeability.

Images