CN102915434B - A kind of face identification system based on low-power-consumption embedded platform - Google Patents
A kind of face identification system based on low-power-consumption embedded platform Download PDFInfo
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- CN102915434B CN102915434B CN201210364725.XA CN201210364725A CN102915434B CN 102915434 B CN102915434 B CN 102915434B CN 201210364725 A CN201210364725 A CN 201210364725A CN 102915434 B CN102915434 B CN 102915434B
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Abstract
The present invention relates to a kind of face identification system based on low-power-consumption embedded platform, comprise ARM core processing module, video acquisition module, display module and peripheral data coffret, described ARM core processing module connects respectively video acquisition module, display module and peripheral data coffret; Video acquisition module gathers vision signal and is transferred to ARM core processing module, ARM core processing module is converted into vision signal after picture signal, this picture signal is carried out, after face detection, human eye location, face image standardization, feature extraction and identification comparison processing, detection recognition result being presented on display module or by peripheral data coffret and being exported. Compared with prior art, the present invention has the advantages such as low in energy consumption, fast operation, accuracy of identification be high, applied widely.
Description
Technical field
The present invention relates to a kind of image recognition technology, especially relate to a kind of people based on low-power-consumption embedded platformFace recognition system.
Background technology
Along with the development of Information technology, face recognition technology progressively moves to maturity with practical, at video monitoring, doorThe security fields such as access control system, attendance checking system and clearance system have obtained important application. At present, the reality of recognition of faceExisting hardware platform has PC and embedded hardware system. PC volume is large, cost is high, power consumption is high and inconvenientIn the shortcoming such as carrying, the application scenario of recognition of face is greatly limited. Along with the development of technology, embedThe arithmetic speed of formula platform is more and more faster, and volume is more and more less, and power consumption and cost are more and more lower, makes in exploitation justThe face identification system of taking formula has had sufficient hardware supported. Therefore, exploitation has the embedding of more wide applicationFormula face identification system becomes possibility.
At present the Embedded Hardware Platform of main flow has ARM(AdvancedRISCMachines), DSP(DigitalSignalProcessor), Leonardo da Vinci's double-core platform etc. Dsp processor has powerful data processing and computing energyPower, but limited to the control ability of peripheral hardware, user interactions interface is supported to imperfection and price. Leonardo da Vinci is twoControl and the data processing function of core platform to peripheral hardware is more intense, but workmanship is complicated, development difficulty is large and price highExpensive. Arm processor has powerful function at aspects such as man-machine interaction, equipment controls, simultaneously along with ARMThe fast development of processor, its ability to data processing is more and more stronger, and price is also more and more cheap. With DSPAnd Leonardo da Vinci's platform compares, it is excellent that ARM series platform has that cost is low, the little while arithmetic speed of power consumption is very fast etc.Point, can meet the needs of face recognition algorithms, and ARM series processors, in intelligent terminal extensive use, makes simultaneouslyObtain face identification system and can more easily enter ordinary populace consumption. Therefore develop the people of low-power consumption at ARM series platformFace recognition system has very important using value. Current embedded human face recognition system has based on visible ray with nearTwo kinds of infrared techniques, the recognition of face of visible ray is subject to ambient light very large according to variable effect, and near-infrared recognition of face systemSystem can effectively be eliminated ambient light according to conversion impact, but the relatively power consumption of the light compensating lamp of near-infrared camera.
Summary of the invention
Object of the present invention is exactly to provide a kind of low in energy consumption, fortune in order to overcome the defect that above-mentioned prior art existsThe face identification system based on low-power-consumption embedded platform that calculation speed is fast, accuracy of identification is high.
Object of the present invention can be achieved through the following technical solutions:
Based on a face identification system for low-power-consumption embedded platform, comprise ARM core processing module, videoAcquisition module, display module and peripheral data coffret, described ARM core processing module connects respectivelyVideo acquisition module, display module and peripheral data coffret;
Video acquisition module gathers vision signal and is transferred to ARM core processing module, ARM core processing mouldPiece is converted into vision signal after picture signal, and this picture signal is carried out to face detection, human eye location, face figurePicture standardization, feature extraction and identification comparison are presented at detection recognition result on display module or pass through after processingThe output of peripheral data coffret.
Described ARM core processing module comprises that arm processor, DDR memory chip, NandFlash depositReservoir, power management submodule, crystal oscillating circuit and peripheral interface management submodule, described arm processor dividesNot connecting DDR memory chip, NandFlash memory, power management submodule, crystal oscillating circuit and periphery connectsMouth management submodule, described DDR memory chip connects respectively video acquisition module and display module, describedPeripheral interface management submodule is connected with peripheral data coffret.
Described NandFlash memory is the memory that stores the priori that precondition obtains.
Described face image standardization refers to the position of human eye of orienting according to human eye, facial image from view picture figureIn picture, intercept out, then by rotation, shearing, convergent-divergent and illumination pretreatment, finally obtain standard faces image;
Described identification comparison is processed the face characteristic and the NandFlash that refer to extracting after standard faces image and is depositedThe priori that in reservoir, precondition obtains is identified comparison and is processed.
Described video acquisition module comprises visible image capturing head and near-infrared camera, described near-infrared cameraIn be provided with LED near-infrared light compensating lamp.
Described video acquisition module also comprises following image acquisition step:
1) visible image capturing head gathers visible images and is transferred to ARM core processing module, ARM core placeReason module this image is carried out to face detection, and judge whether to detect if so, perform step 2 by face),If not, perform step 3);
2) open LED near-infrared light compensating lamp, near-infrared camera collection near-infrared facial image is also transferred to ARMCore processing module is carried out recognition of face, returns to step 1);
3) judgement does not detect that whether the number of times of face is greater than setting value, if so, performs step 4 continuously), ifNo, return to step 1);
4) close LED near-infrared light compensating lamp, stop the identification of near-infrared man face image acquiring, return to step 1).
Described peripheral data coffret comprises that GPRS interface, WIFI interface, USB interface and Ethernet connectMouthful.
In described display module, be provided with voice message submodule.
Compared with prior art, the present invention has the following advantages:
1) the present invention adopts the ARM core processor of low-power consumption to identify face, has fast operation,The advantage that accuracy of identification is high;
2) the present invention adjusts the opening time of visible image capturing head and near-infrared camera adaptively, has low meritConsume energy-conservation advantage;
3) the present invention is the face identification system based on near-infrared image, can effectively overcome visible images faceThe shortcoming that identification is acutely affected according to conversion by ambient light, illumination conversion has good adaptability to external world;
4) the present invention is provided with multiple peripheral data coffret, can adapt to the demand of various transmission environments;
5) the present invention's combination interface application simultaneously and background data base support, modules independence or co-ordination,Complete recognition of face task, there is good user friendly prompt facility simultaneously.
Brief description of the drawings
Fig. 1 is the structural representation of system of the present invention;
Fig. 2 is face identifying schematic diagram of the present invention;
Fig. 3 is systemic-function schematic diagram of the present invention.
Detailed description of the invention
Below in conjunction with the drawings and specific embodiments, the present invention is described in detail.
Embodiment
As shown in Figure 1, the face identification system of the present embodiment based on low-power-consumption embedded platform, comprises ARM coreHeart processing module 1, video acquisition module 2, display module 3 and peripheral data coffret 4, described ARMCore processing module 1 connects respectively video acquisition module 2, display module 3 and peripheral data coffret 4; Depending onFrequency acquisition module 2 Real-time Collection vision signals are also transferred to ARM core processing module 1, ARM core processingModule 1 is converted into vision signal after picture signal, and this picture signal is carried out to face detection, human eye location, peopleFace image standardization, feature extraction and identification comparison are presented at display module 3 by detection recognition result after processingGo up or export by peripheral data coffret 4.
Wherein, ARM core processing module 1 comprises arm processor 11, DDR memory chip 12, NandFlashMemory 13, power management submodule 14, crystal oscillating circuit 15 and peripheral interface management submodule 16, describedArm processor 11 connects respectively DDR memory chip 12, NandFlash memory 13, power management submodulePiece 14, crystal oscillating circuit 15 and peripheral interface management submodule 16, described DDR memory chip 12 connects respectivelyConnect video acquisition module 2 and display module 3, described peripheral interface management submodule 16 and peripheral data transmissionInterface 4 connects. In NandFlash memory 13, store the priori that precondition obtains, for identificationComparison is processed. The present embodiment adopts the NandFlash memory of 1Gbyte and the DDR internal memory core of 256MbyteSheet.
Face recognition algorithms data operation quantity is large, and the computing that comprises a large amount of floating datas needs data fortune fastThe processor of calculation and high-precision floating-point operation ability. Arm processor mainly comprises ARM9, ARM11, ARMCortex-A8, ARMCortex-A9 and with there is similar performance and more high performance processor. But in applicationOccasion is analyzed, and ARM9 and ARM11 are applicable to real-time and the not high environment of capacity requirement; ARMThe more applicable capacity of high-performance processor is large for Cortex-A8, Cortex-A9 etc., the environment that real-time performance is high. WhereinARM11 processor technology maturation, be widely used, data processing and operational capability strong, possess fast processing faceThe performance of recognizer, simultaneously low price, is conducive to the universalness of embedded human face recognition system; Basis simultaneouslyARM series platform under certain compatibility, make the face identification system of ARM11 platform more easily to ARMThe higher platform upgrading of Cortex-A8 series. The slow while of ARM9 arithmetic speed does not have hard floating-point operation function.ARMCortex-A8 series and higher platform are arithmetic speed is faster and floating-point disposal ability is stronger, but its valencyLattice are relatively costly. Therefore realizing aspect the platform of face identification system, according to specific environment demand, it is suitable to selectARM platform develop. The present embodiment illustrates as an example with ARM11 processor.
Video acquisition module 2 comprises visible image capturing head and near-infrared camera, in described near-infrared camera, establishesThere is LED near-infrared light compensating lamp, open very power consumption for a long time. Video acquisition module can be simulated by AVUtilizing camera interface, digital camera interface or USB utilizing camera interface are connected with ARM core processing module, thisA little interfaces are applicable to the application of embedded system under multiple camera occasion. Energy-conservation in order to make system realize low-power consumptionPerformance, the present embodiment adopts following image acquisition step:
1) visible image capturing head gathers visible images and is transferred to ARM core processing module, ARM core placeReason module this image is carried out to face detection, and judge whether to detect if so, perform step 2 by face),If not, perform step 3);
2) open LED near-infrared light compensating lamp, near-infrared camera collection near-infrared facial image is also transferred to ARMCore processing module is carried out recognition of face, returns to step 1);
3) judgement does not detect that whether the number of times of face is greater than setting value, if so, performs step 4 continuously), ifNo, return to step 1);
4) close LED near-infrared light compensating lamp, stop the identification of near-infrared man face image acquiring, return to step 1).
Described peripheral data coffret 4 comprises GPRS interface, WIFI interface, USB interface and EthernetInterface, can adapt to various transmission demands. USB interface is the interface as in-plant rapid data transmission,The transfer rate of at present up-to-date USB2.0 standard has 480Mbps, but its distance limit is in 5m. ForThe transmission data of long distance, can adopt Ethernet interface, and its transfer rate can reach 10Mb/s, and having transmission canLean on, be easy to the features such as realization. WIFI radio network interface and GPRS network interface are to be mainly applied in wireless biographyDefeated field, has portable feature, but the stability of transmission is lower than Ethernet with transfer rate. Therefore thisSeveral data transmission interfaces will be applied according to practical matter. In described display module 3, be provided with voice messageModule.
As shown in Figure 2, the face recognition process of the present embodiment is specially: native system, after startup, first initializesModules, arm processor 11 reads the priori that precondition obtains from NANDFlash memory 13Knowledge; Complete after initialization, enter face and detect the major cycle of identifying. In major cycle, arm processor 11Obtain from video acquisition module 2 view data that camera current time collects, view data is carried out to illumination pre-Process laggard pedestrian's face and detect, if there is face in image, this image is carried out to human eye location, and fixed to human eyeIt is qualified that position result judges whether, qualifiedly proceeds standardization and the feature extraction of facial image and compare knowledgeNot, otherwise again next frame image is detected; Finally export recognition result. Described face image standardizationRefer to the position of human eye of orienting according to human eye, facial image is intercepted out from entire image, then by revolvingTurn, shearing, convergent-divergent and illumination pretreatment, finally obtain standard faces image; Described identification comparison is processed and is referred toThe priori that in face characteristic after extraction standard faces image and NandFlash memory, precondition obtains is knownIdentifying comparison processes.
The face of the present embodiment detects identification based near infrared light image, and near-infrared image refers to near-infrared light wavesThe image of section, for other imaging mode gained images such as visible images, radioscopic image. BaseCan effectively overcome visible images recognition of face in the face identification system of near-infrared image is subject to ambient light according to conversionThe shortcoming of violent impact, illumination conversion has good adaptability to external world.
The present embodiment system adopts hard floating point instruction and ARMv6(ARMv7 or higher while realization) instruction to calculateMethod program compiles, and improves floating-point operation precision and the arithmetic speed of algorithm, efficiently solves embedded platformDifficulty aspect floating-point operation precision and the speed of service of operation face recognition algorithms; Simultaneously for further raisingSpeed, has carried out the optimization of code rank to core algorithm program. Mainly adopt following methods: 1) optimize localThe use of variable to register, reduces the time overhead that register data is stacked and pop; 2) configuration compiler is excellentChange compiling rank, opening speed optimization; 3) to the small function frequently calling, adopt inline mode to call,Reduce call overhead, avoid using the data type of non-32 simultaneously as far as possible; 4) ARM does not have special divisionInstruction, computing division is very consuming time, the division method of transferring to is transported by the method such as table look-up for part program consuming timeCalculate, greatly reduce division arithmetic expense. 4) carry out cycle criterion optimization, reduce decision instruction number; 5) to meterThe formula algorithm of calculating complicated and time consumption launches to simplify, for example, power function is calculated and carried out series expansion calculating.
As shown in Figure 3, the present embodiment face identification system function of initializing, exit function and five application functions.Five application functions are wherein for adding user, identification user, compiles user, deletion user and voice message.Add user function for gathering user's face characteristic and personal information, its flow process is: new user is gathered to its face figureSheet carries out face detection, human eye location, face image standardization and feature extraction, finally by this user's featureBe saved in database with its personal information; Identification user function is to identifying the people in camera front, itsFlow process as shown in Figure 2, is finally exported its recognition result on display screen; Compiles user function is to userThe personal information preservation of modifying; Deleting user function is personal information and the face characteristic of deleting unwanted userData, the information of having deleted rear real-time update internal memory and database; Sound prompt function is to carry out friendly voice messageFunction, carries out certain prompting to user's use procedure, and be conducive to user's use and improve system user friendliness,Can carry out certain man-machine interaction, improve systematic function simultaneously.
Claims (6)
1. the face identification system based on low-power-consumption embedded platform, is characterized in that, comprises ARM coreHeart processing module, video acquisition module, display module and peripheral data coffret, described ARM coreProcessing module connects respectively video acquisition module, display module and peripheral data coffret;
Video acquisition module gathers vision signal and is transferred to ARM core processing module, ARM core processing mouldPiece is converted into vision signal after picture signal, and this picture signal is carried out to face detection, human eye location, face figurePicture standardization, feature extraction and identification comparison are presented at detection recognition result on display module or pass through after processingThe output of peripheral data coffret;
Described video acquisition module comprises visible image capturing head and near-infrared camera, described near-infrared cameraIn be provided with LED near-infrared light compensating lamp;
Described video acquisition module also comprises following image acquisition step:
1) visible image capturing head gathers visible images and is transferred to ARM core processing module, ARM core placeReason module this image is carried out to face detection, and judge whether to detect if so, perform step 2 by face),If not, perform step 3);
2) open LED near-infrared light compensating lamp, near-infrared camera collection near-infrared facial image is also transferred to ARMCore processing module is carried out recognition of face, returns to step 1);
3) judgement does not detect that whether the number of times of face is greater than setting value, if so, performs step 4 continuously), ifNo, return to step 1);
4) close LED near-infrared light compensating lamp, stop the identification of near-infrared man face image acquiring, return to step 1).
2. a kind of face identification system based on low-power-consumption embedded platform according to claim 1, its spyLevy and be, described ARM core processing module comprises arm processor, DDR memory chip, NandFlashMemory, power management submodule, crystal oscillating circuit and peripheral interface management submodule, described arm processorConnect respectively DDR memory chip, NandFlash memory, power management submodule, crystal oscillating circuit and peripheryInterface management submodule, described DDR memory chip connects respectively video acquisition module and display module, described inPeripheral interface management submodule be connected with peripheral data coffret, the storage of described NandFlash memoryCapacity is 1G, and the memory capacity of described DDR memory chip is 256M.
3. a kind of face identification system based on low-power-consumption embedded platform according to claim 2, its spyLevy and be, described NandFlash memory is the memory that stores the priori that precondition obtains.
4. a kind of face identification system based on low-power-consumption embedded platform according to claim 3, its spyLevy and be, described face image standardization refers to the position of human eye of orienting according to human eye, facial image from wholeIn width image, intercept out, then by rotation, shearing, convergent-divergent and illumination pretreatment, finally obtain standard facesImage;
Described identification comparison processing refers to deposits face characteristic and the NandFlash of the standard faces image of extractionThe priori that in reservoir, precondition obtains is identified comparison and is processed.
5. a kind of face identification system based on low-power-consumption embedded platform according to claim 1, its spyLevy and be, described peripheral data coffret comprises GPRS interface, WIFI interface, USB interface and etherNetwork interface.
6. a kind of face identification system based on low-power-consumption embedded platform according to claim 1, its spyLevy and be, in described display module, be provided with voice message submodule.
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| CN103207991A (en) * | 2013-03-26 | 2013-07-17 | 苏州福丰科技有限公司 | Face recognition chip |
| CN103280005A (en) * | 2013-04-16 | 2013-09-04 | 无锡市崇安区科技创业服务中心 | Entrance guard system |
| CN103607794A (en) * | 2013-10-18 | 2014-02-26 | 烽火通信科技股份有限公司 | Home gateway apparatus integrated with HomeNodeB function |
| CN103985165A (en) * | 2014-05-12 | 2014-08-13 | 深圳市威富多媒体有限公司 | Attendance method and device based on mobile terminal, voice and face identification |
| CN104573679B (en) * | 2015-02-08 | 2018-06-22 | 天津艾思科尔科技有限公司 | Face identification system based on deep learning under monitoring scene |
| JP2016161830A (en) * | 2015-03-03 | 2016-09-05 | カシオ計算機株式会社 | Content output device, content output method, and program |
| CN108074303A (en) * | 2016-11-16 | 2018-05-25 | 常熟安智生物识别技术有限公司 | A kind of scheme that can expand recognition of face number of users |
| CN107292300A (en) * | 2017-08-17 | 2017-10-24 | 湖南创合未来科技股份有限公司 | A kind of face recognition device and method |
| CN108460330A (en) * | 2018-01-17 | 2018-08-28 | 上海鹰觉科技有限公司 | It is a kind of it is non-controllable under the conditions of fast and accurately face identification device |
| CN108520217A (en) * | 2018-03-28 | 2018-09-11 | 朱旭辉 | A kind of face identification and Activity recognition system |
| CN110418102A (en) * | 2018-04-27 | 2019-11-05 | 江苏联禹智能工程有限公司 | A kind of video monitoring system of infrared/temperature-sensitive recognition of face |
| CN110047071A (en) * | 2019-04-26 | 2019-07-23 | 杭州智趣智能信息技术有限公司 | A kind of image quality measure method, apparatus and medium |
| CN110309759A (en) * | 2019-06-26 | 2019-10-08 | 深圳市微纳集成电路与***应用研究院 | Light source control method based on human body image identification |
| CN111707375B (en) * | 2020-06-10 | 2021-07-09 | 青岛联合创智科技有限公司 | Electronic class card with intelligent temperature measurement attendance and abnormal behavior detection functions |
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Effective date of registration: 20180720 Address after: 201201 1 floor of No. 977, Shanghai Feng Road, Pudong New Area, Shanghai. Patentee after: Shanghai Ling Technology Co., Ltd. Address before: 200240 No. 800, Dongchuan Road, Shanghai, Minhang District Patentee before: Shanghai Jiao Tong University |