CN105224906B - Palm vein recognition intelligent system - Google Patents
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- CN105224906B CN105224906B CN201410227590.1A CN201410227590A CN105224906B CN 105224906 B CN105224906 B CN 105224906B CN 201410227590 A CN201410227590 A CN 201410227590A CN 105224906 B CN105224906 B CN 105224906B
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- 210000003462 vein Anatomy 0.000 title claims abstract description 116
- 230000003287 optical effect Effects 0.000 claims abstract description 29
- 238000003384 imaging method Methods 0.000 claims abstract description 20
- 238000012549 training Methods 0.000 claims abstract description 20
- 238000000034 method Methods 0.000 claims abstract description 9
- 230000005540 biological transmission Effects 0.000 claims abstract description 8
- 238000004891 communication Methods 0.000 claims abstract description 4
- 238000005259 measurement Methods 0.000 claims abstract description 4
- 239000011159 matrix material Substances 0.000 claims description 9
- 238000005286 illumination Methods 0.000 claims description 6
- 238000012545 processing Methods 0.000 claims description 6
- 238000012360 testing method Methods 0.000 claims description 6
- 238000012795 verification Methods 0.000 claims description 6
- 230000004927 fusion Effects 0.000 claims description 3
- 238000000605 extraction Methods 0.000 claims description 2
- 230000007613 environmental effect Effects 0.000 abstract description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 208000032544 Cicatrix Diseases 0.000 description 1
- 238000005299 abrasion Methods 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000008280 blood Substances 0.000 description 1
- 210000004369 blood Anatomy 0.000 description 1
- 210000004204 blood vessel Anatomy 0.000 description 1
- 238000011109 contamination Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 210000002837 heart atrium Anatomy 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 238000007670 refining Methods 0.000 description 1
- 231100000241 scar Toxicity 0.000 description 1
- 230000037387 scars Effects 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/14—Vascular patterns
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Abstract
The invention belongs to the field of biological identification, and particularly relates to a palm vein identification intelligent system for intelligent identification. The wireless identification device comprises an imaging circuit, a lighting circuit, an identification module and a wireless transmission module; the imaging circuit comprises a CCD camera, an optical lens and an optical filter; the lighting circuit consists of near-infrared LEDs; the identification module comprises an identification unit, an electronic distance measurement unit and a voice unit, and the wireless transmission module transmits video information and control signals to the computer and realizes communication with the computer. By means of the training and feature matching method, the response speed can be kept within 8s, interference of environmental factors on palm vein recognition can be accurately eliminated, and accuracy and efficiency of palm vein recognition are improved.
Description
Technical Field
The invention belongs to the field of biological identification, and particularly relates to a palm vein identification intelligent system for intelligent identification.
Background
The veins are the vessels that lead blood back to the heart, originating in the capillaries, ending in the atrium, and the superficial veins are visible subcutaneously. The palm vein, as the name implies, is the internal palm vein. The palm vein recognition is a kind of vein recognition, belongs to biological recognition, and the palm vein recognition system is characterized in that a palm vein distribution diagram of an individual is obtained through a vein recognition instrument, a characteristic value is extracted from the palm vein distribution diagram according to a special comparison algorithm, images of veins of a finger, a palm and a back of the hand are obtained through an infrared CCD camera, a digital image of the veins is stored in a computer system, and the characteristic value is stored. When vein is compared, a vein image is adopted in real time, characteristic values are extracted, advanced filtering, image binarization and refining means are used for extracting characteristics of the digital image, the characteristics are compared with vein characteristic values stored in a host computer, and a complex matching algorithm is used for matching the vein characteristics, so that identity identification is carried out on individuals, and the identities are confirmed.
When the palm vein is used for identity authentication, the image characteristics of the palm vein are acquired, and the image characteristics exist only when the palm is a living body. In this system, the palm of the non-living body is not provided with the vein image features and thus cannot be identified, and thus cannot be counterfeited. When the palm vein is used for identity authentication, the image characteristics of the veins inside the palm are acquired, but not the image characteristics of the palm surface. Therefore, there is no recognition obstacle due to damage, abrasion, dryness, or too wet of the palm surface, etc. The palm vein is used for identity authentication, and when the palm vein image is obtained, the palm does not need to be in contact with equipment, and the palm can be recognized by slightly placing the palm vein image. This approach avoids the problem of insanitation when the hand is touching the device and the safety problems associated with the possible duplication of finger surface features and avoids the psychological discomfort of being considered as an object of examination and also does not become unrecognizable after contamination with dirt. The palm vein mode is almost suitable for all users because the veins are positioned in the palm, and the influence degree of external factors such as air temperature and the like can be ignored. The user acceptance is good. In addition to not requiring direct contact with the scanner surface, this non-invasive scanning process is simple and natural, alleviating the user's resistance that may be present due to concerns about hygiene or bothersome use. Because of the above living body identification, internal features and non-contact 3 aspects of features, the palm vein feature of the user is ensured to be difficult to forge. Therefore, the palm vein recognition system has high safety level and is particularly suitable for places with high safety requirements. The traditional vein recognition algorithm and how to use an expensive DSP processor to process floating point operation and improve the real-time requirement, and shorten the recognition time, the palm vein still has the following technical problems to be solved at present: and (1) belongs to internal physiological characteristics, cannot be worn, is difficult to forge and has high safety. (2) The blood vessel features are usually more obvious, easy to identify and good in anti-interference performance. (3) The non-contact measurement can be realized, the sanitation is good, and the method is easy to accept by users. (4) Is not easily affected by the scars or oil stains on the surface of the hand. The above techniques have the disadvantages that: the acquisition equipment has special requirements, relatively complex design and high manufacturing cost.
Disclosure of Invention
1. The object of the invention is to provide a method for producing a high-quality glass.
The invention provides a palm vein recognition intelligent system for intelligent recognition, which aims to improve the recognition accuracy of palm veins and solve the problem of low accuracy caused by environmental interference or different palm placing angles in the prior art.
2. The technical scheme adopted by the invention is disclosed.
The palm vein identification intelligent system comprises an imaging circuit, a lighting circuit, an identification module and a wireless transmission module; the imaging circuit comprises a CCD camera, an optical lens and an optical filter; the lighting circuit consists of near-infrared LEDs; the identification module comprises an identification unit, an electronic distance measurement unit and a voice unit, the wireless transmission module transmits video information and control signals to a computer and realizes communication with the computer, and the identification module identifies the palm vein according to the following steps:
firstly, training and projecting palm vein images, and obtaining five candidate palm vein images through matching of a classifier;
secondly, finding the best test image from five candidate palm vein images in the classifier:
a. loading all palm vein image training sets, and corresponding to the candidate palm veins;
b. extracting the deformation of each palm vein from the training set by using the fusion palm vein description;
c. extracting deformation of the palm vein test image, which is expressed as Dq;
d. matching the Dq with the five previous candidate palm vein images to find the number of matching key points
And thirdly, determining a verification criterion according to the number of the matching key points, setting the palm vein descriptor with the maximum number of the matching points as a most probable item, and obtaining a target palm vein image through feature matching.
preferably, in the third step, for the matching process, the palm veins are classified by using the euclidean distance based on the nearest neighbor rule, negative samples, that is, the non-training palm vein image and the non-palm vein image, are used to define a threshold for palm vein verification, if the minimum score is lower than the defined threshold, the input data is considered to be a known positive candidate palm vein, and otherwise, the input data is considered to be a negative palm vein image or an unknown palm vein image.
Preferably, in the first step, the image of the palm vein and the image of the palm vein with the query are preprocessed, feature extraction, training and projection are respectively performed, and the trained palm vein stroke projection and the data matrix are performed.
Preferably, in the imaging circuit, the optical lens is a large-view-field optical lens, the optical filter is an infrared-transmitting optical filter with a cut-off wavelength of 720nm, the optical lens is mounted on the near-infrared camera, and the infrared-transmitting optical filter is embedded in the front panel of the shell and positioned in front of the optical lens.
Preferably, the recognition module measures the palm distance information of the user through the electronic distance measuring unit, the control circuit sends a corresponding instruction to the voice unit, and the voice unit gives a prompt of the moving direction of the user.
Preferably, the electronic distance measuring unit in the identification module is an ultrasonic or infrared distance measuring module, and measures the palm distance information of the user in real time; the voice unit adopts a special voice processing chip and is provided with a high-sensitivity loudspeaker, and voice to be broadcasted is burnt into FLASH of the voice processing chip in advance.
Preferably, the single chip microcomputer in the identification module is used as a main control chip of the system, and the single chip microcomputer reads the distance information of the electronic distance measuring unit in real time and judges whether the palm of the user is in a clear imaging range or not; if the imaging range exceeds the clear imaging range, the singlechip sends a corresponding instruction to the voice unit to control the voice unit to broadcast corresponding voice to prompt the user to move; the illumination light source can be adjusted according to the requirement of the actual acquisition environment; the computer sends a corresponding dimming instruction to the single chip microcomputer, and the single chip microcomputer performs PWM (pulse width modulation) or IO (input/output) port level change after receiving the instruction to control the brightness and the quantity of the near-infrared LEDs so as to adjust the illumination brightness.
3. The invention has the beneficial effects.
By means of the training and feature matching method, the response speed can be kept within 8s, interference of environmental factors on palm vein recognition can be accurately eliminated, and accuracy and efficiency of palm vein recognition are improved.
Drawings
Fig. 1 is a flow chart of palm vein recognition according to the present invention.
Detailed Description
In order to make the technical spirit and advantages of the present invention more clearly understandable to examiners of the patent office and particularly to the public, the applicant shall describe in detail below by way of examples, but the description of the examples is not a limitation of the present invention, and any equivalent changes made according to the present inventive concept, which are merely formal and insubstantial, shall be considered to be within the scope of the present invention.
Examples
The palm vein identification intelligent system comprises an imaging circuit, a lighting circuit, an identification module and a wireless transmission module; the imaging circuit comprises a CCD camera, an optical lens and an optical filter; in the imaging circuit, the optical lens is a large-view-field optical lens, the optical filter adopts an infrared-transmitting optical filter with the cut-off wavelength of 720nm, the optical lens is arranged on the near-infrared camera, and the infrared-transmitting optical filter is embedded on the front panel of the shell and positioned in front of the optical lens. The lighting circuit consists of near-infrared LEDs; the recognition module comprises an electronic distance measuring unit and a voice unit, the wireless transmission module transmits video information and control signals to a computer and realizes communication with the computer, the recognition module measures palm distance information of a user through the electronic distance measuring unit, the control circuit sends a corresponding instruction to the voice unit, and a prompt of the moving direction of the user is given through the voice unit. The electronic distance measuring unit in the identification module is an ultrasonic or infrared distance measuring module and is used for measuring the palm distance information of the user in real time; the voice unit adopts a special voice processing chip and is provided with a high-sensitivity loudspeaker, and voice to be broadcasted is burnt into FLASH of the voice processing chip in advance. The single chip microcomputer in the identification module is used as a main control chip of the system, and the single chip microcomputer reads the distance information of the electronic distance measuring unit in real time and judges whether the palm of the user is in a clear imaging range or not; if the imaging range exceeds the clear imaging range, the singlechip sends a corresponding instruction to the voice unit to control the voice unit to broadcast corresponding voice to prompt the user to move; the illumination light source can be adjusted according to the requirement of the actual acquisition environment; the computer sends a corresponding dimming instruction to the single chip microcomputer, and the single chip microcomputer performs PWM (pulse width modulation) or IO (input/output) port level change after receiving the instruction to control the brightness and the quantity of the near-infrared LEDs so as to adjust the illumination brightness.
The identification module identifies the palm vein according to the following steps:
firstly, preprocessing an image of a palm vein and a palm vein image with query, respectively extracting features, training and projecting, and projecting a trained palm vein stroke and a data matrix. Training and projecting the palm vein image, obtaining five candidate palm vein images through matching of the classifier, wherein an optimal projection matrix obtained through training is as follows:
secondly, finding the best test image from five candidate palm vein images in the classifier:
a. loading all palm vein image training sets, and corresponding to the candidate palm veins;
b. extracting the deformation of each palm vein from the training set by using the fusion palm vein description;
c. extracting deformation of the palm vein test image, which is expressed as Dq;
d. matching the Dq with the five previous candidate palm vein images to find the number of matching key points
And thirdly, determining a verification criterion according to the number of the matching key points, setting the palm vein descriptor with the maximum number of the matching points as a most probable item, and obtaining a target palm vein image through feature matching. For the matching process, the palm veins are classified by using the Euclidean distance based on the nearest neighbor rule, negative samples, namely a non-training palm vein image and a non-palm vein image are used for defining a threshold value for palm vein verification, if the minimum score is lower than the defined threshold value, input data is considered to be a known positive candidate palm vein, and otherwise, input data is considered to be a negative palm vein image or an unknown palm vein image.
Claims (7)
1. A palm vein recognition intelligent system is characterized in that: the wireless identification device comprises an imaging circuit, a lighting circuit, an identification module and a wireless transmission module; the imaging circuit comprises a CCD camera, an optical lens and an optical filter; the lighting circuit consists of near-infrared LEDs; the identification module comprises an identification unit, an electronic distance measurement unit and a voice unit, the wireless transmission module transmits video information and control signals to a computer and realizes communication with the computer, and the identification module identifies the palm vein according to the following steps:
firstly, training and projecting palm vein images, and obtaining five candidate palm vein images through matching of a classifier;
secondly, finding the best test image from five candidate palm vein images in the classifier:
a. loading all palm vein image training sets, and corresponding to the candidate palm veins;
b. extracting the deformation of each palm vein from the training set by using the fusion palm vein description;
c. extracting deformation of the palm vein test image, which is expressed as Dq;
d. matching the Dq with the five previous candidate palm vein images to find the number of matching key points
Thirdly, determining a verification criterion according to the number of the matching key points, setting the palm vein descriptor with the maximum number of the matching points as a most probable item, and obtaining a target palm vein image through feature matching;
the optimal projection matrix obtained by training in the first step is as follows:
is an optimal projection matrix, wherein
And
is defined as follows:
2. the palm vein recognition intelligent system according to claim 1, wherein: in the third step, for the matching process, classifying the palm veins by using the Euclidean distance based on the nearest neighbor rule, wherein negative samples, namely a non-training palm vein image and a non-palm vein image are used for defining a threshold value for palm vein verification, if the minimum score is lower than the defined threshold value, input data is considered to be a known positive candidate palm vein, and otherwise, the input data is considered to be a negative palm vein image or an unknown palm vein image.
3. The palm vein recognition intelligent system according to any one of claims 1 and 2, wherein: in the first step, firstly, the palm vein image and the palm vein image with query are preprocessed, feature extraction, training and projection are respectively carried out, and the trained palm vein stroke projection and data matrix are carried out.
4. The palm vein recognition intelligent system according to claim 1, wherein: the optical lens in the imaging circuit is a large-view-field optical lens, the optical filter adopts an infrared-transmitting optical filter with the cut-off wavelength of 720nm, the optical lens is arranged on the near-infrared camera, and the infrared-transmitting optical filter is embedded in the front panel of the shell and positioned in front of the optical lens.
5. The palm vein recognition intelligent system according to claim 1, wherein: the recognition module measures the palm distance information of the user through the electronic distance measuring unit, the control circuit sends a corresponding instruction to the voice unit, and the voice unit gives a prompt of the moving direction of the user.
6. The palm vein recognition intelligent system according to claim 1, wherein: the electronic distance measuring unit in the identification module is an ultrasonic or infrared distance measuring module and is used for measuring the palm distance information of the user in real time; the voice unit adopts a special voice processing chip and is provided with a high-sensitivity loudspeaker, and voice to be broadcasted is burnt into FLASH of the voice processing chip in advance.
7. The palm vein recognition intelligent system according to claim 1 or 5, wherein: the single chip microcomputer in the identification module is used as a main control chip of the system, and the single chip microcomputer reads the distance information of the electronic distance measuring unit in real time and judges whether the palm of the user is in a clear imaging range or not; if the imaging range exceeds the clear imaging range, the singlechip sends a corresponding instruction to the voice unit to control the voice unit to broadcast corresponding voice to prompt the user to move; the illumination light source can be adjusted according to the requirement of the actual acquisition environment; the computer sends a corresponding dimming instruction to the single chip microcomputer, and the single chip microcomputer performs PWM (pulse width modulation) or IO (input/output) port level change after receiving the instruction to control the brightness and the quantity of the near-infrared LEDs so as to adjust the illumination brightness.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201410227590.1A CN105224906B (en) | 2014-05-27 | 2014-05-27 | Palm vein recognition intelligent system |
| PCT/CN2014/094463 WO2015180460A1 (en) | 2014-05-27 | 2014-12-22 | Palm vein smart recognition system |
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| CN201410227590.1A CN105224906B (en) | 2014-05-27 | 2014-05-27 | Palm vein recognition intelligent system |
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Families Citing this family (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104156705A (en) * | 2014-08-08 | 2014-11-19 | 常熟安智生物识别技术有限公司 | Intelligent finger vein recognition system |
| CN106991380A (en) * | 2017-03-10 | 2017-07-28 | 电子科技大学 | A kind of preprocess method based on vena metacarpea image |
| CN108564080B (en) * | 2018-04-18 | 2024-02-02 | 青岛海泰新光科技股份有限公司 | Biological recognition feature detection device and method |
| CN109033981A (en) * | 2018-06-29 | 2018-12-18 | 张维先 | The method for reducing palm vein identification system power consumption based on ultrasonic distance measurement |
| CN111160246A (en) * | 2019-12-28 | 2020-05-15 | 广东智冠信息技术股份有限公司 | Mobile terminal and palm vein identification method and system thereof |
| CN111797807A (en) * | 2020-07-17 | 2020-10-20 | 熵基科技股份有限公司 | Fusion identification method and device considering body temperature measurement and identity authentication |
| CN114612941B (en) * | 2022-05-11 | 2022-08-30 | 四川圣点世纪科技有限公司 | Palm vein feature-based multi-mode identity authentication method, device and system |
| CN116620219B (en) * | 2023-07-21 | 2023-10-20 | 宁波芯然科技有限公司 | Low-power-consumption vehicle-mounted palm vein unlocking method |
| CN117809341A (en) * | 2024-02-29 | 2024-04-02 | 广州市仪美医用家具科技股份有限公司 | Palm vein-based identity recognition method, system, equipment and storage medium |
| CN118097724B (en) * | 2024-04-23 | 2024-07-26 | 江西百胜智能科技股份有限公司 | Palm vein-based identity recognition method and device, readable storage medium and equipment |
| CN118212666B (en) * | 2024-05-21 | 2024-08-06 | 杭州名光微电子科技有限公司 | Multi-angle-based living body palm vein recognition system and method thereof |
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| CN202041967U (en) * | 2011-04-08 | 2011-11-16 | 中国矿业大学 | Palm vein and human face bimodal biological identification instrument |
| CN102402679A (en) * | 2010-09-07 | 2012-04-04 | 北京北科慧识科技股份有限公司 | Non-contact type palm print and palm vein recognition system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101002682A (en) * | 2007-01-19 | 2007-07-25 | 哈尔滨工程大学 | Method for retrieval and matching of hand back vein characteristic used for identification of status |
| CN101251889B (en) * | 2007-12-25 | 2010-10-13 | 哈尔滨工业大学 | Personal identification method and near-infrared image forming apparatus based on palm vena and palm print |
| CN101196987B (en) * | 2007-12-25 | 2011-05-25 | 哈尔滨工业大学 | On-line palm print, palm vein image personal identification method and its special capturing instrument |
| US8229178B2 (en) * | 2008-08-19 | 2012-07-24 | The Hong Kong Polytechnic University | Method and apparatus for personal identification using palmprint and palm vein |
| CN101840511B (en) * | 2010-06-04 | 2013-08-28 | 哈尔滨工程大学 | Method for extracting, matching and recognizing characteristics of finger veins |
| CN103136522A (en) * | 2011-11-28 | 2013-06-05 | 常熟安智生物识别技术有限公司 | Finger vein identification technical scheme |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102402679A (en) * | 2010-09-07 | 2012-04-04 | 北京北科慧识科技股份有限公司 | Non-contact type palm print and palm vein recognition system |
| CN202041967U (en) * | 2011-04-08 | 2011-11-16 | 中国矿业大学 | Palm vein and human face bimodal biological identification instrument |
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