CN108564018A - A kind of biological characteristic 3D 4 D datas recognition methods and system based on infrared photography - Google Patents

Abstract

The biological characteristic 3D 4 D datas recognition methods and system that the present invention provides a kind of based on infrared photography, 2D coloured images collected to target organism to one or more zoom color camera and depth infrared camera pre-process the collected infrared image of target organism, obtain spatial point cloud information of the target organism within given time, 3D data of the target organism within given time are obtained after registration fusion, complete model reconstruction.Database is formed using the identity information of organism as distinguishing mark；The biological characteristic 3D 4 D datas stored in database are found using the identity information of target organism, and point cloud is compared to identify the identity of target organism accordingly.It is that the 2D high clear colorfuls picture of color camera and the collected depth 3D information of depth infrared camera are subjected to registration fusion in the present invention, to reduce the extraction of characteristic point, reduces the complexity of algorithm, improve the precision and efficiency of reconstruction.

Description

A kind of biological characteristic 3D 4 D datas recognition methods and system based on infrared photography

Technical field

The present invention relates to biometrics identification technology field, especially a kind of biological characteristic 3D based on infrared photography is four-dimensional Data identification method and system.

Background technology

Biological characteristic is the intrinsic physiology or behavioural characteristic of biology, such as fingerprint, palmmprint, iris or face.Biological characteristic There are certain uniqueness and stability, i.e., the diversity ratio between certain biological characteristic of any two biology is larger, and biological characteristic It will not generally change a lot with the time, this allows for biological characteristic and is well suited for applying in authentication or identifying system In the scenes such as authentication information in.

In current binocular scheme, the method for registering for generally using basic gray scale, changing domain and essential characteristic, first Feature extraction is carried out to two width or multiple image, obtains the characteristic point of image, then by carrying out similarity measurement to characteristic point Find matched characteristic point pair；Then by matched characteristic point to the coordinate conversion parameter between obtaining a few width images；Finally Complete image matching, method for registering of this method for registering images based on half-tone information, the method for registering based on transform domain and The method for registering of feature based, mainly has the disadvantage that:

1) when the characteristic point unobvious or low resolution ratio in image, it is difficult to extract characteristic point from image.

2) when scene is close, the coordinate correspondence relationship of two images is not linear, is had using nonlinear transformation very big Limitation.

3) characteristic point is found from image, further carries out characteristic matching, the calculation of large amount of complex is needed in whole process Method, also, resolution ratio is higher, it is desirable that precision is higher, then calculate it is more complicated, it is in addition final therefore, it is necessary to high calculated performance Result of calculation is simultaneously unstable.

Therefore, there is an urgent need for being directed to biological characteristic to carry out multidimensional data identification, safety is improved, and branch is provided for subsequent application Support.

Invention content

In view of the above problems, it is proposed that the present invention overcoming the above problem in order to provide one kind or solves at least partly State biological characteristic 3D 4 D datas recognition methods based on infrared photography and the system of problem.

A kind of biological characteristic 3D 4 D data recognition methods based on infrared photography comprising following steps：

S01. biological information is acquired,

Using several biometric images of infrared camera and color camera acquisition organism within given time, according to institute Four dimension modules for stating several biometric images structure biological characteristic, to realize the biological characteristic 3D 4 D datas of the organism Acquisition；

S02. biological characteristic 4 D data is stored,

Scanning or typing with the identity information (I1, I2 ... In) of organism, using the identity information (I1, I2 ... In) as Distinguishing mark is associated storage to collected biological characteristic 3D 4 D datas, and formation includes a plurality of tetra- dimensions of biological characteristic 3D According to the database of (D1, D2 ... Dn)；

S03. the identification of target organism,

Acquire the biological characteristic 3D 4 D datas (T1, T2 ... Tn) of target organism, and target life described in scanning or typing The identity information (I1, I2 ... In) of object finds the data by the identity information (I1, I2 ... In) of the target organism The biological characteristic 3D 4 D datas (D1, D2 ... Dn) stored in library, by the biological characteristic 3D 4 D datas of the target organism (T1, T2 ... Tn) is compared with the biological characteristic 3D 4 D datas (D1, D2 ... Dn) stored in the corresponding database respectively It is right, to identify the identity of target organism.

Further, step S01 further includes：

The color camera is zoom color camera, to the collected 2D coloured images of one or more zoom color camera It is pre-processed, obtains the 2D high clear colorful pictures of target organism；

The collected infrared image of depth infrared camera is pre-processed, the depth infrared of the target organism is obtained Data, wherein the depth infrared data include the depth dimensions data of the target organism；

According to the depth infrared data of the target organism, obtain each composition point of the target organism to Spatial point cloud information in fixing time；

The 2D high clear colorfuls picture is carried out being registrated fusion with the spatial point cloud information；

According to the 2D high clear colorfuls picture and the spatial point cloud information be registrated result data that fusion obtains, with And the calibration information of the zoom color camera and the depth infrared camera, obtain the 4 D data of the target organism.

Further, the 4 D data step for obtaining the target organism further comprises：

By the depth infrared data transmission of several target organisms to image processor GPU and central processing unit The processing unit of CPU；The depth infrared data information of several target organisms is assigned in the block block of GPU and is carried out Operation, and centralized dispatching and the distribution function of CPU are combined, calculate the respective characteristic point of several described biometric images.

Further, carrying out pretreatment to the 2D coloured images includes：

The 2D coloured images are split, by the image-region of the target organism in the 2D coloured images It is split with background area；

The image-region that the target organism is obtained to segmentation carries out image enhancement processing, obtains the target organism 2D high clear colorful pictures；Wherein, described image enhancing processing includes at least one of：Automatic white balance processing, automatic exposure Light processing, auto-focusing processing and the processing of image deformity correction.

Further, the collected infrared image of depth infrared camera is pre-processed, including：

The infrared image is split, by the image-region and the back of the body of the target organism in the infrared image Scene area is split；

The infrared matrix abnormal pigmentary deposit on the skin information noise filtering of image-region progress to the target organism that segmentation obtains；

The 3D dimension datas of the target organism are obtained from the image-region of the filtered target organism.

Optionally, the 2D high clear colorfuls picture is carried out being registrated fusion with the spatial point cloud information, including：

According to the 3D dimension datas of each composition point in the spatial point cloud information, TOF inverse transformations are carried out, the mesh is obtained Mark the structure light depth image of organism；

Gaussian filtering is carried out respectively to the 2D high clear colorfuls picture and the structure light depth image；

Respectively from the 2D high clear colorfuls picture and the structure light depth image after gaussian filtering described in extraction The characteristic of target organism determines the common characteristic portion of the 2D high clear colorfuls picture and the structure light depth image Point；

In the common characteristic part, determine that the 2D high clear colorfuls picture is corresponding with the structure light depth image Point；

According to coordinate of the corresponding points in the 2D high clear colorfuls picture and the structure light depth image, it is based on three Method is cutd open at angle, determines the coordinate conversion relation of the 2D high clear colorfuls picture and the structure light depth image；

According to the coordinate conversion relation, the institute in the 2D high clear colorfuls picture and the structure light depth image is completed State the registration fusion of each characteristic of target organism.

Optionally, it is carried out being registrated the result for merging and obtaining with the spatial point cloud information according to the 2D high clear colorfuls picture The calibration information of data and the zoom color camera and the depth infrared camera, obtains the 3D of the target organism Data, including：

According to the 2D high clear colorfuls picture and the spatial point cloud information be registrated result data that fusion obtains, with And the calibration information of the zoom color camera and the depth infrared camera, in each characteristic of the target organism It is middle to choose multiple sampled points respectively, and the multiple sampled point is calculated within given time in the coordinate of three dimensions, it is based on institute It states multiple sampled points and obtains the 4 D data of the target organism in the coordinate of three dimensions.

Optionally, after obtaining the 3D data of the target organism, the method further includes：

Four-dimensional modeling is carried out according to 3D data of the target organism within given time, and four dimension modules are sent to Display is shown.

Optionally, the target organism includes：Head, face or the hand of human body.

Further, when the step S03 is to the identification of target organism, using temmoku point cloud matching identification method pair The biological characteristic 3D tetra- stored in the biological characteristic 3D 4 D datas (T1, T2 ... Tn) of the target organism and the database Dimension data (D1, D2 ... Dn) is compared；The temmoku point cloud matching identification method includes the following steps：

S301. characteristic point is fitted；

S302. curved surface entirety best fit；

S303. similarity calculation；

Further, the temmoku point cloud matching identification method comprises the following specific steps that：

Characteristic point fitting is carried out using based on spatial domain directly matched method, in the corresponding rigid region of two clouds, It chooses three and features above point is used as fitting key point, pass through coordinate transform, directly carry out characteristic point Corresponding matching；

After characteristic point Corresponding matching, the alignment of data of the point cloud after whole curved surface best fit；

Similarity calculation is carried out using least square method.

A kind of biological characteristic 3D 4 D data identifying systems based on infrared photography, including following device：

Collecting biological feature information device, for acquiring several biometric images of organism within given time, and Four dimension modules that biological characteristic is built according to several described biometric images, to realize the biological characteristic 3D tetra- of the organism Dimension data acquires；

Biological characteristic 4 D data storage device, for scanning or the identity information of typing organism (I1, I2 ... In), with The identity information (I1, I2 ... In) is associated storage as distinguishing mark to collected biological characteristic 3D 4 D datas, Formation includes the database of a plurality of biological characteristic 3D 4 D datas (D1, D2 ... Dn)；

The identity recognition device of target organism, for according to scanning or typing target organism identity information (I1, I2 ... In) find the biological characteristic 3D 4 D datas (D1, D2 ... Dn) stored in the database, and by the target organism Biological characteristic 3D 4 D datas (T1, T2 ... Tn) respectively with tetra- dimensions of biological characteristic 3D that are stored in the corresponding database It is compared according to (D1, D2 ... Dn), to identify the identity of target organism.

Further, the collecting biological feature information device includes：

First preprocessing module, for being located in advance to the collected 2D coloured images of one or more zoom color camera Reason, obtains the 2D high clear colorful pictures of target organism；

Second preprocessing module obtains described for being pre-processed to the collected infrared image of depth infrared camera The depth infrared data of target organism, wherein the depth infrared data include the depth dimensions number of the target organism According to；

Point cloud generation module, for the depth infrared data according to the target organism, to the target organism It is sampled, obtains the spatial point cloud information of the target organism；

Registration module, for carrying out being registrated fusion with the spatial point cloud information to the 2D high clear colorfuls picture；

3D data acquisition modules, for be registrated melting with the spatial point cloud information according to the 2D high clear colorfuls picture The calibration information for closing obtained result data and the zoom color camera and the depth infrared camera, obtains the mesh 3D data of the mark organism in given time.

Further, first preprocessing module in the following way pre-processes the 2D coloured images：

The 2D coloured images are split, by the image-region of the target organism in the 2D coloured images It is split with background area；

The image-region that the target organism is obtained to segmentation carries out image enhancement processing, obtains the target organism 2D high clear colorful pictures；Wherein, described image enhancing processing includes at least one of：Automatic white balance processing, automatic exposure Light processing, auto-focusing processing and the processing of image deformity correction.

Further, second preprocessing module is in the following way to the collected infrared image of depth infrared camera It is pre-processed：

The infrared image is split, by the image-region and the back of the body of the target organism in the infrared image Scene area is split；

The infrared matrix abnormal pigmentary deposit on the skin information noise filtering of image-region progress to the target organism that segmentation obtains；

The 3D dimension datas of the target organism are obtained from the image-region of the filtered target organism.

Optionally, the registration module is in the following way to the 2D high clear colorfuls picture and the spatial point cloud information Carry out registration fusion：

According to the 3D dimension datas of each sampled point in the spatial point cloud information, TOF inverse transformations are carried out, the mesh is obtained Mark the structure light depth image of organism；

Gaussian filtering is carried out respectively to the 2D high clear colorfuls picture and the structure light depth image；

Respectively from the 2D high clear colorfuls picture and the structure light depth image after gaussian filtering described in extraction The characteristic of target organism is based on triangulation, determines the 2D high clear colorfuls picture and the structure optical depth The shared image-region of image；

In the shared image-region, determine that the 2D high clear colorfuls picture is corresponding with the structure light depth image Point；

According to coordinate of the corresponding points in the 2D high clear colorfuls picture and the structure light depth image, institute is determined State the coordinate conversion relation of 2D high clear colorfuls picture and the structure light depth image；

According to the coordinate conversion relation, the institute in the 2D high clear colorfuls picture and the structure light depth image is completed State the registration fusion of each characteristic of target organism.

Optionally, the 3D data acquisition modules obtain the 3D data of the target organism in the following way：

The registration result with the spatial point cloud information and the zoom colour phase according to the 2D high clear colorfuls picture The calibration information of machine and the depth infrared camera chooses multiple adopt respectively in each characteristic of the target organism Sampling point, and calculate the coordinate of three dimensions of the multiple sampled point within given time, based on the multiple sampled point The coordinate of three dimensions in given time obtains the 4 D data of the target organism.

Optionally, further include：

Four-dimensional model modeling module, for being reconstructed according to 3D data of the target organism within given time, And four dimension modules are sent to display and are shown.

The beneficial effects of the invention are as follows：Provide a kind of biological characteristic 3D 4 D data recognition methods based on infrared photography And system first adopts target organism one or more zoom color camera in method provided in an embodiment of the present invention The 2D coloured images and depth infrared camera collected pre-processes the collected infrared image of target organism, is then based on It pre-processes obtained depth infrared data to be sampled, obtains spatial point cloud information of the target organism within given time, so It carries out being registrated fusion to pre-processing obtained 2D high clear colorfuls picture and 3D point cloud information afterwards, and then is based on registration result and change The calibration information of the camera of burnt color camera and depth infrared camera obtains the 3D data of target organism, completes target life 3D of the object within given time is rebuild.To identify that the identity information of target identifies data, it is not necessary to by the data and number of target person It is compared one by one according to the mass data in library, improves the efficiency of matching identification, greatly improved the speed of identification, adopt Characteristic point fitting is carried out with based on the directly matched temmoku point cloud matching identification method in spatial domain, realizes the Fast Quasi of biological characteristic point Composition and division in a proportion pair, and then realize the identification of identity rapid authentication.The face of people and hand are combination rigid and flexible, flexible portion Because action variation has different forms, such as expression shape change, facial muscle can change correspondingly state, and hand carries out different dynamic Make, hand state can also change correspondingly.Therefore different 3D renderings can be formed, if being identified with individual data characteristics, can deposited In error.Therefore several biometric images of Visible Light Camera acquisition organism within given time, according to several described lifes Object characteristic image builds four dimension modules of biological characteristic, realizes and is acquired to the 4 D data of organism, stores and be associated with to life afterwards The identity information of object, when whether again identify that target organism is the organism identity, even if target organism such as face Espressiove or hand have action, and also the identity of recognizable object organism, further improves accuracy of identification.

Description of the drawings

By reading the detailed description of hereafter preferred embodiment, various other advantages and benefit are common for this field Technical staff will become clear.Attached drawing only for the purpose of illustrating preferred embodiments, and is not considered as to the present invention Limitation.And throughout the drawings, the same reference numbers will be used to refer to the same parts.In the accompanying drawings：

Fig. 1 shows the biological characteristic 3D 4 D data recognition methods according to an embodiment of the invention based on infrared photography Flow chart；

Fig. 2 shows according to biological characteristic 3D 4 D data acquisition method stream of the one embodiment of the invention based on infrared photography Cheng Tu；

Fig. 3 shows the coordinate conversion relation according to an embodiment of the invention cutd open based on triangle between method two width figures of calculating Schematic diagram；

Fig. 4 shows the framework according to an embodiment of the invention based on infrared head face 4 D data acquisition system Schematic diagram；

Fig. 5 shows the module according to an embodiment of the invention based on infrared head face 4 D data acquisition system Structural schematic diagram；

Fig. 6 shows the framework signal according to an embodiment of the invention based on infrared hand 4 D data acquisition system Figure；

Fig. 7 shows the modular structure according to an embodiment of the invention based on infrared hand 4 D data acquisition system Schematic diagram；And

Fig. 8 shows the structural schematic diagram according to an embodiment of the invention based on infrared 4 D data identifying system.

Specific implementation mode

The exemplary embodiment of the disclosure is more fully described below with reference to accompanying drawings.Although showing the disclosure in attached drawing Exemplary embodiment, it being understood, however, that may be realized in various forms the disclosure without should be by embodiments set forth here It is limited.On the contrary, these embodiments are provided to facilitate a more thoroughly understanding of the present invention, and can be by the scope of the present disclosure Completely it is communicated to those skilled in the art.

It should be noted that the 3D 4 D datas in the present invention refer to three-dimensional space data binding time dimension data institute shape At data, three dimensions binding time dimension refers to：Multiple same time intervals or different time intervals, different angle, no With the data acquisition system of image or image formation situations such as orientation or different conditions.In other words：4 D data can be multiple phases With the 3D data acquisition systems of time interval or different time intervals, different angle, different direction, different expression forms etc..Described Head refers to all organs of human body neck (cervical vertebra) or more；Described face refers to face and ear.

In order to solve the above technical problems, an embodiment of the present invention provides a kind of, the biological characteristic 3D based on infrared photography is four-dimensional Data identification method.Fig. 1 shows that the biological characteristic 3D 4 D datas according to an embodiment of the invention based on infrared photography are known The flow chart of other method：

S01. biological information is acquired,

Utilize several biometric images of infrared camera and zoom color camera acquisition organism within given time, root Four dimension modules that biological characteristic is built according to several described biometric images, to realize that the biological characteristic 3D of the organism is four-dimensional Data acquire；

S02. biological characteristic 4 D data is stored,

Scanning or typing with the identity information (I1, I2 ... In) of organism, using the identity information (I1, I2 ... In) as Distinguishing mark is associated storage to collected biological characteristic 3D 4 D datas, and formation includes a plurality of tetra- dimensions of biological characteristic 3D According to the database of (D1, D2 ... Dn)；

S03. the identification of target organism,

Acquire the biological characteristic 3D 4 D datas (T1, T2 ... Tn) of target organism, and target life described in scanning or typing The identity information (I1, I2 ... In) of object finds the data by the identity information (I1, I2 ... In) of the target organism The biological characteristic 3D 4 D datas (D1, D2 ... Dn) stored in library, by the biological characteristic 3D 4 D datas of the target organism (T1, T2 ... Tn) is compared with the biological characteristic 3D 4 D datas (D1, D2 ... Dn) stored in the corresponding database respectively It is right, to identify the identity of target organism.

Preferably, as shown in Fig. 2, step S01 acquisition biological informations can also specifically include following steps S102 extremely Step S108.

Step S102 pre-processes the collected 2D coloured images of one or more zoom color camera, obtains mesh Mark the 2D high clear colorful pictures of organism；

Step S104 obtains the spatial point of the target organism according to the depth infrared data of the target organism Cloud information；

Step S106 carries out being registrated fusion to the 2D high clear colorfuls picture with the spatial point cloud information；

Step S108 be registrated the knot that fusion obtains according to the 2D high clear colorfuls picture and the spatial point cloud information The calibration information of fruit data and the zoom color camera and the depth infrared camera obtains the target organism and exists 3D data in given time.

The embodiment of the present invention carries out the acquisition of target organism using zoom color camera and depth infrared camera, and utilization is red The depth information of outer projection acquisition target organism, can significantly improve the acquisition precision and effect of the 3D data of target organism Rate solves the problems, such as the 3D accuracy of data acquisition of existing target organism and inefficient；Also, due to depth infrared camera Resolution ratio it is not high, therefore, the embodiment of the present invention coordinate zoom color camera, can to avoid the not high problem of resolution ratio, also, Due to color camera can with zoom, can effectively to target organism carry out local focusing, more improve image Clarity；In addition, due to being that the 2D high clear colorfuls picture of color camera and depth infrared camera is collected in the present invention Depth 3D information carries out registration fusion, to reduce the extraction of characteristic point, reduces the complexity of algorithm, improves reconstruct Precision and efficiency.

In the alternative embodiment of the present invention, 2D coloured images are pre-processed in above step S102, it specifically can be with Include the following steps S1021 to step S1022.

Step S1021 is split 2D coloured images, by the image-region of the target organism in 2D coloured images with Background area is split.In this step, 2D coloured images collected to zoom color camera are split, and target is given birth to The image-region of object and background area are separated, follow-up only to handle the image-region of target organism, to improve Processing speed.

Step S1022, the image-region that target organism is obtained to segmentation carry out image enhancement processing, obtain target organism The 2D high clear colorful pictures of body；Wherein, image enhancement processing includes at least one of：Automatic white balance processing, automatic exposure Processing, auto-focusing processing and the processing of image deformity correction.By the step, can to the coloured image of target organism into Row enhancing, to improve the clarity and contrast of image, improves the quality of coloured image, is merged convenient for subsequent registration.

Preferably, image enhancement processing includes image processor GPU and central processor CPU, is transmitted to at image Manage the processing unit of device GPU and central processor CPU；The image information of several biometric images is assigned to the block of GPU Operation is carried out in block, and combines centralized dispatching and the distribution function of CPU, calculates the respective feature of several biometric images Point.It can be seen that the embodiment of the present invention carries out biological information using infrared camera and zoom color camera control technology Acquisition, can significantly improve the collecting efficiency of biological information.Also, the embodiment of the present invention is based on central processing unit and figure The parallel computation of processor can efficiently realize the processing of characteristic information.

Preferably, GPU is double GPU, and every GPU has a multiple block, such as 56 block, the embodiment of the present invention to this not It is restricted.

In the alternative embodiment of the present invention, to the collected infrared image of depth infrared camera in above step S104 It carries out pretreatment and may comprise steps of S1041- steps S1043.

Step S1041：The collected infrared image of depth infrared camera is split, the target in infrared image is given birth to The image-region of object is split with background area.

Step S1042, the infrared matrix abnormal pigmentary deposit on the skin information noise filtering of image-region progress to the target organism that segmentation obtains. By the way that infrared matrix abnormal pigmentary deposit on the skin information noise, the noise in infrared image can be filtered out, precision is improved, is reduced at subsequent data Reason.

Step S1043 obtains the 3D dimension datas of target organism from the image-region of filtered target organism. The sensor of depth infrared camera sends out modulated near infrared light, meets object back reflection, and sensor is emitted by calculating light , to generate depth information, pass through the depth of target organism with reflection interval difference or phase difference come the distance for the target organism that converts Information is spent, the 3D dimension datas of target organism can be obtained.

In the alternative embodiment of the present invention, in above step S106 to 2D high clear colorfuls picture and 3D point cloud information into Row registration, can specifically include following steps S1061- steps S1066.

Step S1061 carries out TOF inverse transformations, obtains mesh according to the 3D dimension datas of each composition point in 3D point cloud information Mark the structure light depth image of organism.

Step S1062 carries out gaussian filtering respectively to 2D high clear colorfuls picture and structure light depth image.

Step S1063, respectively from the 2D high clear colorfuls picture and the structure light depth image after gaussian filtering The characteristic of the middle extraction target organism determines being total to for the 2D high clear colorfuls picture and the structure light depth image There is characteristic.

Step S1064 determines that 2D high clear colorfuls picture is corresponding with structure light depth image in common characteristic part Point.

Step S1065 cuts open method based on triangle, according to corresponding points in 2D high clear colorfuls picture and structure light depth image Coordinate determines the coordinate conversion relation of 2D high clear colorfuls picture and structure light depth image.As shown in figure 3, method is cutd open based on triangle, It can obtain the coordinate of the 2D high clear colorfuls picture and the structure light depth image of depth infrared camera of the acquisition of zoom color camera Transformation relation.

Step S1066 completes the target in 2D high clear colorfuls picture and structure light depth image according to coordinate conversion relation The registration of each characteristic of organism merges.

In above-mentioned steps S1063, different characteristics can be extracted, for example, such as according to different target organisms Fruit target organism is the hand of human body, then characteristic can be fingerprint lines, if target organism is the face of human body, Then characteristic can be five lines of outline seen of people on the face, and the specific embodiment of the present invention is not construed as limiting.

S1061- steps S1066 through the above steps can carry out 2D high clear colorfuls picture and structure light depth image Registration fusion, obtains the 3D information of target organism, including but not limited to：The spatial form characteristic of target organism, table Face textural characteristics data, Facing material and light characteristic etc..

In the alternative embodiment of the present invention, according to the 2D high clear colorfuls picture and the sky in above step S108 Between point cloud information carry out the registration obtained result data of fusion and the zoom color camera and the depth infrared camera Calibration information can be according to the 2D high clear colorfuls picture and the spatial point when obtaining the 3D data of the target organism Cloud information carries out the calibration of result data and the zoom color camera and the depth infrared camera that registration fusion obtains Information chooses multiple sampled points in each characteristic of the target organism, and calculates the multiple sampled point respectively In the coordinate of three dimensions, the 3D numbers of the target organism are obtained in the coordinate of three dimensions based on the multiple sampled point According to.In the alternative embodiment, sampled point can be with the key point of selection target organism, for example, on the profile of characteristic Key point etc. can specifically be determined according to target organism, is not construed as limiting in the embodiment of the present invention.

In the alternative embodiment of the present invention, after step S108, target organism can also be modeled, because This, after step S108, this method can also include：It is carried out according to 3D data of the target organism within given time Modeling, and this four dimension module is sent to display and is shown.It, can be by collected target organism by the alternative embodiment 3D data within given time carry out four-dimensional modeling, obtain four dimension modules of target organism, and by the model visualization, make User can easily detect whether collected data accurate, and can aspect this model is applied in other sides Face.

In the alternative embodiment of the present invention, target organism includes but not limited to：The head of human body, face, iris or Hand.

In the alternative embodiment of the present invention, it can be directed to different target organisms, different systems pair can be built Target organism is acquired.For example, in the case of the head and face that target organism is human body, may be used such as Fig. 4 It is acquired with acquisition system shown in fig. 5.

As shown in Figure 4 and Figure 5, should include mainly based on infrared head, face, iris 4 D data acquisition system：In Entreat processing module 301, depth infrared camera 302, zoom color camera 303, light module 304, camera rotating mechanism 305, people Body-sensing is answered measurement module 306, camera data transmission module 307, display interface 308, operation interface 309, understructure 310, is adjusted Save seat 311 and power module 312.

Wherein, as shown in Figure 4 and Figure 5, human body sensing measurement module 306 is fixed on understructure 310, display interface 308 and operation interface 309 connect with understructure 310, central processing module 301 is fixed on inside understructure 310, camera number It is located inside understructure 310 according to transmission module 307, understructure 310 is connect with camera rotating mechanism 305, camera whirler Structure 305 connects zoom color camera 303, depth infrared camera 302 and light module 304.

Camera rotating mechanism 305 can include but is not limited to adjustable angle camera fixed frame and tumbler, and rotate Device may include servo motor, with fast case and transmission device.Zoom color camera 303, depth infrared camera 302, light mould Group 304 is fixed on the adjustable angle fixed frame of camera rotating mechanism 305, and adjustable angle fixed frame is fixed on camera rotation On the tumbler of mechanism 305.The rotation dress of the camera rotating module connection camera rotating mechanism 305 of central processing module 301 The servo motor set, is worked by control servomotor, to drive with fast case and transmission operation, and then drives rotation dress Rotation is set, finally so that adjustable angle camera fixed frame rotates, and then reaches adjustment zoom color camera 303 and depth infrared The purpose of the angle of camera 302.

It adjusts seat 311 and is fixed on understructure 310, adjust about 311 adjustable height of seat and the rotatable angle in left and right Degree, adjust seat 311 include horizontally rotate servo motor, vertical lift servo motor, it is horizontal with fast case, horizontally rotate gear, It is vertically moved up or down transmission gear screw rod and body weight inductor, wherein the chair control module connection of central processing module 301 is adjusted Seat 311 is saved, about 311 seat adjustment height is controlled to adjust or rotates left and right angle.

Wherein, as shown in figure 5, central processing module 301 may include image quality processing chip 3011, at infrared distance measurement It is aobvious to manage chip 3012, point cloud generation unit 3013,3D registration Algorithms processing module 3014,3D Data Synthesis module 3015, video Show module 3016, microprocessor control module 3017, chair control module 3018, camera rotation control module 3019 and light control Molding block 3010.

Wherein, central processing module 301 can pass through Camera Link high-speed datas with camera data transmission module 307 Line connects；Depth infrared camera 302 can be connect with camera data transmission module 307 by 3.0 data line of high speed USB；It is colored Infrared camera can be connect with camera data transmission module 307 by MIPI high speed data lines；The control of light module 304 and phase Machine data transmission module 307 can be connected by RS232 serial port data lines；The rotating module of camera rotating mechanism 305 and center Camera rotation control module 3019 in processing module 301 is connected by I2C serial port data lines；Human body sensing measurement module 306 Control section connect by tri- line serial port data lines of SPI with the microprocessor control module 3017 of central processing module 301；It adjusts The control section for saving seat 311 and the microprocessor control module 3017 of central processing module 301 pass through RS232 serial port data lines Connection；The data transmit-receive part of display interface 308 passes through high definition HDMI with the video display module 3016 of central processing module 301 Data line connects；The data transmit-receive part of operation interface 309 is logical with the microprocessor control module 3017 of central processing module 301 Cross the connection of I2C data lines.

In one embodiment of the invention, image quality processing chip 3011 is mainly used for exporting camera transmission module Picture color saturation adjustment, noise filtering and distortion correction etc..Infrared distance measurement processing chip 3012 mainly for the treatment of The distance matrix information of infrared image, filtering noise reduction and deep conversion etc..Data after the processing of image quality processing chip 3011 With data fusion after the processing of infrared distance measurement processing chip 3012 mould is handled to 3D registration Algorithms processing module 3014,3D registration Algorithms Block 3014 cuts open method and gaussian filtering method etc. by triangle and carries out registration fusion to two class data, the 3D for finally obtaining registration fusion Data are output to 3D Data Synthesis module 3015 and carry out 3D modeling, and the 3D data that 3D modeling obtains are output to video display module 3016 show.

It in an alternate embodiment of the present invention where, can be first zoom color camera 303 and depth infrared camera 302 Lens optical is centrally located in 0 degree of state of level, and the light source center and zoom color camera 303 and depth of light module 304 are red The lens optical centralized positioning of outer camera 302 is in together on vertical line, and wherein 305 rotational angle of camera rotating mechanism can be 0- 180 degree, speed can be that 5cm-48cm is per second, wherein the speed ratio of matching with fast case can be 300：1 (servo motor：Turning gear Wheel).

In an alternate embodiment of the present invention where, horizontal turn servo motor, level with fast case and horizontally rotate gear Seat horizontal rotational structure is formed, chair vertical lifting is by servo motor and vertical lift transmission gear screw rod control, wherein seat The speed of chair vertical lift can be that 10cm-30cm is per second, and the speed of horizontal rotation can be per second with 15cm-35cm, and level is with speed Case matches speed ratio 200：1 (motor speed：Horizontally rotate gear rotational speed).

When specifically used, it can be executed with 1- steps 11 according to the following steps.

Step 1, start setting：After startup, the input equipment relevant parameter on display interface 308, including the weight of people and Height, colour of skin setting, the colour temperature and luminance parameter of Auto-matching light, operating mode：Automatic operation mode and manual work mould Formula.

Step 2, whether in place human body sensing measurement module 306 detects people, and measures the height value of people's sitting posture, and zoom is colored Camera 303 detects face automatically, judges the angle value that people sits.

Step 3, seat is adjusted：According to the present level value and angle value of people's sitting posture, adjusts seat and be automatically adjusted to face It is suitble to zoom color camera 303 to take pictures the state scanned with depth infrared camera 302.

Step 4, zoom color camera 303 is according to face size, control camera lens automatic telescopic to suitable visual angle and clearly Clear degree.

Step 5, for light module 304 according to the colour of skin and ambient light of face, the brightness of adjust automatically light and colour temperature make change Burnt color camera 303 and depth infrared camera 302 collect the picture of high-resolution and high contrast.

Step 6, after the sitting posture of people reaches suitable position and light Matching and modification, depth infrared camera 302 is in face side Position starts to collect depth distance information.

Step 7, from a side position of face start-up operation after, camera rotating mechanism 305 with fixed speed rotate and simultaneously Camera picture and Range finder data are transmitted at the image quality processing chip 3011 and infrared distance measurement of central processing module 301 Manage chip 3012.

Step 8, infrared Range finder data transmission generates 3D to the point cloud generation unit 3013 of central processing module 301 Point cloud information.

Step 9, the high definition picture combination 3D point cloud information input of zoom color camera 303 is to 3D registration Algorithm processing modules 3014,3D registration Algorithm processing modules 3014 carry out registration fusion calculation and obtain registration fused data.

Step 10, registration fused data is input to 3D Data Synthesis module 3015,3D Data Synthesis module 3015 according to Quasi- fused data generates 3D data models.

Step 11, after 3D data models generate, 3D data models are input to display interface 308 by video display module 3016 Upper display, and the 3D data models of display can be operated by operation interface 309.

In the alternative embodiment of the present invention, hand can also be directed to and build the 3D numbers that corresponding acquisition information carries out hand According to acquisition.Fig. 5 is the configuration diagram based on infrared hand 3D data collecting systems, and Fig. 6 is based on infrared hand 3D numbers It, as shown in Figure 5 and Figure 6, should be main based on infrared hand 3D data collecting systems according to the modular structure schematic diagram of acquisition system Including：Central processing module 501, depth infrared camera 502, zoom color camera 503, light module 504, rotating mechanism 505, Runing rest 510, hand model support construction 506, display operation module 511, hand fixed model 507, cabinet 508 and power supply Module 509.

In the alternative embodiment, as shown in Figure 6 and Figure 7, hand model support construction 506 is fixed on cabinet 508, hand Portion's fixed model 507 is fixed in hand model support construction 506, and display operation module 511 is fixed on cabinet 508, center Processing module 501 is fixed on the inside of cabinet 508, and rotating mechanism 505 is fixed on the inside of cabinet 508, and runing rest 510 is fixed On rotating mechanism 505, depth infrared camera 502, zoom color camera 503 and light module 504 are fixed on runing rest 510 On.

In an alternate embodiment of the present invention where, as shown in fig. 7, central processing module 501 includes image quality processing Chip 5010, infrared distance measurement processing chip 5011, point cloud generation unit 5012,3D registration Algorithms processing module 5013,3D data Synthesis module 5014, video display module 5015, microprocessor control module 5016, camera rotation control module 5017 and light Control module 5018.

In an alternate embodiment of the present invention where, depth infrared camera 502 can pass through height with central processing module 501 Fast USB3.0 data lines connection；Zoom color camera 503 can be connected with central processing module 501 by MIPI high speed data lines It connects；The control section of light module 504 can pass through with the camera rotation control module 5017 in central processing module 501 RS232 serial port data lines connect；The control section of rotating mechanism 505 and the camera rotation control mould in central processing module 501 Block 5017 can be connected by I2C serial port data lines；The data display unit and central processing module of display operation module 511 501 video display module 5015 is connected by high definition HDMI data lines；The data control section of display operation module 511 is in The microprocessor control module 5016 of centre processing module 501 is connected by I2C data lines.

In the optional embodiment of the present invention, structure light mode may be used in depth infrared camera 502, is differentiating Increase by 503 combination of zoom color camera in terms of rate, to be conducive to improve precision, resist strong light aspect, power consumption, resolution ratio, Parameter advantage in terms of frame speed and volume.

In an alternate embodiment of the present invention where, image quality processing chip 5010 includes automatic white balance for handling AWB, automatic exposure AE, auto-focusing AF and image deformity correction etc..

In an alternate embodiment of the present invention where, infrared distance measurement processing chip 5011 includes infrared matrix abnormal pigmentary deposit on the skin for handling The filtering of information noise, the 3D dimension datas for obtaining target organism and point cloud information etc..

In an alternate embodiment of the present invention where, zoom color camera 503, depth infrared camera 502 and light module 504 are fixed on the rotating mechanism 505 of adjustable angle, first the camera lens of zoom color camera 503 and depth infrared camera 502 Optical centre is located in 0 degree of state of level, light source center and the zoom color camera 503 and depth infrared phase of light module 504 The lens optical centralized positioning of machine 502 is in together on vertical line.Optionally, the rotational angle of rotating mechanism 505 could be provided as 0-175 degree, speed could be provided as that 6cm-30m is per second, could be provided as 200 with speed ratio with fast case：1 (servo motor：Rotation Gear).The focal range of zoom color camera 503 could be provided as f=4.5~108mm, the image of zoom color camera 503 The resolution ratio of sensor could be provided as 16,000,000 pixels, Aperture Range F=3.0~6.9, in addition, according to the size of finger, most Nearly focal distance could be provided as 10cm, accurately to focus to finger.

In an alternate embodiment of the present invention where, depth infrared camera 502 could be provided as：Resolution ratio is 1920x1080, frame per second 30fps, measurement distance 0.2-4m, power consumption 1W.Certainly, however it is not limited to this, in practical applications, It can also use above-mentioned parameter that other values, the specific present invention can also be used to be not construed as limiting.

It in a particular application, can be with using the above-mentioned 3D data for acquiring fingerprint based on infrared hand 3D data collecting systems Include the following steps 1-11.

Step 1, start setting：After startup, the input equipment relevant parameter in display operation module 511, may include but It is not limited to the colour temperature and luminance parameter of the weight of people and the light module 504 of height, colour of skin setting and Auto-matching.

Step 2, it after finger is put into model, is automatically adjusted to finger and zoom color camera 503 is suitble to take pictures and depth infrared The state that camera 502 scans.

Step 4, zoom color camera 503 is according to finger size, camera lens automatic telescopic to suitable visual angle and clarity.

Step 5, adjustment light module 504：According to the colour of skin and ambient light of finger, the 504 adjust automatically brightness of light module And colour temperature, so that zoom color camera 503 and depth infrared camera 502 can collect the picture of high-resolution and high contrast.

Step 6, depth infrared camera 502 starts to collect depth distance information in the first finger side position, successively to the Ten fingers.

Step 7, after the start-up operation of a side position of finger, rotating mechanism 505 is rotated with fixed speed, and simultaneous transmission The image quality processing chip 5010 and infrared distance measurement of camera picture and Range finder data to central processing module 501 handle core Piece 5011 is acquired to the tenth finger successively.

It step 8, will be for the point cloud generation unit of the data of the depth infrared of each finger to central processing module 501 5012, point cloud generation unit 5012 generates 3D point cloud information according to the depth infrared data of each finger.

Step 9, the finger high definition picture combination 3D point cloud information input of zoom color camera 503 is handled to 3D registration Algorithms Module 5013,3D registration Algorithms processing module 5013 carry out registration fusion calculation and obtain registration fused data.

Step 10, registration fused data is input to 3D Data Synthesis module 5014, and 3D Data Synthesis module 5014 will be registrated Data are coordinated to generate 3D finger data models.

Step 11, after 3D finger datas model generates, 3D finger data models are transferred to aobvious by video display module 5015 Show that the display interface of operation module 511 shows and operates 3D data by operation interface.

In an alternate embodiment of the present invention where, light module 504 is adjustable color temperature and brightness, and reference color temperature can Think that 4000-5000 (Kelvin), range of luminance values can be 20-30lux/W.

In an alternate embodiment of the present invention where, it is 40- that the parameter of zoom color camera 503, which can be horizontal field of view angle, 97 degree, vertical 45-70 degree.

In an alternate embodiment of the present invention where, structure light mode, ranging model may be used in depth infrared camera 502 Enclose 0.2m-4m, precision is +/- 0.1mm, horizontal field of view angle is 43-63 degree, vertical 25-56 degree.

In embodiments of the present invention, the dimension of time is added in the biological characteristic of 3D, constitutes four-dimensional biological characteristic, completely The various features for restoring biology, unlimited possibility is provided for the application of subsequent biological attribute data.

May include the space shape for describing four dimension modules on different time in four dimension modules of the biological characteristic of structure Shape characteristic, surface texture feature data of four dimension modules of description on different time, four dimension modules of description are in different time On Facing material and 4 D datas, the embodiment of the present invention such as light characteristic this is not restricted.

In embodiments of the present invention, in step S02, the collected biological characteristic 3D 4 D datas of storing step S01 institutes, And collected biological characteristic 3D 4 D datas are deposited using the identity information of organism (I1, I2 ... In) as distinguishing mark Storage, formation include the database of a plurality of biological characteristic 3D 4 D datas (D1, D2 ... Dn), such as：4 D data D1 and the biology The identity information I1 of body is associated storage, and the 4 D data D2 of another organism and the identity information I2 of the organism are closed Connection storage, and so on, formation includes the database of n organism 4 D data.

Wherein, when acquisition target, that is, organism is human body, then identity information I includes but not limited to people's：Name, property , not one or more in age and certificate number, certificate number may include people in life commonly used such as identification card number, It is one or more in passport No., license number, social security number or officer's identity card number.

Preferably, the identity information is obtained by scanning identity card, passport, driving license, social security card or officer's identity card, alternatively, Manually or automatically the mode of typing obtains identity information from identity card, passport, driving license, social security card or officer's identity card.

Preferably, in identifications of the step S03 to target organism, using temmoku point cloud matching identification method to target The life stored in the biological characteristic 3D 4 D datas (T1, T2 ... Tn) and database of organism (organism of identity i.e. to be identified) Object feature 3D 4 D datas (D1, D2 ... Dn) are compared, to identify the identity of target organism.First, by inputting target The identity information of organism can be quickly found out have stored in database with the identity in this way such as the identification card number of human body Card number be filename a 4 D data (D1, D2 ... Dn), without the mass data in the data and database by target person into Row compares one by one, improves the efficiency of matching identification, greatly improves the speed of identification, then again current collected The 4 D data (T1, T2 ... Tn) of the human body is compared with the 4 D data taken out in data, finally identifies the human body Identity whether meet, and then realize authentication, specifically, being included the following steps using temmoku point cloud matching identification method：

S301. characteristic point is fitted；

S302. curved surface entirety best fit；

S303. similarity calculation.

Preferably, temmoku point cloud matching identification method further includes following specific steps：

Characteristic point fitting is carried out using based on spatial domain directly matched method, in the corresponding rigid region of two clouds, It chooses three and features above point is used as fitting key point, pass through coordinate transform, directly carry out characteristic point Corresponding matching；

After characteristic point Corresponding matching, the alignment of data of the point cloud after whole curved surface best fit；

Similarity calculation is carried out using least square method.

Temmoku point cloud matching identification method (Yare Eyes point cloud match recognition method) is known Other process and operation principle are as follows：First, point cloud at a time is the basic element for forming four dimension modules, it includes space Coordinate information (XYZ) and colouring information (RGB).The attribute of point cloud includes spatial resolution, positional accuracy, surface normal etc.. Its feature is not influenced by external condition, will not all be changed for translating and rotating.Reverse software can carry out a cloud Editor and processing, such as：Imageware, geomagic, catia, copycad and rapidform etc..Temmoku point cloud, which compares, to be known Other method is distinctive to include based on the directly matched method in spatial domain：Iteration closest approach method ICP (Iterative closest Point), ICP methods are generally divided into two steps, the fitting of first step characteristic point, second step curved surface entirety best fit.First fitting alignment The purpose of characteristic point is in order to which the shortest time is found and is aligned two clouds of fitting to be compared.But not limited to this.Such as it can be with It is：

The first step chooses three and features above point is used as fitting key point in the corresponding rigid region of two clouds, By coordinate transform, characteristic point Corresponding matching is directly carried out.

ICP is a very effective tool in 3D data reconstruction process, at certain for curve or the registration of curved surface segment One moment gave the rough initial alignment condition of two 3D models, and ICP iteratively seeks rigid transformation between the two with minimum Change alignment error, realizes the registration of the space geometry relationship of the two.

Given setWithSet element indicates two model surfaces Coordinate points, the iterative solution of ICP registration techniques apart from nearest corresponding points, establish transformation matrix, and implement to become to one of It changes, until reaching some condition of convergence, its coding of iteration stopping is as follows：

1.1 ICP algorithm

Input .P₁, P₂.

P after output is transformed₂

P₂(0)=P₂, l=0；

Do

For P₂(l) each point in

In P₁In look for a nearest point yi；

End For

It calculatesRegistration error E；

IfE is more than a certain threshold value

Calculate P₂(l) the transformation matrix T (l) between Y (l)；

P₂(l+1)=T (l) P₂(l), l=l+1；

Else

Stop；

End If

While||P₂(l+l)-P₂(l)||>threshold；

Wherein registration error

1.2 matchings based on local feature region：

By taking the identification of human face's information as an example, faceform is broadly divided into rigid model part and plasticity model part, plasticity The accuracy of deformation effect alignment, and then influence similarity.Second of gathered data has local difference to plasticity model for the first time, A kind of solution route be only in rigid region selected characteristic point, characteristic point be extracted from an object, under certain condition Constant attribute is stablized in holding, and alignment is fitted using common method iteration closest approach method ICP characteristic points.

Extraction face is by the smaller region of expression influence first, such as nasal area nose, eye outer frame angle, forehead region, cheekbone Bone region, ear region etc..Human hands finger joint is rigid region, and metacarpus is plastic region, in finger portion region selected characteristic point It is best.Iris is rigid model.

Requirement to characteristic point：

1) completeness contains object information as much as possible, is allowed to be different from the object of other classifications；2) compactedness tables It is as few as possible up to required data volume；3) feature is also required preferably to be remained unchanged under model rotation, translation, mirror transformation.

In 3D living things feature recognitions, using two 3D biological characteristic model point clouds of alignment, the similar of input model is calculated Degree, wherein registration error is as difference measure.

Second step：After characteristic point best fit, the alignment of data of the point cloud after whole curved surface best fit.

Third walks, similarity calculation.Least square method

Least square method (also known as least squares method) is a kind of mathematical optimization techniques.It by minimize error quadratic sum Find the optimal function matching of data.Unknown data can be easily acquired using least square method, and these are acquired Data and real data between error quadratic sum be minimum.Least square method can also be used for curve matching.It is some other excellent Change problem can also be expressed by minimizing energy or maximizing entropy with least square method.It is usually used in solving curve fit problem, And then solve the complete fitting of curved surface.It can accelerate Data Convergence by iterative algorithm, quickly acquire optimal solution.

If 3D data models at a time are inputted with stl file format, pass through calculating point cloud and triangle The distance of piece determines its deviation.Therefore, this method needs to establish plane equation to each tri patch, and deviation arrives flat for point The distance in face.And be IGES or STEP models for 3D data models at a time, since free form surface expression-form is The faces NURBS, so the distance calculating in point to face needs the method for using numerical optimization to be calculated.By in iterative calculation point cloud Each point expresses deviation to the minimum range of nurbs surface, or that nurbs surface carried out specified scale is discrete, with point and point Apart from approximate expression point deviation, or it is converted into STL formats and carries out deviation calculating.Different coordinate alignment and deviation calculating side The testing result of method, acquisition is also different.The size of alignment error will directly affect the confidence level of accuracy of detection and assessment report.

Best fit alignment is that detection error averagely arrives entirety, is terminated in terms of iteration by ensureing the whole minimum condition of deviation The alignment procedure of calculation carries out 3D analyses to registration result, generates result object in the form of the root mean square of error between two figures Output, root mean square is bigger, and difference of two models of reflection at this is bigger.Vice versa.Judge according to registration ratio is compared Whether it is to compare subject matter.

The biological characteristic 3D 4 D data identifying systems based on infrared photography that the present invention also provides a kind of comprising following dress It sets：

Collecting biological feature information device, for acquiring several biometric images of organism within given time, and Four dimension modules that biological characteristic is built according to several described biometric images, to realize the biological characteristic 3D tetra- of the organism Dimension data acquires；

Biological characteristic 4 D data storage device, for scanning or the identity information of typing organism (I1, I2 ... In), with The identity information (I1, I2 ... In) is associated storage as distinguishing mark to collected biological characteristic 3D 4 D datas, Formation includes the database of a plurality of biological characteristic 3D 4 D datas (D1, D2 ... Dn)；

The identity recognition device of target organism, for according to scanning or typing target organism identity information (I1, I2 ... In) find the biological characteristic 3D 4 D datas (D1, D2 ... Dn) stored in the database, and by the target organism Biological characteristic 3D 4 D datas (T1, T2 ... Tn) respectively with tetra- dimensions of biological characteristic 3D that are stored in the corresponding database It is compared according to (D1, D2 ... Dn), to identify the identity of target organism.

Preferably, collecting biological feature information device includes：

Image acquisition units, the camera matrix for being formed using more cameras are acquired biological information, obtain To several biometric images；

Feature point extraction unit is extracted for handling several biometric images in several biometric images Respective characteristic point；

It is special to generate biology for respective characteristic point in several biometric images based on extraction for point cloud generation unit The feature point cloud data of sign；

Four-dimensional model construction unit, four dimension modules for building biological characteristic according to feature point cloud data, to realize life The acquisition of object feature 3D 4 D datas.

It should be noted that the biological characteristic in the embodiment of the present invention is not limited to above-mentioned head, face and/or iris And hand, it can also be without limitation including other biological feature, such as foot, the embodiment of the present invention.

Based on each embodiment offer above based on infrared 4 D data recognition methods, it is based on same inventive concept, The embodiment of the present invention additionally provides a kind of based on infrared 4 D data identifying system.Fig. 8 is shown to be implemented according to the present invention one The structural schematic diagram of the biological characteristic 3D 4 D data identifying systems based on infrared photography of example.As shown in figure 8, the device can be with Including collecting biological feature information device 910, biological information storage device 920 and target organism identification 930.Its Middle collecting biological feature information device 910 includes the first preprocessing module 110, the second preprocessing module 120, point cloud generation module 130, registration module 140 and 3D data acquisition modules 150.

Now introduce the function of each composition or device based on infrared 4 D data identification device of the embodiment of the present invention with And the connection relation between each section：

First preprocessing module 110, for being carried out to the collected 2D coloured images of one or more zoom color camera Pretreatment, obtains the 2D high clear colorful pictures of target organism；

Second preprocessing module 120 obtains mesh for being pre-processed to the collected infrared image of depth infrared camera Mark the depth infrared data of organism, wherein depth infrared data include the depth dimensions data of target organism；

Point cloud generation module 130, for the depth infrared data according to target organism, to adopting for target organism Sample obtains the spatial point cloud information of target organism；

Registration module 140 is registrated fusion for being carried out with spatial point cloud information to 2D high clear colorfuls picture；

3D data acquisition modules 150, for be registrated merging with spatial point cloud information according to 2D high clear colorfuls picture The calibration information of the result data and zoom color camera and depth infrared camera that arrive obtains target organism to timing Interior 3D data.

In an alternate embodiment of the present invention where, the first preprocessing module 110 can be in the following way to 2D colours Image is pre-processed：

2D coloured images are split, by the image-region of the target organism in 2D coloured images and background area into Row segmentation；

The image-region that target organism is obtained to segmentation carries out image enhancement processing, obtains the 2D high definitions of target organism Color image；Wherein, image enhancement processing includes at least one of：Automatic white balance processing, automatic exposure handle, are automatic right Coke processing and the processing of image deformity correction.

In an alternate embodiment of the present invention where, the second preprocessing module 120 is in the following way to depth infrared phase The collected infrared image of machine is pre-processed：

Infrared image is split, the image-region of the target organism in infrared image and background area are divided It cuts；

The infrared matrix abnormal pigmentary deposit on the skin information noise filtering of image-region progress to the target organism that segmentation obtains；

The 3D dimension datas of target organism are obtained from the image-region of filtered target organism.

In an alternate embodiment of the present invention where, registration module 140 in the following way to 2D high clear colorfuls picture with Spatial point cloud information carries out registration fusion：

According to the 3D dimension datas of each sampled point in spatial point cloud information, TOF inverse transformations are carried out, target organism is obtained Structure light depth image；

Gaussian filtering is carried out respectively to 2D high clear colorfuls picture and structure light depth image；

Respectively from the 2D high clear colorfuls picture after gaussian filtering and extraction target organism in structure light depth image Characteristic is based on triangulation, determines the shared image-region of 2D high clear colorfuls picture and structure light depth image；

In shared image-region, the corresponding points of 2D high clear colorfuls picture and structure light depth image are determined；

According to coordinate of the corresponding points in 2D high clear colorfuls picture and structure light depth image, 2D high clear colorful pictures are determined With the coordinate conversion relation of structure light depth image；

According to coordinate conversion relation, each of 2D high clear colorfuls picture and the target organism in structure light depth image is completed The registration of a characteristic merges.

In an alternate embodiment of the present invention where, 3D data acquisition modules 150 obtain target organism in the following way 3D data of the body within given time：

According to the registration result and zoom color camera and depth infrared of 2D high clear colorfuls picture and spatial point cloud information The calibration information of camera chooses multiple sampled points in each characteristic of target organism, and calculates multiple samplings respectively Point obtains the 3D data of target organism based on multiple sampled points in the coordinate of three dimensions in the coordinate of three dimensions.

In an alternate embodiment of the present invention where, further include：Modeling module is used for according to target organism to timing Interior 3D data are modeled, and four dimension module is sent to display and is shown.

Biological attribute data storage device 920 acquires biological characteristic 3D 4 D datas (T1, T2 ... of target organism Tn), the biological characteristic 3D tetra- stored in the database is found using the identity information of the target organism (I1, I2 ... In) Dimension data (D1, D2 ... Dn).

The identification 930 of target organism, by biological characteristic 3D 4 D datas (T1, T2 ... of the target organism Tn it) is compared respectively with the biological characteristic 3D 4 D datas (D1, D2 ... Dn) stored in the corresponding database, with identification The identity of target organism.

According to the combination of any one above-mentioned alternative embodiment or multiple alternative embodiments, the embodiment of the present invention can reach Following advantageous effect：

The recognition methods of 3D 4 D datas and device that an embodiment of the present invention provides a kind of based on infrared photography, in the present invention In the method that embodiment provides, 2D coloured images collected to target organism to one or more zoom color camera first The collected infrared image of target organism is pre-processed with depth infrared camera, is then based on the depth that pretreatment obtains Infrared data is sampled, and spatial point cloud information of the target organism within given time is obtained, and is then obtained to pretreatment 2D high clear colorfuls picture carries out being registrated fusion with space cloud information, and then based on registration result and zoom color camera and depth The calibration information of the camera of infrared camera obtains 3D data of the target organism within given time, completes target organism Model reconstruction.Simultaneously using target organism identity information as mark to collected biological characteristic 3D 4 D datas into Row associated storage, formation include the database of a plurality of biological characteristic 3D 4 D datas.Target biometric data is acquired again, profit The biological characteristic 3D 4 D datas stored in database are found with the identity information of the target organism, by the target organism The biological characteristic 3D 4 D datas of body are compared with the biological characteristic 3D 4 D datas stored in the corresponding database respectively It is right, to identify the identity of target organism.It can thus be seen that due to being by the two-dimentional high clear colorful of color camera in the present invention Picture and the collected depth 3D information of depth infrared camera carry out registration fusion, to reduce the extraction of characteristic point, reduce The complexity of algorithm, improves the precision and efficiency of reconstruction.

In the instructions provided here, numerous specific details are set forth.It is to be appreciated, however, that the implementation of the present invention Example can be put into practice without these specific details.In some instances, well known method, structure is not been shown in detail And technology, so as not to obscure the understanding of this description.

Similarly, it should be understood that in order to simplify the disclosure and help to understand one or more of each inventive aspect, Above in the description of exemplary embodiment of the present invention, each feature of the invention is grouped together into single implementation sometimes In example, figure or descriptions thereof.However, the method for the disclosure should be construed to reflect following intention：It is i.e. required to protect Shield the present invention claims the more features of feature than being expressly recited in each claim.More precisely, as following Claims reflect as, inventive aspect is all features less than single embodiment disclosed above.Therefore, Thus the claims for following specific implementation mode are expressly incorporated in the specific implementation mode, wherein each claim itself All as a separate embodiment of the present invention.

It should be noted that the present invention will be described rather than limits the invention for above-described embodiment, and ability Field technique personnel can design alternative embodiment without departing from the scope of the appended claims.In the claims, Any reference mark between bracket should not be configured to limitations on claims.Word "comprising" does not exclude the presence of not Element or step listed in the claims.Word "a" or "an" before element does not exclude the presence of multiple such Element.The present invention can be by means of including the hardware of several different elements and being come by means of properly programmed computer real It is existing.In the unit claims listing several devices, several in these devices can be by the same hardware branch To embody.The use of word first, second, and third does not indicate that any sequence.These words can be explained and be run after fame Claim.

So far, although those skilled in the art will appreciate that present invention has been shown and described in detail herein multiple shows Example property embodiment still without departing from the spirit and scope of the present invention, still can according to the present disclosure directly Determine or derive many other variations or modifications consistent with the principles of the invention.Therefore, the scope of the present invention is understood that and recognizes It is set to and covers other all these variations or modifications.

Claims (10)

1. a kind of biological characteristic 3D 4 D data recognition methods based on infrared photography, which is characterized in that include the following steps：

S01. biological information is acquired,

Using several biometric images of infrared camera and color camera acquisition organism within given time, according to described more Width biometric image builds four dimension modules of biological characteristic, to realize that the biological characteristic 3D 4 D datas of the organism are adopted Collection；

S02. biological characteristic 4 D data is stored,

Scanning or typing are with the identity information (I1, I2 ... In) of organism, using the identity information (I1, I2 ... In) as identification Mark is associated storage to collected biological characteristic 3D 4 D datas, and formation includes a plurality of biological characteristic 3D 4 D datas The database of (D1, D2 ... Dn)；

S03. the identification of target organism,

Acquire the biological characteristic 3D 4 D datas (T1, T2 ... Tn) of target organism, and target organism described in scanning or typing Identity information (I1, I2 ... In), found in the database by the identity information (I1, I2 ... In) of the target organism The biological characteristic 3D 4 D datas (D1, D2 ... Dn) of storage, by the biological characteristic 3D 4 D datas of the target organism (T1, T2 ... Tn) it is compared respectively with the biological characteristic 3D 4 D datas (D1, D2 ... Dn) stored in the corresponding database, with Identify the identity of target organism.

2. according to the method described in claim 1, it is characterized in that, the color camera is zoom color camera, step S01 is also Including：

The collected 2D coloured images of one or more zoom color camera are pre-processed, the 2D high of target organism is obtained Clear color image；

The collected infrared image of depth infrared camera is pre-processed, the depth infrared number of the target organism is obtained According to, wherein the depth infrared data include the depth dimensions data of the target organism；

According to the depth infrared data of the target organism, obtain each composition point of the target organism to timing Interior spatial point cloud information；

The 2D high clear colorfuls picture is carried out being registrated fusion with the spatial point cloud information；

Be registrated result data, the Yi Jisuo that fusion obtains according to the 2D high clear colorfuls picture and the spatial point cloud information The calibration information for stating zoom color camera and the depth infrared camera, obtains the 4 D data of the target organism.

3. according to the method described in claim 2, it is characterized in that, obtaining the 4 D data step of the target organism into one Step includes：

By the depth infrared data transmission of several target organisms to image processor GPU and central processor CPU Processing unit；The depth infrared data information of several target organisms is assigned in the block block of GPU and is transported It calculates, and combines centralized dispatching and the distribution function of CPU, calculate the respective characteristic point of several described biometric images.

4. according to the method described in claim 3, wherein, carrying out pretreatment to the 2D coloured images includes：

The 2D coloured images are split, by the image-region and the back of the body of the target organism in the 2D coloured images Scene area is split；

The image-region that the target organism is obtained to segmentation carries out image enhancement processing, obtains the 2D of the target organism High clear colorful picture；Wherein, described image enhancing processing includes at least one of：At automatic white balance processing, automatic exposure Reason, auto-focusing processing and the processing of image deformity correction.

5. according to the method described in claim 3, wherein, pre-processed to the collected infrared image of depth infrared camera, Including：

The infrared image is split, by the image-region and background area of the target organism in the infrared image Domain is split；

The infrared matrix abnormal pigmentary deposit on the skin information noise filtering of image-region progress to the target organism that segmentation obtains；

The 3D dimension datas of the target organism are obtained from the image-region of the filtered target organism.

6. according to claim 2 to 5 any one of them method, wherein to the 2D high clear colorfuls picture and the spatial point Cloud information carries out registration fusion, including：

According to the 3D dimension datas of each composition point in the spatial point cloud information, TOF inverse transformations are carried out, obtain the target life The structure light depth image of object；

Gaussian filtering is carried out respectively to the 2D high clear colorfuls picture and the structure light depth image；

Respectively the target is extracted from the 2D high clear colorfuls picture and the structure light depth image after gaussian filtering The characteristic of organism determines the common characteristic part of the 2D high clear colorfuls picture and the structure light depth image；

In the common characteristic part, the corresponding points of the 2D high clear colorfuls picture and the structure light depth image are determined；

According to coordinate of the corresponding points in the 2D high clear colorfuls picture and the structure light depth image, cutd open based on triangle Method determines the coordinate conversion relation of the 2D high clear colorfuls picture and the structure light depth image；

According to the coordinate conversion relation, the mesh in the 2D high clear colorfuls picture and the structure light depth image is completed Mark the registration fusion of each characteristic of organism.

7. according to claim 2 to 5 any one of them method, wherein according to the 2D high clear colorfuls picture and the space Point cloud information carries out the mark of result data and the zoom color camera and the depth infrared camera that registration fusion obtains Determine information, obtains the 3D data of the target organism, including：

Be registrated result data, the Yi Jisuo that fusion obtains according to the 2D high clear colorfuls picture and the spatial point cloud information The calibration information for stating zoom color camera and the depth infrared camera is divided in each characteristic of the target organism Multiple sampled points are not chosen, and calculate the multiple sampled point within given time in the coordinate of three dimensions, based on described more A sampled point obtains the 4 D data of the target organism in the coordinate of three dimensions.

8. according to claim 2 to 5 any one of them method, wherein after obtaining the 3D data of the target organism, The method further includes：

Four-dimensional modeling is carried out according to 3D data of the target organism within given time, and four dimension modules are sent to display Device is shown；The target organism includes：Head, face or the hand of human body.

9. according to the method described in claim 1, it is characterized in that, when the step S03 is to the identification of target organism, Using temmoku point cloud matching identification method to the biological characteristic 3D 4 D datas (T1, T2 ... Tn) of the target organism and the number It is compared according to the biological characteristic 3D 4 D datas (D1, D2 ... Dn) stored in library；The temmoku point cloud matching identification method includes Following steps：

S301. characteristic point is fitted；

S302. curved surface entirety best fit；

S303. similarity calculation；The temmoku point cloud matching identification method comprises the following specific steps that：

Characteristic point fitting is carried out using based on the directly matched method in spatial domain, in the corresponding rigid region of two clouds, is chosen Three and features above point conduct fitting key point, pass through coordinate transform, directly carry out characteristic point Corresponding matching；

After characteristic point Corresponding matching, the alignment of data of the point cloud after whole curved surface best fit；

Similarity calculation is carried out using least square method.

10. a kind of biological characteristic 3D 4 D data identifying systems based on infrared photography, which is characterized in that including following device：

Collecting biological feature information device, for acquiring several biometric images of organism within given time, and according to Four dimension modules of several biometric images structure biological characteristic, to realize tetra- dimensions of biological characteristic 3D of the organism According to acquisition；

Biological characteristic 4 D data storage device, for scanning or the identity information of typing organism (I1, I2 ... In), with described Identity information (I1, I2 ... In) is associated storage as distinguishing mark to collected biological characteristic 3D 4 D datas, is formed Include the database of a plurality of biological characteristic 3D 4 D datas (D1, D2 ... Dn)；

The identity recognition device of target organism, for identity information (I1, I2 ... according to scanning or the target organism of typing In the biological characteristic 3D 4 D datas (D1, D2 ... Dn) stored in the database) are found, and by the life of the target organism Object feature 3D 4 D datas (T1, T2 ... Tn) respectively with the biological characteristic 3D 4 D datas that are stored in the corresponding database (D1, D2 ... Dn) is compared, to identify the identity of target organism；The collecting biological feature information device includes：

First preprocessing module, for being pre-processed to the collected 2D coloured images of one or more zoom color camera, Obtain the 2D high clear colorful pictures of target organism；

Second preprocessing module obtains the target for being pre-processed to the collected infrared image of depth infrared camera The depth infrared data of organism, wherein the depth infrared data include the depth dimensions data of the target organism；

Point cloud generation module, for the depth infrared data according to the target organism, the progress to the target organism Sampling, obtains the spatial point cloud information of the target organism；

Registration module, for carrying out being registrated fusion with the spatial point cloud information to the 2D high clear colorfuls picture；

3D data acquisition modules, for be registrated merging with the spatial point cloud information according to the 2D high clear colorfuls picture The calibration information of the result data and the zoom color camera and the depth infrared camera that arrive obtains the target life 3D data of the object within given time；First preprocessing module in the following way carries out the 2D coloured images pre- Processing：

The 2D coloured images are split, by the image-region and the back of the body of the target organism in the 2D coloured images Scene area is split；

The image-region that the target organism is obtained to segmentation carries out image enhancement processing, obtains the 2D of the target organism High clear colorful picture；Wherein, described image enhancing processing includes at least one of：At automatic white balance processing, automatic exposure Reason, auto-focusing processing and the processing of image deformity correction；Second preprocessing module is in the following way to depth infrared The collected infrared image of camera is pre-processed：

The infrared image is split, by the image-region and background area of the target organism in the infrared image Domain is split；

The infrared matrix abnormal pigmentary deposit on the skin information noise filtering of image-region progress to the target organism that segmentation obtains；

The 3D dimension datas of the target organism are obtained from the image-region of the filtered target organism；It is described to match Quasi-mode block carries out being registrated fusion to the 2D high clear colorfuls picture with the spatial point cloud information in the following way：

According to the 3D dimension datas of each sampled point in the spatial point cloud information, TOF inverse transformations are carried out, obtain the target life The structure light depth image of object；

Gaussian filtering is carried out respectively to the 2D high clear colorfuls picture and the structure light depth image；

Respectively the target is extracted from the 2D high clear colorfuls picture and the structure light depth image after gaussian filtering The characteristic of organism is based on triangulation, determines the 2D high clear colorfuls picture and the structure light depth image Shared image-region；

In the shared image-region, the corresponding points of the 2D high clear colorfuls picture and the structure light depth image are determined；

According to coordinate of the corresponding points in the 2D high clear colorfuls picture and the structure light depth image, the 2D is determined The coordinate conversion relation of high clear colorful picture and the structure light depth image；

According to the coordinate conversion relation, the mesh in the 2D high clear colorfuls picture and the structure light depth image is completed Mark the registration fusion of each characteristic of organism；The 3D data acquisition modules obtain the target life in the following way The 3D data of object：

According to the registration result of the 2D high clear colorfuls picture and the spatial point cloud information and the zoom color camera and The calibration information of the depth infrared camera chooses multiple samplings respectively in each characteristic of the target organism Point, and the coordinate of three dimensions of the multiple sampled point within given time is calculated, based on the multiple sampled point given The coordinate of three dimensions in time obtains the 4 D data of the target organism；Further include：Four-dimensional model modeling module is used It is reconstructed according to 3D data of the target organism within given time, and four dimension modules is sent to display and are shown Show.