CN203733135U - Finger vein recognition system based on 808nm laser - Google Patents
Finger vein recognition system based on 808nm laser Download PDFInfo
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- CN203733135U CN203733135U CN201420100703.7U CN201420100703U CN203733135U CN 203733135 U CN203733135 U CN 203733135U CN 201420100703 U CN201420100703 U CN 201420100703U CN 203733135 U CN203733135 U CN 203733135U
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Abstract
The utility model discloses a finger vein recognition system based on 808nm laser, comprising a finger vein image acquisition sensor, a finger vein image processing module, a finger vein image recognition module, a storage unit, a micro control unit, a system power supply unit, an execution module and a man-machine interface. The finger vein image acquisition sensor includes a U-shaped groove finger contact glass, a light mixing film, an 808nm laser diode, an 808nm interference filter, a focusing lens, a lens cartridge, a CMOS imaging sensor, a circuit system and an outer package shell. 808nm infrared light is irradiated on fingers after being mixed, and is absorbed by deoxygenated hemoglobin in blood so as to enable an image focused and imaged on a CMOS after being reflected and penetrating through the 808nm interference filter to present a shadow zone, and then the obtained image is processed, a finger vein feature database is established, the similarity threshold value is set, and a person to be tested is recognized by matching finger vein data to be tested and the finger vein data in the feature database. The system adopts the 808nm laser diode and has the advantages of high light emitting power, strong penetrating capacity and strong detection signals.
Description
Technical field
The utility model belongs to living things feature recognition field, refers in particular to vein identification field, is specifically related to a kind of finger vein recognition system based on 808nm laser.
Background technology
In recent years, along with the development of computer technology and other association areas, information security is more and more paid close attention to by people, and authentication and identification are in whole information security system, and most important is also most basic part.Because people's physical trait is not reproducible and does not more become in time, biometrics identification technology starts to become the main direction of studying of authentication, but it is still in one progressively on stage of ripe, popularization and application at present.The feature of biometrics identification technology maximum is: uniqueness, security and convenience, as recognition of face, iris recognition and fingerprint recognition are used in as fields such as gate inhibition, enterprise's Work attendance management system safety certifications more and more widely for authenticating user identification provides safety, convenience, favourable approach, particularly fingerprint recognition.
Existing biometrics identification technology is as fingerprint recognition, recognitions of face etc. all belong to people's surface identification: on the one hand, these features are easily forged by people, as fingerprint film or people's face film etc.: on the other hand, the position of user's face and luminous environment around etc. all have considerable influence to face recognition, and fingerprint recognition also cannot be avoided doing, wet and dirty finger, or the impact of certain customers' finger surface peeling and scar.Iris recognition, as a kind of physical property contact biometrics identification technology that needs, can provide a fairly large number of unique point and affected by environment little, is one of biological identification technology that degree of accuracy is the highest, for the identity of high reliability is differentiated, is ideal; But because its sensor holds at high price, also cannot gear to the needs of the society and extensively promote the use of.
The principle that refers to vein identification is, because the deoxyhemoglobin in blood has absorption near infrared light 700-1000nm wave band, the small-sized imaging system with infrared induction degree is photographed facing to finger, just can extract the image that refers to vein blood vessel from shaded side, again the pattern obtaining is carried out to digital processing, make blood vessel pattern image.Refer to that first vein recognition system refers to vein distribution plan by referring to that vein image acquisition sensor obtains, to referring to that vein distribution plan carries out pre-service and sets up and refer to vein pattern database according to special-purpose alignment algorithm extraction eigenwert again, finally the finger vein image to be measured gathering be stored in database middle finger vein pattern point and compare, adopt complicated matching algorithm to referring to that vein pattern mates, thereby individual is carried out to identity authentication, and overall process adopts contactless
Owing to referring to that vein distributes, conceal in body interior, belong to inborn password, can not lose and forget, do not have imitated or stolen risk, everybody different and temporal evolution not, Image Acquisition mode is contactless, is not subject to the impact of external environment.Fingerprint recognition and recognition of face relatively, refers to that vein identification has higher Real time identification rate; And with respect to iris recognition, refer to that vein identification sensor price is medium, be conducive to promote; With respect to vena metacarpea, identify, refer to that vein identification sensor is simple in structure, size is little, more easily realizes miniaturization, integrated.
Summary of the invention
In order to overcome above-mentioned prior art shortcoming, the purpose of this utility model is to provide a kind of finger vein recognition system based on 808nm laser, and the finger vein image acquisition sensor penetration capacity of this system is strong, and detectable signal is strong, and signal to noise ratio (S/N ratio) is high.
The technical scheme that the utility model adopts is: a kind of finger vein recognition system based on 808nm laser, system comprises finger vein image acquisition sensor, refer to vein image processing module, refer to vein image identification module, storage unit, micro-control unit, SPU, execution module and man-machine interface, its middle finger vein image acquisition sensor is comprised of U-shaped groove finger contact glass, mixing film, 808nm laser diode, 808nm interference filter, condenser lens, lens card cylinder, cmos imaging sensor, Circuits System and outer package shell, its general structure is that U-shaped groove finger contact glass is positioned at whole finger vein image acquisition sensor upper surface, mixing film is plated in two inclined-planes of U-shaped groove finger contact glass, distance two 2~5mm place, inner side, plated film inclined-plane fixed placement 2 row are taken advantage of the 808nm laser diode of 2 row, array 808nm laser diode obtains system power supply by connecting bottom surface Circuits System, at place, distance U-shaped groove finger contact bath of glass plane lower surface 5mm left and right fixed in position lens card cylinder, lens card cylinder upper end is 808nm interference filter fixedly, condenser lens fixed in position at lens card cylinder middle part, under condenser lens, place cmos imaging sensor, cmos imaging sensor is fixed in Circuits System, Circuits System is fixed on encapsulating shell bottom, refer to that vein image identification module, storage element are connected with referring to vein image acquisition sensor by micro-control unit, refer to that vein image acquisition sensor is connected with referring to vein image processing module by USB interface, refer to that vein image processing module is connected with referring to vein image identification module, storage unit by USB interface, micro-control unit is connected with SPU, execution module and man-machine interface respectively by USB interface.
Described 808nm output power of laser diode is 200mW, and emission wavelength is 808nm ± 3nm, working current≤250mA, operating voltage≤1.2V.
Described cmos imaging sensor drives to obtain finger vein image by CPLD.
Described micro-control unit selects Cortex-M3 as main control chip, and described interface unit adopts RS232 interface, and whole system adopts 5V direct current supply.
The beneficial effects of the utility model are:
1. adopt 808nm laser diode, luminous power is large, guarantees to gather the impact that image does not allow to be subject to environment temperature and light; Penetration capacity is strong, can obviously weaken the shade of the inhomogeneous light of gathered image;
2. adopt 808nm interference filter to filter, improve system signal noise ratio.
Accompanying drawing explanation
Below in conjunction with drawings and Examples, the utility model is further illustrated.
Fig. 1 is finger vein image acquisition sensor construction schematic diagram of the present utility model;
Fig. 2 is system architecture diagram of the present utility model;
Fig. 3 is that the utility model refers to vein identification process figure;
In accompanying drawing: 1 is U-shaped groove finger contact glass; 2 is mixing film; 3 is 808nm laser diode; 4 is 808nm interference filter; 5 is condenser lens; 6 is cmos imaging sensor; 7 is Circuits System; 8 is lens card cylinder; 9 is outer package shell; 10 is finger.
Embodiment
Below in conjunction with structural principle of the present utility model and principle of work, elaborate:
As shown in Figure 1, refer to vein image acquisition sensor, comprise that U-shaped groove finger contact glass 1, mixing film 2,808nm laser diode 3,808nm interference filter 4, condenser lens 5, cmos imaging sensor 6, Circuits System 7, lens card cylinder 8 and outer package shell 9 form.People's finger 10 is placed in U-shaped groove finger contact glass 1 table plane; U-shaped groove finger contact glass 1 is positioned at whole finger vein image acquisition sensor upper surface; Mixing film 2 is plated in two inclined-planes of U-shaped groove finger contact glass 1, plays the effect of even light and acquisition platform; Distance two 2~5mm place, inner side, plated film inclined-plane fixed placement 2 row are taken advantage of the 808nm laser diode 3 of 2 row; Array 808nm laser diode 3 obtains system power supply by connecting bottom surface Circuits System 7; At U-shaped groove finger contact glass 1 place, the surface level lower surface 5mm left and right fixed in position lens card cylinder 8 of distance; Lens card cylinder 8 upper ends are 808nm interference filter 4 fixedly, avoids visible ray to enter collecting device, has further guaranteed to gather image and can not be subject to the impact of surround lighting; Condenser lens 5 fixed in position at lens card cylinder 8 middle parts; Under condenser lens 5, place cmos imaging sensor 6; Cmos imaging sensor 6 is fixed in Circuits System 7; Circuits System 7 is fixed on outer package shell 9 bottoms.With the laser diode of 808nm, irradiate finger, when four laser diodes (being LD array) are worked simultaneously, U-shaped groove finger contact temperature on glass can reach 37 ℃ of left and right, and in this temperature, can guarantee fully to point the normal expansion state of blood vessel, therefore no matter be to gather at what temperature, the Stability Analysis of Structures of the finger vena of collection; The penetration capacity of laser diode light is strong, and the shade that gathers the inhomogeneous light of image can significantly be weakened; Laser diode high-power can also guarantee to gather the impact that image does not allow to be subject to surround lighting.Transparent mixing film is plated in groove double inclined plane inner side, plays the effect of even light and acquisition platform; 808nm interference filter avoids visible ray to enter collecting device, has further guaranteed to gather image and can not be subject to the impact of surround lighting; Due to Infrared irradiation on finger time, the absorption of deoxyhemoglobin in blood near infrared light 700-1000nm wave band, the image that reflection enters cmos imaging sensor by condenser lens will produce dash area, just can extract the image that refers to vein blood vessel from shaded side.
As shown in Figure 2, a kind of finger vein recognition system block diagram based on 808nm laser, comprises and refers to vein image acquisition sensor, refer to vein image processing module, refer to vein image identification module, storage unit, micro-control unit, SPU, execution module and man-machine interface.By referring to that the collection of vein image acquisition sensor refers to intravenous angiography image, by USB interface, pass to and refer to vein image processing module, the image of handling well is passed to PC by USB interface and mate with the finger vein pattern image being originally stored in PC, matching result is passed to man-machine interface and execution module by microcontroller, and the SPU of whole system under controlling by MCU obtains power supply.
As shown in Figure 3, refer to vein identification process figure.
Step 1 is for carrying out pre-service to finger vein image: adopt the background separating method based on the field of direction, first by the gradient of each pixel in Sobel operator computed image, then image is divided into equal-sized overlapping region, and then calculate the statistical gradient of each subregion, then set a threshold value, and in conjunction with statistical gradient, calculate the edge of background image, finally, will effectively refer to that vein image partly proposes out, reaches the effect of background separation.
Step 2 is for being normalized finger vein image: according to the intensity profile of pixel, adopt histogrammic method, by referring to that the value of vein image by zonule normalizes to [0,1] this interval, to facilitate calculating.
Step 3 is for carrying out figure image intensifying to finger vein image: adopt NiBlack algorithm to strengthen image, consider the noise problem of cmos image sensor self and circuit, in order to improve signal to noise ratio (S/N ratio), the image after we adopt maximum-minimum filters to effective normalization carries out filtering.
Step 4 is for carrying out post-processed to finger vein image: the one, and some the isolated regions in removal of images, these regions show as cavity or spot in referring to vein image.For these regions, we take connected region elimination method to process them; The 2nd, " burr " pruned, so-called " burr " is exactly the rough phenomenon of finger intravenous line causing in Image Acquisition or image processing step above, if do not eliminate it, can bring very large impact to feature extraction algorithm below, adopt a kind of burr Pruning Algorithm based on minimum spanning tree, substantially can eliminate the burr referring to above intravenous line.
Step 5 is that binaryzation and extraction refer to vein pattern: point of crossing and the end points referring in vein image mainly extracted in feature extraction, because we operate on bianry image, therefore we can complete this work in 3 * 3 neighborhood, in this neighborhood, we only need to calculate 0 and 1 exchange times and just point of crossing and end points can be extracted.
Step 6 refers to vein pattern database for setting up: storage refers to vein pattern data, and corresponding finger vein pattern is set up to numbering and index by Competition coding mode;
Step 7 is for referring to vein pattern coupling: similarity threshold is set, personnel to be measured is referred to vein carries out 1: 1 or 1 with the finger vein pattern point in characteristic thesaurus: N's mates.1: 1 coupling refers to that the finger vein pattern that collects and the finger vein pattern of the database middle finger number of delimiting the organizational structure mate, speed fast (for judging); 1: N coupling is that in the finger vein that collects and database, all finger vein patterns mate (for identification), if the match is successful, provide the finger vein that the match is successful the numbering in database.In native system, we adopt the matching algorithm based on Hausdorff distance.
Step 8 feeds back to man-machine interface and execution module by the result after coupling by micro-control unit.
Claims (4)
1. the finger vein recognition system based on 808nm laser, system comprises and refers to vein image acquisition sensor, refers to vein image processing module, refers to vein image identification module, storage unit, micro-control unit, SPU, execution module and man-machine interface, its middle finger vein image acquisition sensor is comprised of U-shaped groove finger contact glass, mixing film, 808nm laser diode, 808nm interference filter, condenser lens, lens card cylinder, cmos imaging sensor, Circuits System and outer package shell, it is characterized in that, U-shaped groove finger contact glass is positioned at whole finger vein image acquisition sensor upper surface, mixing film is plated in two inclined-planes of U-shaped groove finger contact glass, distance two 2~5mm place, inner side, plated film inclined-plane fixed placement 2 row are taken advantage of the 808nm laser diode of 2 row, array 808nm laser diode obtains system power supply by connecting bottom surface Circuits System, at place, distance U-shaped groove finger contact bath of glass plane lower surface 5mm left and right fixed in position lens card cylinder, lens card cylinder upper end is 808nm interference filter fixedly, condenser lens fixed in position at lens card cylinder middle part, under condenser lens, place cmos imaging sensor, cmos imaging sensor is fixed in Circuits System, Circuits System is fixed on encapsulating shell bottom, refer to that vein image identification module, storage element are connected with referring to vein image acquisition sensor by micro-control unit, refer to that vein image acquisition sensor is connected with referring to vein image processing module by USB interface, refer to that vein image processing module is connected with referring to vein image identification module, storage unit by USB interface, micro-control unit is connected with SPU, execution module and man-machine interface respectively by USB interface.
2. a kind of finger vein recognition system based on 808nm laser as claimed in claim 1, is characterized in that, described 808nm output power of laser diode is 200mW, and emission wavelength is 808nm ± 3nm, working current≤250mA, operating voltage≤1.2V.
3. a kind of finger vein recognition system based on 808nm laser as claimed in claim 1, is characterized in that, described cmos imaging sensor drives to obtain finger vein image by CPLD.
4. a kind of finger vein recognition system based on 808nm laser as claimed in claim 1, is characterized in that, described micro-control unit selects Cortex-M3 as main control chip, and described interface unit adopts RS232 interface, and whole system adopts 5V direct current supply.
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Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
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CN107239772A (en) * | 2017-06-23 | 2017-10-10 | 深圳市利众信息科技有限公司 | Palm print and palm vein image collecting device and clearance gate |
CN109784141A (en) * | 2018-11-27 | 2019-05-21 | 中国船舶重工集团公司第七一八研究所 | A kind of finger vena identification encryption system based on arm processor |
CN112395981A (en) * | 2020-11-17 | 2021-02-23 | 华北电力大学扬中智能电气研究中心 | Authentication method, device, equipment and medium based on finger vein image |
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2014
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Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107239772A (en) * | 2017-06-23 | 2017-10-10 | 深圳市利众信息科技有限公司 | Palm print and palm vein image collecting device and clearance gate |
CN107239772B (en) * | 2017-06-23 | 2018-10-16 | 深圳市中识智能科技有限公司 | Palm print and palm vein image collecting device and clearance gate |
CN109784141A (en) * | 2018-11-27 | 2019-05-21 | 中国船舶重工集团公司第七一八研究所 | A kind of finger vena identification encryption system based on arm processor |
CN112395981A (en) * | 2020-11-17 | 2021-02-23 | 华北电力大学扬中智能电气研究中心 | Authentication method, device, equipment and medium based on finger vein image |
CN112395981B (en) * | 2020-11-17 | 2023-08-18 | 华北电力大学扬中智能电气研究中心 | Authentication method, device, equipment and medium based on finger vein image |
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