CN104809452A - Fingerprint identification method - Google Patents

Fingerprint identification method Download PDF

Info

Publication number
CN104809452A
CN104809452A CN201510253511.9A CN201510253511A CN104809452A CN 104809452 A CN104809452 A CN 104809452A CN 201510253511 A CN201510253511 A CN 201510253511A CN 104809452 A CN104809452 A CN 104809452A
Authority
CN
China
Prior art keywords
fingerprint
image
block
point
direction
Prior art date
Application number
CN201510253511.9A
Other languages
Chinese (zh)
Inventor
田野
夏梅宸
刘志才
祝昌宇
卢力君
Original Assignee
成都英力拓信息技术有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 成都英力拓信息技术有限公司 filed Critical 成都英力拓信息技术有限公司
Priority to CN201510253511.9A priority Critical patent/CN104809452A/en
Publication of CN104809452A publication Critical patent/CN104809452A/en

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00006Acquiring or recognising fingerprints or palmprints

Abstract

The invention provides a fingerprint identification method, which comprises the following steps of, in the process of identifying a fingerprint by utilizing a fingerprint identification device, first collecting the fingerprint, and then carrying out quality evaluation on a collected fingerprint image, and outputting a quality evaluation result onto a screen. The invention provides the fingerprint identification method; a user is enabled to intuitively know image quality; moreover, the identification success rate is improved; the fingerprint identification method is easy to realize; moreover, the execution efficiency is higher.

Description

A kind of fingerprint identification method

Technical field

The present invention relates to image procossing, particularly a kind of fingerprint identification method.

Background technology

Fingerprint is widely used in person identification means in worldwide.Fingerprint recognition has become a gordian technique of process individual affair and information security.In fingerprint image quality is evaluated, prior art evaluates fingerprint image quality by the contrast of each sub-block of the image that takes the fingerprint and curvature characteristic mass, but this method is just analyzed from partial fingerprint image texture, is not enough to reflect fingerprint image global information; Can not obtain the directional diagram of fingerprint image very well when picture noise is larger, the pseudo-random numbers generation elimination result in addition for the fingerprint image of non-homogeneous collection is not good enough, thus affects last finger print information extraction and identify.

Summary of the invention

For solving the problem existing for above-mentioned prior art, the present invention proposes a kind of fingerprint identification method, comprising:

Utilize fingerprint identification device to gather fingerprint, and quality assessment is carried out to the fingerprint image gathered, quality evaluation result is outputted to screen.

Preferably, the described fingerprint identification device that utilizes gathers fingerprint, comprise further and sampling to fingerprint grayscale image by the mode of dot interlace, dot interlace obtains original fingerprint gray level image, represents the local grain trend at each pixel place in described dot interlace original fingerprint gray level image with point directional image;

Calculated by fingerprint image point directional image, each image block in fingerprint image is divided into foreground blocks or background block, adopt 7 × 7 templates, reference point is positioned at template center, from horizontal level, determine a direction every π/4, definition I=1,2,3,4, corresponding 0, π/4,2 π/4,3 π/4, π four direction, calculates the grey scale change D of all directions i, compare D i, find minimum value, just represent the direction D of this point i:

D I=Σ|f’ I(i,j)-f I(i k,j k)|

F ' i(i, j) is the gray average along I direction is put, f i(i k, j k) be the gray-scale value of kth point on I direction, will be distributed with the foreground blocks of image block as image of fingerprint ridge line, remainder is background block, foreground blocks is set to 1, and background block is set to 0, and before realizing fingerprint grayscale image, Background is separated:

1) judge whether to meet: 6f i(i, j)+S min+ S max>0.75 Σ S iif meet, then current point is foreground point; Otherwise be background dot, wherein, f (i, j) is the gray-scale value that (i, j) puts; Σ S ifor adding up of gray-scale value on I direction; S maxfor the upper limit of accumulated value; S minfor the lower limit of accumulated value;

2) according to the ratio of background dot in fritter, judge that each image block is foreground blocks or background block, if the quantity of background dot exceedes threshold value T in fritter b, then by this image block block as a setting, otherwise foreground blocks is defined as.

Preferably, described fingerprint identification device comprises controller, and this controller connects LED screen, fingerprint sensor, JTAG debugging interface, reset circuit, outside SDRAM data-carrier store, serial ports and USB interface respectively; Wherein, described screen is used for showing the result that fingerprint image initial mass is evaluated, the placement location of prompting user finger; Fingerprint sensor is used for obtaining the information in fingerprint pointed; JTAG debugging interface is used for being connected with host computer debugging; Reset circuit is used for initialization fingerprint identification device; FLASH program storage be used for store fingerprint identification device run program; Outside SDRAM data-carrier store is used for storing the ephemeral data produced in fingerprint identification device operational process; Serial ports and USB interface are used for communicating with the connection of host computer.

The present invention compared to existing technology, has the following advantages:

The present invention proposes a kind of fingerprint identification method, allow user intuitively understand picture quality, and improve recognition success rate, be easy to realize, and execution efficiency is higher.

Accompanying drawing explanation

Fig. 1 is the process flow diagram of the fingerprint identification method according to the embodiment of the present invention.

Embodiment

Detailed description to one or more embodiment of the present invention is hereafter provided together with the accompanying drawing of the diagram principle of the invention.Describe the present invention in conjunction with such embodiment, but the invention is not restricted to any embodiment.Scope of the present invention is only defined by the claims, and the present invention contain many substitute, amendment and equivalent.Set forth many details in the following description to provide thorough understanding of the present invention.These details are provided for exemplary purposes, and also can realize the present invention according to claims without some in these details or all details.

An aspect of of the present present invention provides a kind of fingerprint identification method.Fig. 1 is the fingerprint identification method process flow diagram according to the embodiment of the present invention.First the present invention adopts the fingerprint identification device with information displaying, gather fingerprint and quality evaluation result is outputted to screen, achieve and improve fingerprint recognition success ratio, certain link allowing user intuitively understand fingerprint collecting goes wrong, and how to revise.Fingerprint identification device comprises controller, and controller connects LED screen, fingerprint sensor, JTAG debugging interface, reset circuit, outside SDRAM data-carrier store, serial ports and USB interface respectively with different interfaces; Power management module provides power management for the chip in each part mentioned above and circuit.Wherein, screen is used for showing the result that fingerprint image initial mass is evaluated, the placement location of prompting user finger; Fingerprint sensor is used for obtaining the information in fingerprint pointed; JTAG debugging interface is used for being connected with host computer debugging; Reset circuit is used for initialization fingerprint identification device; FLASH program storage be used for store fingerprint identification device run program; Outside SDRAM data-carrier store is used for storing the ephemeral data produced in fingerprint identification device operational process; Serial ports and USB interface are used for communicating with the connection of host computer; Controller is the core of fingerprint identification device, controls the operation of fingerprint identification device.

Controller is the chip of embedded fingerprint identification technology, the image acquisition of fingerprint, feature extraction, chip that aspect ratio is right can be realized on sheet, performance history is made to become simple, developer can realize the function of fingerprint recognition easily, the preferred controller of the present invention, adopt 32 risc processor kernels, built-in special DSP instruction set.There is SEA/RSA accelerating engine, tailor-made algorithm software, built-in 128KB high speed static random access memory, embed 1MB high-capacity FLASH, clock, symmetry algorithm engine accelerator, RSA encryption and decryption engine, tandom number generator on 64kB ROM and 4kB OTP ROM, and possess abundant external interface: 3 groups USART interfaces, intelligent card interface, sheet.

Fingerprint sensor is made up of sensor array, and each array is a metal electrode.Be placed on the corresponding point of the finger on sensitive face then as an other pole, its principle of work is the capacitance type sensor changing polar plate spacing, whole sensor reads by reading the instruction of inductor, and the size of pickup area is by the decision of register XSHIFT and YSHIFT value.

In fingerprint collecting input process, due to the reason such as fingerprint quality, riding position of finger, all possibly correctly finger print information cannot be identified.For improving fingerprint recognition efficiency, first quality assessment is carried out to the finger print information gathered.Safety governor carries out the sampling of fingerprint grayscale image dot interlace to fingerprint image, and fingerprint image point directional image calculates, and before fingerprint grayscale image, Background is separated, image processing process such as Fingerprint Image Quality Analysis, and showing evaluation result.If quality assessment is defective, according to display information, Resurvey information in fingerprint.

Sample to fingerprint grayscale image by the mode of dot interlace, dot interlace obtains original fingerprint gray level image, and the basis not changing fingerprint character code is reduced data acquisition amount.The local grain trend at each pixel place in described dot interlace original fingerprint gray level image is represented with point directional image, specific as follows:

Calculated by fingerprint image point directional image, each image block in fingerprint image is divided into foreground blocks or background block.Adopt 7 × 7 templates, reference point is positioned at template center, from horizontal level, determine a direction every π/4, definition I=1, and 2,3,4, corresponding 0, π/4,2 π/4,3 π/4, π four direction.Calculate the grey scale change D of all directions i, compare D i, find minimum value, just represent the direction of this point:

D I=Σ|f’ I(i,j)-f I(i k,j k)|

In formula, f ' i(i, j) is the gray average along I direction is put, f i(i k, j k) be the gray-scale value that I direction is put.The foreground blocks of image is the image block being distributed with fingerprint ridge line, and remainder is background block.Foreground blocks is set to 1, and background block is set to 0, before realizing fingerprint grayscale image, Background be separated.Specific as follows:

1) judge whether to meet: 6f i(i, j)+S min+ S max>0.75 Σ S i

Wherein, f (i, j) is the gray-scale value that (i, j) puts; S i=Σ f i(i k, j k) adding up for gray-scale value on I direction; S maxfor the upper limit of accumulated value; S minfor the lower limit of accumulated value.If meet the condition of formula, then current point is foreground point; Otherwise be background dot.

2) according to the ratio of background dot in fritter, judge that each image block is foreground blocks or background block.If the quantity of background dot exceedes threshold value T in fritter b, then think that this image block belongs to background block, otherwise be foreground blocks.

By picture quality Rule of judgment, compare quality assessment parameter Q and threshold value T q.If Q≤T q, illustrate that picture quality does not reach requirement, judge whether finger position is placed correctly.

Specific as follows:

1) whether belong to a certain specific direction according to each point in this block, judge whether a foreground image block has directivity characteristics;

2) calculate the direction of each image block, obtain the direction histogram of each piece.If the number of pixels with some direction D exceedes preset value T 1, then the characteristic direction of this block is marked as D;

3) ratio that the quality of fingerprint image can account for all fingerprint foreground pictures by calculating continuous print characteristic direction region is described.Take method of weighting, the image block that distance reference point is far away, the information that it comprises is more reliable, and its weights are also higher;

4) for the arbitrary image block x in fingerprint foreground picture i, its picture quality Q can be determined with the weights with continuous characteristic direction block with the ratio of the weights of all fingerprint foreground blocks;

5) by lower limit T that fingerprint image quality parameter Q and fingerprint image quality evaluate qcompare, if Q≤T q, then Image semantic classification is carried out; Otherwise departing from of finger position is analyzed, and shows corresponding suggestion content.

Whether the no matter fingerprint of which kind of type, exist a complete crestal line determine whether finger departs from by analyzing fingerprint image central area.The present invention uses the tracking based on directional diagram to judge, and whether the placement location pointed is correct.Specific as follows:

1) with the barycenter of foreground picture for initial point, build coordinate system;

2) at the left half axle of x-axis, a characteristic direction is selected not to be that the image block of 0 is as start reference image block;

3) whether belong to according to each point in block the characteristic direction that a certain certain party always judges image block.If block feature direction is 0, then reselect start reference image block; If block feature direction is not 0, then according to the direction of current image block, search for next image block to the right;

4) judge that the direction of this image block and previous image block changes.If the direction of image block and previous image block changes more than 90 °, show to undergo mutation in the direction of current image block, according to the continuity of crestal line, the direction of current image block is substituted the direction of previous image block, search for next image block on this basis;

5) if the direction of image block is no more than 90 °, then judge whether to search a complete crestal line.

If find complete crestal line, the fingerprint image of collection is correct, correct in onscreen cue input, terminates fingerprint image search; Otherwise, illustrate that current image block does not have enough close to the positive axis of x-axis, continue the next image block of search;

6) judge whether the negative semiaxis of x-axis completes search.If do not search for complete, then continue search; If the negative semiaxis of x-axis completes search, the positive axis of search x-axis;

7) positive axis of x-axis is searched in the opposite direction similarly.

If search a complete crestal line, then correct in onscreen cue input, terminate fingerprint image search; Otherwise continue search.If a complete crestal line all cannot be determined from the positive and negative semiaxis of x-axis, then show that this fingerprint image departs from, according to the position indicating user Resurvey fingerprint of barycenter.

According to the position of selected barycenter and the result of judgement, show on screen respectively.

Before carrying out feature extraction and matching, pre-service must be carried out to fingerprint image, recover dactylotype, so that the fingerprint characteristic that reliable extraction is correct.The complexity that direct effect characteristics extracts and mates by result, is related to the discrimination of whole algorithm.The present invention is directed to the problem that conventional fingerprint recognizer complexity is higher, computing is consuming time, consider system hardware platform features, existing algorithm is optimized.The fingerprint recognition optimized comprises fingerprint image preprocessing and feature point extraction and mates.Wherein pre-service comprises: the deletion of Iamge Segmentation, image enhaucament, binaryzation and aftertreatment, refinement and pseudo-random numbers generation.Because picture quality is different, can not directly split.

First adopt 3 × 3 Gaussian template filtering, remove the partial noise in image, make the texture of fingerprint image more level and smooth.Different for picture quality, to the process of fingerprint image unified specification, make all fingerprint images all have unified average and mean square deviation, reduce the gray difference between the crestal line of fingerprint and valley line simultaneously.Normalization and Iamge Segmentation flow process as follows:

(1) original image gray average and gray scale mean square deviation is obtained.

E ( G ) = 1 M × N Σ i = 0 M - 1 Σ j = 0 N - 1 G ( i , j )

V ( G ) = 1 M × N Σ i = 0 M - 1 Σ j = 0 N - 1 [ G ( i , j ) - E ( G ) ] 2

Obtain the image intensity value after normalization.

G , ( i , j ) = E 0 + V 0 × ( G ( i , j ) - E ( G ) ) 2 V ( G ) G ( i , j ) > E ( G ) E 0 - V 0 × ( G ( i , j ) - E ( G ) ) 2 V ( G ) G ( i , j ) ≤ E ( G )

Wherein, G (i, j) represents that original fingerprint image is at (i, j) gray-scale value of place's pixel, M, N are the height and the width of fingerprint image, the gray average that E (G) is former fingerprint image, the gray scale mean square deviation that V (G) is former fingerprint image, E 0, V 0for gray average and the gray scale mean square deviation of expectation, generally experimentally choose moderate expectation value; G'(i, j) represent the gray-scale value of the fingerprint image after regularization at (i, j) place pixel.The present invention preferably chooses E 0=100, V 0=100.

(3) Sobel operator asks gradient and block gradient segmentation.

In conjunction with fingerprint image gray scale mean square deviation and directional information, by fingerprint image piecemeal, utilize Sobel operator to calculate each pixel gradient respectively, and obtain block gradient average and block gradient mean square deviation.Get the block gradient standard deviation sum of all directions as block eigenvalue, then the segmentation threshold that average finds out block gradient is got to block eigenvalue, be greater than threshold portion as fingerprint image prospect, be less than threshold value as fingerprint image background.

Image enhancement processes comprises: image smoothing, directional diagram and discretize and filtering.

Irregular noise extracts the accuracy of Fingerprint diretion and has a great impact, and in order to the field of direction that takes the fingerprint more accurately, first to picture smooth treatment, removes irregular noise.G (i, j) is the pixel value at (i, j) place.Adopt 3 × 3 templates to pixel (i, j) eight neighborhood obtains mean value E'(i, j), if | G'(i, j)-E'(i, j) | be greater than predetermined threshold value, then think that this place's pixel value is noise pixel, with E'(i, j) replace G'(i, j) as the pixel value at (i, j) place.Sobel operator is adopted to level and smooth fingerprint image, obtains the transverse gradients at pixel (i, j) place and longitudinal gradient, and fingerprint ridge direction span is defined as between [0 °, 180 °].Get a direction every 22.5 °, amount to 8 general orientation.Calculate the general direction of pixel crestal line, Choose filtering window be 5 × 5 this directional diagram of low-pass filter filter correction obtain smoothly discrete directional diagram.

Filtering Template according to structure construction eight directions of linear space carries out medium filtering.To remove in image noise region little compared with filtering size through medium filtering, filter function be expressed as:

g uv ( x , y ) = k 2 σ 2 exp [ - k 2 ( x 2 + y 2 ) 2 σ 2 ] · [ exp ( ik · x y ) - exp ( - σ 2 2 ) ]

k = k v cos α k v sin α , k v = 2 - v + 2 2 π

α=uπ/k

The value of v determines the wavelength of filtering, and the value of u represents the direction of kernel function, and K represents total direction number.Parameter σ/k determines the size of Gauss's window, gets here 4 frequencies (v=0,1,2,3) are got in program, 8 directions (i.e. K=8, u=0,1 ..., 7), totally 32 kernel functions.

In order to remove edge fog effect as much as possible, it is Hx=0.1 (1,0,2,0,4,0 that the present invention sets tangential direction Filtering Template parameter, 2,0,1), normal direction Filtering Template is Hy=1/3 (-1,0 ,-2,0,9,0 ,-2,0 ,-1), rectangular filter process is adopted.Rectangular filter is estimated with tangential direction and normal direction 2 one-dimensional filtering devices.In conjunction with medium filtering, first normal direction sharpening is carried out to fingerprint image, then it is level and smooth to carry out tangential direction.

In image binaryzation process, comprise the following steps:

(1) fingerprint image after segmentation is divided into the wicket that n pixel is identical, window pixel number is W.The all pixel summations of each window are averaged as p i, getting empirical value is ω, and dynamic window threshold value T is met:

T=p i

p i=G' 1+G' 2+…+G' W/W

(2) some assignment pixel values all in window being greater than T is 1, and the some assignment being less than T is 0.

(3) white point in searching image, searches for and adds up this white point four neighborhood stain number N 1points N black in eight neighborhood 2if, N 2>=7 or N 1>=3, N 2>=5, then this eight connected region white point is filled to stain, otherwise the number TR of white point in statistics white point eight connected region R, it is W that threshold value is analyzed in setting 1if, TR≤W 1, to connected domain R, add up and judge the pixel distance S of 2 stains adjacent with a certain row (column) white point respectively x(S y), if all S x(S y)≤W2, is filled to stain by this eight connected region white point.Otherwise, the white point that mark connected domain is corresponding.

(4) until when there is not unlabelled white point in repetitive operation, and image negate look, returns (3); After processing completely, negate obtains final image again.

Thinning process adopts mathematics to table look-up refinement.Crestal line pixel after refinement can be divided into isolated point, end points, interior point, bifurcation according to eight neighborhood feature.In order to delete pseudo-random numbers generation better, threshold value being chosen and adopts statistics to be averaging, automatic selected threshold.

As follows for judging the formula of eight neighborhood central point attribute:

Wherein, P'(8)=P'(0), P'(i) represent the value of i-th neighborhood territory pixel point in eight neighborhood, if pixel is white point, then P'(i)=1; If stain, P'(i)=0.Y characterizes the attribute that crestal line is put, Y=0,1, the central point of 2 corresponding eight neighborhood is respectively isolated point, end points, interior point, Y >=3, central point is bifurcation.The present invention, in conjunction with the directional information of fingerprint and threshold information, provides pseudo-random numbers generation delet method.Concrete steps are as follows:

(1) in conjunction with the partial structurtes information of unique point, judge the attribute of fingerprint image black pixel point, after all Edge Feature Points of filtering, mark all accurate unique points.

(2) judge that accurate unique point belongs to isolated point, end points, bifurcation successively.Isolated point is directly deleted; For end points, judge whether the pixel number in this connected domain is greater than threshold value M 1if be greater than threshold value, store, otherwise delete; Bifurcation is judged whether 3 adjacent crestal lines are greater than threshold value M successively 1if be all greater than threshold value M 1then store, otherwise, if having one to mark crestal line pixel number be not more than threshold value, then delete and be not more than threshold value M 1gauge point; If have 2 to mark crestal line pixel number be not more than threshold value M 1, judge that these 2 crestal lines are in tangential direction corresponding to central spot, and contrast with the tangential direction of the 3rd article of crestal line, retain the crestal line that tangential direction is close, another is filled.

(3) by crestal line directional information and correlativity, the comparatively large and unique point pixel distance of filtering relevance is not more than M 1unique point, be left for obtain real features point.

In sum, the present invention proposes a kind of fingerprint identification method, allow user intuitively understand picture quality, and improve recognition success rate, be easy to realize, and execution efficiency is higher.

Obviously, it should be appreciated by those skilled in the art, above-mentioned of the present invention each module or each step can realize with general computing system, they can concentrate on single computing system, or be distributed on network that multiple computing system forms, alternatively, they can realize with the executable program code of computing system, thus, they can be stored and be performed by computing system within the storage system.Like this, the present invention is not restricted to any specific hardware and software combination.

Should be understood that, above-mentioned embodiment of the present invention only for exemplary illustration or explain principle of the present invention, and is not construed as limiting the invention.Therefore, any amendment made when without departing from the spirit and scope of the present invention, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.In addition, claims of the present invention be intended to contain fall into claims scope and border or this scope and border equivalents in whole change and modification.

Claims (3)

1. a fingerprint identification method, is characterized in that, comprising:
Utilize in fingerprint identification device identification fingerprinting process, first fingerprint is gathered, then quality assessment is carried out to the fingerprint image gathered, quality evaluation result is outputted to screen.
2. method according to claim 1, it is characterized in that, the described fingerprint identification device that utilizes gathers fingerprint, comprise further and by the mode of dot interlace, fingerprint grayscale image being sampled, dot interlace obtains original fingerprint gray level image, represents the local grain trend at each pixel place in described dot interlace original fingerprint gray level image with point directional image;
Calculated by fingerprint image point directional image, each image block in fingerprint image is divided into foreground blocks or background block, adopt 7 × 7 templates, reference point is positioned at template center, from horizontal level, determine a direction every π/4, definition I=1,2,3,4, corresponding 0, π/4,2 π/4,3 π/4, π four direction, calculates the grey scale change D of all directions i, compare D i, find minimum value, just represent the direction D of this point i:
D I=Σ|f’ I(i,j)-f I(i k,j k)|
F ' i(i, j) is the gray average along I direction is put, f i(i k, j k) be the gray-scale value of kth point on I direction, will be distributed with the foreground blocks of image block as image of fingerprint ridge line, remainder is background block, foreground blocks is set to 1, and background block is set to 0, and before realizing fingerprint grayscale image, Background is separated:
1) judge whether to meet: 6f i(i, j)+S min+ S max>0.75 Σ S iif meet, then current point is foreground point; Otherwise be background dot, wherein, f (i, j) is the gray-scale value that (i, j) puts; Σ S ifor adding up of gray-scale value on I direction; S maxfor the upper limit of accumulated value; S minfor the lower limit of accumulated value;
2) according to the ratio of background dot in fritter, judge that each image block is foreground blocks or background block, if the quantity of background dot exceedes threshold value T in fritter b, then by this image block block as a setting, otherwise foreground blocks is defined as.
3. method according to claim 2, it is characterized in that, described fingerprint identification device comprises controller, and this controller connects LED screen, fingerprint sensor, JTAG debugging interface, reset circuit, outside SDRAM data-carrier store, serial ports and USB interface respectively; Wherein, described screen is used for showing the result that fingerprint image initial mass is evaluated, the placement location of prompting user finger; Fingerprint sensor is used for obtaining the information in fingerprint pointed; JTAG debugging interface is used for being connected with host computer debugging; Reset circuit is used for initialization fingerprint identification device; FLASH program storage be used for store fingerprint identification device run program; Outside SDRAM data-carrier store is used for storing the ephemeral data produced in fingerprint identification device operational process; Serial ports and USB interface are used for communicating with the connection of host computer.
CN201510253511.9A 2015-05-19 2015-05-19 Fingerprint identification method CN104809452A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201510253511.9A CN104809452A (en) 2015-05-19 2015-05-19 Fingerprint identification method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510253511.9A CN104809452A (en) 2015-05-19 2015-05-19 Fingerprint identification method

Publications (1)

Publication Number Publication Date
CN104809452A true CN104809452A (en) 2015-07-29

Family

ID=53694263

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510253511.9A CN104809452A (en) 2015-05-19 2015-05-19 Fingerprint identification method

Country Status (1)

Country Link
CN (1) CN104809452A (en)

Cited By (22)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105303174A (en) * 2015-10-19 2016-02-03 广东欧珀移动通信有限公司 Fingerprint input method and device
CN105549872A (en) * 2015-10-30 2016-05-04 东莞酷派软件技术有限公司 Touch screen navigation method based on fingerprint identifier, and relevant equipment
CN105788048A (en) * 2016-04-13 2016-07-20 时建华 Electronic lock system achieving recognition through fingerprints
CN105827226A (en) * 2016-04-13 2016-08-03 时建华 Control switch performing identification through fingerprints
CN105825206A (en) * 2016-04-13 2016-08-03 时建华 Household appliance automatic regulation and control device having identity identification function
CN105868698A (en) * 2016-03-25 2016-08-17 东华大学 Embedded type fingerprint recognition system based on Cortex-M3 core
CN105912955A (en) * 2016-04-13 2016-08-31 时建华 Movable storage equipment with identity authentication function
CN105913520A (en) * 2016-04-13 2016-08-31 时建华 Elevator car using fingerprint for identification
CN105912907A (en) * 2016-04-13 2016-08-31 时建华 Mobile terminal with identity authentication function
CN105913027A (en) * 2016-04-13 2016-08-31 时建华 Data transmission method with high safety
CN105931324A (en) * 2016-04-13 2016-09-07 时建华 Door lock recognized through fingerprint
CN105931322A (en) * 2016-04-13 2016-09-07 时建华 Central air conditioning system with identity recognition function
CN105931320A (en) * 2016-04-13 2016-09-07 时建华 Image control device with identity recognition function
CN105931319A (en) * 2016-04-13 2016-09-07 时建华 Device for safely opening cabinet
CN105930776A (en) * 2016-04-13 2016-09-07 时建华 High tension switchgear with identity verification function
CN105930777A (en) * 2016-04-13 2016-09-07 时建华 ATM (Automatic Teller Machine) using fingerprint for identification
CN106485823A (en) * 2016-11-09 2017-03-08 太原理工大学 The certification gate control system of the User Defined gesture based on WISP label and authentication method
CN107087075A (en) * 2017-04-28 2017-08-22 维沃移动通信有限公司 A kind of reminding method and mobile terminal based on screen fingerprint recognition
CN107194325A (en) * 2017-04-28 2017-09-22 广东欧珀移动通信有限公司 Palmmprint acquisition method and Related product
CN107341437A (en) * 2016-05-03 2017-11-10 联咏科技股份有限公司 The method of fingerprint acquisition apparatus and sensing fingerprint
CN108764015A (en) * 2015-10-19 2018-11-06 广东欧珀移动通信有限公司 A kind of acquisition methods, device and the mobile terminal of fingerprint image to be identified
CN109949028A (en) * 2019-02-19 2019-06-28 江苏金农股份有限公司 One kind having intelligent settlement network payment system

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050238212A1 (en) * 2004-04-23 2005-10-27 Sony Corporation System for fingerprint image reconstruction based on motion estimate across a narrow fingerprint sensor
CN101901336A (en) * 2010-06-11 2010-12-01 哈尔滨工程大学 Fingerprint and finger vein bimodal recognition decision level fusion method
CN102567993A (en) * 2011-12-15 2012-07-11 中国科学院自动化研究所 Fingerprint image quality evaluation method based on main component analysis
CN103065134A (en) * 2013-01-22 2013-04-24 江苏超创信息软件发展股份有限公司 Fingerprint identification device and method with prompt information

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050238212A1 (en) * 2004-04-23 2005-10-27 Sony Corporation System for fingerprint image reconstruction based on motion estimate across a narrow fingerprint sensor
CN101901336A (en) * 2010-06-11 2010-12-01 哈尔滨工程大学 Fingerprint and finger vein bimodal recognition decision level fusion method
CN102567993A (en) * 2011-12-15 2012-07-11 中国科学院自动化研究所 Fingerprint image quality evaluation method based on main component analysis
CN103065134A (en) * 2013-01-22 2013-04-24 江苏超创信息软件发展股份有限公司 Fingerprint identification device and method with prompt information

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
付玉虎等: ""基于方向图和Gabor滤波的指纹预处理算法"", 《计算机与现代化》 *

Cited By (26)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105303174A (en) * 2015-10-19 2016-02-03 广东欧珀移动通信有限公司 Fingerprint input method and device
CN105303174B (en) * 2015-10-19 2019-12-10 Oppo广东移动通信有限公司 fingerprint input method and device
CN108764015A (en) * 2015-10-19 2018-11-06 广东欧珀移动通信有限公司 A kind of acquisition methods, device and the mobile terminal of fingerprint image to be identified
US10628694B2 (en) 2015-10-19 2020-04-21 Guangdong Oppo Mobile Telecommunications Corp., Ltd. Fingerprint enrolling method, apparatus, and terminal device
CN105549872A (en) * 2015-10-30 2016-05-04 东莞酷派软件技术有限公司 Touch screen navigation method based on fingerprint identifier, and relevant equipment
CN105868698A (en) * 2016-03-25 2016-08-17 东华大学 Embedded type fingerprint recognition system based on Cortex-M3 core
CN105931324A (en) * 2016-04-13 2016-09-07 时建华 Door lock recognized through fingerprint
CN105913520A (en) * 2016-04-13 2016-08-31 时建华 Elevator car using fingerprint for identification
CN105912907A (en) * 2016-04-13 2016-08-31 时建华 Mobile terminal with identity authentication function
CN105913027A (en) * 2016-04-13 2016-08-31 时建华 Data transmission method with high safety
CN105912955A (en) * 2016-04-13 2016-08-31 时建华 Movable storage equipment with identity authentication function
CN105931322A (en) * 2016-04-13 2016-09-07 时建华 Central air conditioning system with identity recognition function
CN105931320A (en) * 2016-04-13 2016-09-07 时建华 Image control device with identity recognition function
CN105827226A (en) * 2016-04-13 2016-08-03 时建华 Control switch performing identification through fingerprints
CN105930776A (en) * 2016-04-13 2016-09-07 时建华 High tension switchgear with identity verification function
CN105930777A (en) * 2016-04-13 2016-09-07 时建华 ATM (Automatic Teller Machine) using fingerprint for identification
CN105788048A (en) * 2016-04-13 2016-07-20 时建华 Electronic lock system achieving recognition through fingerprints
CN105825206A (en) * 2016-04-13 2016-08-03 时建华 Household appliance automatic regulation and control device having identity identification function
CN105931319A (en) * 2016-04-13 2016-09-07 时建华 Device for safely opening cabinet
CN107341437A (en) * 2016-05-03 2017-11-10 联咏科技股份有限公司 The method of fingerprint acquisition apparatus and sensing fingerprint
CN106485823B (en) * 2016-11-09 2018-08-21 太原理工大学 The certification access control system and authentication method of User Defined gesture based on WISP labels
CN106485823A (en) * 2016-11-09 2017-03-08 太原理工大学 The certification gate control system of the User Defined gesture based on WISP label and authentication method
CN107194325A (en) * 2017-04-28 2017-09-22 广东欧珀移动通信有限公司 Palmmprint acquisition method and Related product
CN107087075A (en) * 2017-04-28 2017-08-22 维沃移动通信有限公司 A kind of reminding method and mobile terminal based on screen fingerprint recognition
CN107087075B (en) * 2017-04-28 2020-04-17 维沃移动通信有限公司 Prompting method based on screen fingerprint identification and mobile terminal
CN109949028A (en) * 2019-02-19 2019-06-28 江苏金农股份有限公司 One kind having intelligent settlement network payment system

Similar Documents

Publication Publication Date Title
Timofte et al. Multi-view traffic sign detection, recognition, and 3D localisation
Neumann et al. Real-time scene text localization and recognition
Alexe et al. Measuring the objectness of image windows
TWI654567B (en) Method and apparatus for extracting specific information from standard cards
US8594431B2 (en) Adaptive partial character recognition
CN104809481B (en) A kind of natural scene Method for text detection based on adaptive Color-based clustering
US8983200B2 (en) Object segmentation at a self-checkout
CN104700099B (en) The method and apparatus for recognizing traffic sign
CN105528604B (en) A kind of bill automatic identification and processing system based on OCR
Shi et al. Automatic road crack detection using random structured forests
Tombari et al. Performance evaluation of 3D keypoint detectors
Deb et al. Vehicle License Plate Detection Method Based on Sliding Concentric Windows and Histogram.
US10229346B1 (en) Learning method, learning device for detecting object using edge image and testing method, testing device using the same
Shi et al. Spectral–spatial classification and shape features for urban road centerline extraction
Mariano et al. Performance evaluation of object detection algorithms
JP2014232533A (en) System and method for ocr output verification
CN104298982B (en) A kind of character recognition method and device
US6895104B2 (en) Image identification system
CN101650783B (en) Image identification method and imaging apparatus
JP5506785B2 (en) Fingerprint representation using gradient histogram
Huang et al. Road centreline extraction from high‐resolution imagery based on multiscale structural features and support vector machines
CN104680127A (en) Gesture identification method and gesture identification system
CN101558431B (en) Face authentication device
CN104217202B (en) Information identifying method, equipment and system
CN104766046B (en) One kind is detected using traffic mark color and shape facility and recognition methods

Legal Events

Date Code Title Description
PB01 Publication
C06 Publication
SE01 Entry into force of request for substantive examination
EXSB Decision made by sipo to initiate substantive examination
RJ01 Rejection of invention patent application after publication

Application publication date: 20150729

RJ01 Rejection of invention patent application after publication