CN203733125U - Comprehensive biological feature recognition system - Google Patents

Comprehensive biological feature recognition system Download PDF

Info

Publication number
CN203733125U
CN203733125U CN201320639098.6U CN201320639098U CN203733125U CN 203733125 U CN203733125 U CN 203733125U CN 201320639098 U CN201320639098 U CN 201320639098U CN 203733125 U CN203733125 U CN 203733125U
Authority
CN
China
Prior art keywords
data processing
processing equipment
similarity
controller
utility
Prior art date
Legal status (The legal status 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 status listed.)
Expired - Fee Related
Application number
CN201320639098.6U
Other languages
Chinese (zh)
Inventor
池静
卢志强
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Wuxi Youchuang Biological Science & Technology Co Ltd
Original Assignee
Wuxi Youchuang Biological Science & Technology Co Ltd
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 Wuxi Youchuang Biological Science & Technology Co Ltd filed Critical Wuxi Youchuang Biological Science & Technology Co Ltd
Priority to CN201320639098.6U priority Critical patent/CN203733125U/en
Application granted granted Critical
Publication of CN203733125U publication Critical patent/CN203733125U/en
Anticipated expiration legal-status Critical
Expired - Fee Related legal-status Critical Current

Links

Abstract

The utility model discloses a comprehensive biological feature recognition system which comprises a probe array, data processing equipment and a controller. The probe array is electrically connected with the data processing equipment which is electrically connected with the data processing equipment. Multiple features like fingerprints, hand back pore distribution, hand back line distribution and finger blood vessel distribution are taken as feature values for identity recognition, so that accuracy of identity recognition is greatly improved, and false positive and false negative probability is lowered. In addition, the probe array which is modularized is adopted, so that convenience is brought to a user to freely select needed sensor combinations.

Description

A kind of biological characteristic synthesis recognition system
Technical field
The utility model relates to identification field, relates in particular to a kind of biological characteristic synthesis recognition system.
Background technology
Living things feature recognition refers to and utilizes the intrinsic physiological characteristic of human body or behavioural characteristic to carry out personal identification evaluation.Common identification at present comprises fingerprint, face, pupil etc., or the accuracy of the incompatible raising identification of several technology groups, reduces false negative and false-positive probability.In general, eigenvalue is more, and the accuracy of identification is higher.The distribution of human body the back of the hand pore, the back of the hand lines and finger vascular distribution are from teenager, unless there is wound to occur, substantially can not change, and hardly may be identical between Different Individual, therefore can be used as good identification index, to improve the accuracy of identification.
Utility model content
The purpose of this utility model is, by a kind of biological characteristic synthesis recognition system, to solve the problem that above background technology is partly mentioned.
For reaching this object, the utility model by the following technical solutions:
A biological characteristic synthesis recognition system, it comprises linear transducer array, data processing equipment and controller;
Described linear transducer array comprises finger print acquisition module, vision sensor, optical scanner and blood oxygen probe; Wherein, described finger print acquisition module, vision sensor, optical scanner, blood oxygen probe are all connected with data processing equipment;
Described data processing equipment and controller are electrically connected; Described data processing equipment comprises processor and storer; Described processor and storer, finger print acquisition module, vision sensor, optical scanner, blood oxygen probe, controller are electrically connected.
The technical solution of the utility model using that fingerprint, the back of the hand pore distribute, the back of the hand lines distributes and the multinomial feature of finger vascular distribution as the eigenwert of identification, greatly improve the accuracy of identification, false negative and false-positive probability have been reduced, simultaneously, the utility model adopts modular linear transducer array, facilitates user to choose arbitrarily required sensor combinations.
Accompanying drawing explanation
The biological characteristic synthesis recognition system block diagram that Fig. 1 provides for the utility model embodiment.
Embodiment
Below in conjunction with drawings and Examples, the utility model is described in further detail.Be understandable that, specific embodiment described herein is only for explaining the utility model, but not to restriction of the present utility model.It also should be noted that, for convenience of description, in accompanying drawing, only show the part relevant to the utility model but not full content.
Please refer to shown in Fig. 1 the biological characteristic synthesis recognition system block diagram that Fig. 1 provides for the utility model embodiment.
In the present embodiment, biological characteristic synthesis recognition system comprises linear transducer array 101, data processing equipment 102 and controller 103.
Described linear transducer array 101 is electrically connected with data processing equipment 102, for gathering successively finger print image, the back of the hand pore distributed image, the back of the hand lines image, finger blood oxygen saturation data, exports to data processing equipment 102.
In the present embodiment, described linear transducer array 101 comprises finger print acquisition module 1011, vision sensor 1012, optical scanner 1013 and the blood oxygen probe 1014 of arranging successively.Described finger print acquisition module 1011, vision sensor 1012, optical scanner 1013, blood oxygen probe 1014 are all connected with data processing equipment 102, for gathering successively fingerprint image, the back of the hand pore distributed image, the back of the hand lines image, finger blood oxygen saturation data, export to data processing equipment 102.
Described data processing equipment 102 is electrically connected with controller 103, for described fingerprint image and the authorized person's fingerprint image prestoring are compared, obtain fingerprint similarity, described the back of the hand pore distributed image and the back of the hand pore distributed image prestoring are compared, obtain pore distribution similarity, described the back of the hand lines image and the back of the hand lines image prestoring are compared, obtain lines similarity, to described finger blood oxygen saturation data analysis, obtain finger vascular distribution information, itself and the finger vascular distribution information that prestores are compared, obtain vascular distribution similarity, and according to described fingerprint similarity, pore distribution similarity, lines similarity and vascular distribution similarity are calculated comprehensive similarity, whether according to comprehensive similarity, differentiate personnel to be identified is authorized person, if, feedback " opening " signal is to controller 103, otherwise, feedback " not opening " signal is to controller 103.
In the present embodiment, described data processing equipment 102 comprises processor 1021 and storer 1022.Described processor 1021 and storer 1022, finger print acquisition module 1011, vision sensor 1012, optical scanner 1013, blood oxygen probe 1014, controller 103 is electrically connected, for authorized person's fingerprint image that fingerprint image and storer 1022 are prestored, compare, obtain fingerprint similarity, the back of the hand pore distributed image prestoring in described the back of the hand pore distributed image and storer 1022 is compared, obtain pore distribution similarity, the back of the hand lines image prestoring in described the back of the hand lines image and storer 1022 is compared, obtain lines similarity, to described finger blood oxygen saturation data analysis, obtain finger vascular distribution information, by prestoring in itself and storer 1022, finger vascular distribution information is compared, obtain vascular distribution similarity, and according to described fingerprint similarity, pore distribution similarity, lines similarity and vascular distribution similarity are calculated comprehensive similarity, whether according to comprehensive similarity, differentiate personnel to be identified is authorized person, if, feedback " opening " signal is to controller 103, otherwise, feedback " not opening " signal is to controller 103.When in fingerprint similarity, pore distribution similarity, lines similarity and vascular distribution similarity, arbitrary data are not less than 95%, judge that personnel not to be identified are authorized persons, when 100% of fingerprint similarity, pore distribution similarity, lines similarity and vascular distribution similarity remedied several products and be not more than 5%, judge that personnel not to be identified are authorized persons.Take fingerprint similarity as example, and 100% remedies number refers to: if fingerprint similarity is 70%, 100% of fingerprint similarity to remedy number be exactly 30%.
The pore identified on processor 1021 opponent's dorsal body setae pore size distribution images carries out mark, then successively mark pore is carried out to range flags, pore in mark pore and range flags is carried out to line, each angle that above-mentioned line is formed is mated with the pore distributed image through same treatment in storer 1022, obtains pore distribution similarity; After the pre-service of the back of the hand lines image, according to special curvatures point, extract the characteristic portion of lines image, and it is mated with the back of the hand lines image in storer 1022, obtain lines similarity; Blood oxygen saturation data analysis to finger, obtain the vascular distribution information of finger, the vascular distribution information of described finger is comprised to extreme value filtering, once level and smooth pre-service, extract the characteristic portion of vascular distribution, and it is mated with the vascular distribution information in storer 1022, obtain vascular distribution similarity.It should be noted that, the kind of controller 103 has a variety of, according to different application and difference can be for example automatic locking system.
The biological characteristic synthesis recognition system that the utility model provides using that fingerprint, the back of the hand pore distribute, the back of the hand lines distributes and the multinomial feature of finger vascular distribution as the eigenwert of identification, greatly improve the accuracy of identification, false negative and false-positive probability have been reduced, simultaneously, the utility model adopts modular linear transducer array, facilitates user to choose arbitrarily required sensor combinations.
Note, above are only preferred embodiment of the present utility model and institute's application technology principle.Skilled person in the art will appreciate that the utility model is not limited to specific embodiment described here, can carry out for a person skilled in the art various obvious variations, readjust and substitute and can not depart from protection domain of the present utility model.Therefore, although the utility model is described in further detail by above embodiment, but the utility model is not limited only to above embodiment, in the situation that not departing from the utility model design, can also comprise more other equivalent embodiment, and scope of the present utility model is determined by appended claim scope.

Claims (1)

1. a biological characteristic synthesis recognition system, is characterized in that, comprises linear transducer array, data processing equipment and controller;
Described linear transducer array comprises finger print acquisition module, vision sensor, optical scanner and blood oxygen probe; Wherein, described finger print acquisition module, vision sensor, optical scanner, blood oxygen probe are all connected with data processing equipment;
Described data processing equipment and controller are electrically connected; Described data processing equipment comprises processor and storer; Described processor and storer, finger print acquisition module, vision sensor, optical scanner, blood oxygen probe, controller are electrically connected.
CN201320639098.6U 2013-10-16 2013-10-16 Comprehensive biological feature recognition system Expired - Fee Related CN203733125U (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201320639098.6U CN203733125U (en) 2013-10-16 2013-10-16 Comprehensive biological feature recognition system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201320639098.6U CN203733125U (en) 2013-10-16 2013-10-16 Comprehensive biological feature recognition system

Publications (1)

Publication Number Publication Date
CN203733125U true CN203733125U (en) 2014-07-23

Family

ID=51203182

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201320639098.6U Expired - Fee Related CN203733125U (en) 2013-10-16 2013-10-16 Comprehensive biological feature recognition system

Country Status (1)

Country Link
CN (1) CN203733125U (en)

Similar Documents

Publication Publication Date Title
CN106473750B (en) Personal identification method based on photoplethysmographic optimal period waveform
CN101773394B (en) Identification method and identification system using identification method
CN107491740B (en) Newborn pain recognition method based on facial expression analysis
Werner et al. Automatic pain recognition from video and biomedical signals
Bashar et al. Human identification from brain EEG signals using advanced machine learning method EEG-based biometrics
CN107122709B (en) Living body detection method and device
CN104434140A (en) Content evaluation system and content evaluation method using the system
CN108742660A (en) A kind of Emotion identification method based on wearable device
CN110200640B (en) Non-contact emotion recognition method based on dual-mode sensor
EP3449409B1 (en) Biometric method and device for identifying a person through an electrocardiogram (ecg) waveform
You et al. Finger motion decoding using EMG signals corresponding various arm postures
CN106874722A (en) A kind of personal identification method and its device based on electrocardiosignal
CN108091391A (en) Illness appraisal procedure, terminal device and computer-readable medium
CN103544421A (en) Comprehensive biological feature recognition system and method
Kaveh et al. Temporal and spectral features of single lead ECG for human identification
CN107411738A (en) A kind of mood based on resting electroencephalogramidentification similitude is across individual discrimination method
Li et al. Sleep posture classification with multi-stream CNN using vertical distance map
CN104679967A (en) Method for judging reliability of psychological test
Kaur et al. Heart rate variability (HRV): an indicator of stress
Jiang et al. Recent research for unobtrusive atrial fibrillation detection methods based on cardiac dynamics signals: A survey
CN111839482A (en) Non-contact drug addict monitoring method and system based on IPPG
Kwon et al. Sinabro: A smartphone-integrated opportunistic electrocardiogram monitoring system
CN201522734U (en) Iris recognition entrance guard
Lee et al. Mobile embedded health-care system working on wireless sensor network
CN203733125U (en) Comprehensive biological feature recognition system

Legal Events

Date Code Title Description
C14 Grant of patent or utility model
GR01 Patent grant
CF01 Termination of patent right due to non-payment of annual fee

Granted publication date: 20140723

Termination date: 20141016

EXPY Termination of patent right or utility model