CN109241908A - Face identification method and relevant apparatus - Google Patents
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Abstract
The embodiment of the present application provides a kind of face identification method and relevant apparatus, which comprises under noctovision environment, passes through the infrared face image that infrared camera obtains target user；The infrared face image is analyzed, target human face region and target environment parameter are obtained；Focusing position is determined according to the target human face region, and determines target acquisition parameters according to the target environment parameter；It is shot according to the focusing position, target acquisition parameters control visible image capturing head, obtains target facial image；The target facial image is matched with default face template；In the target facial image and the default face template successful match, it is unlocked operation.The acquisition parameters for adjusting visible image capturing head according to infrared camera by the embodiment of the present application, obtain the preferable visible light facial image of quality, are conducive to promote face identification rate.
Description
Technical field
This application involves technical field of image processing, and in particular to a kind of face identification method and relevant apparatus.
Background technique
With electronic technology fast development, electronic equipment (such as mobile phone, tablet computer) increasingly penetrates into user's life,
The convenience in life and work, especially face recognition technology are brought to user, recognition of face is increasingly closed by enterprise
Note, for example, face unlocks, face payment, just like, recognition of face have become a part in user's life, still, in complicated ring
Under border (for example, noctovision, exposure environment), then recognition of face efficiency can be reduced, therefore, how to be promoted under noctovision environment, is mentioned
The problem of rising face identification rate is urgently to be resolved.
Summary of the invention
The embodiment of the present application provides a kind of face identification method and relevant apparatus, can under face noctovision environment,
Promote face identification rate.
In a first aspect, the embodiment of the present application provides a kind of face identification method, comprising:
Under noctovision environment, the infrared face image of target user is obtained by infrared camera；
The infrared face image is analyzed, target human face region and target environment parameter are obtained；
Focusing position is determined according to the target human face region, and determines that target is shot according to the target environment parameter
Parameter；
It is shot according to the focusing position, target acquisition parameters control visible image capturing head, obtains target person
Face image；
The target facial image is matched with default face template；
In the target facial image and the default face template successful match, it is unlocked operation.
Second aspect, the embodiment of the present application provide a kind of face identification device, comprising:
Acquiring unit, for obtaining the infrared face image of target user by infrared camera under noctovision environment；
Analytical unit obtains target human face region and target environment ginseng for analyzing the infrared face image
Number；
Determination unit for determining focusing position according to the target human face region, and is joined according to the target environment
Number determines target acquisition parameters；
Shooting unit, for being clapped according to the focusing position, target acquisition parameters control visible image capturing head
It takes the photograph, obtains target facial image；
Matching unit, for matching the target facial image with default face template；
Unlocking unit, for being unlocked in the target facial image and the default face template successful match
Operation.
The third aspect, the embodiment of the present application provide a kind of face identification device, including processor, memory and one or
Multiple programs, wherein said one or multiple programs are stored in above-mentioned memory, and are configured to be held by above-mentioned processor
Row, above procedure are included the steps that for executing the instruction in the embodiment of the present application first aspect.
Fourth aspect, the embodiment of the present application provide a kind of computer readable storage medium, wherein above-mentioned computer-readable
Storage medium storage is used for the computer program of electronic data interchange, wherein above-mentioned computer program executes computer such as
Step some or all of described in the embodiment of the present application first aspect.
5th aspect, the embodiment of the present application provide a kind of computer program product, wherein above-mentioned computer program product
Non-transient computer readable storage medium including storing computer program, above-mentioned computer program are operable to make to calculate
Machine executes the step some or all of as described in the embodiment of the present application first aspect.The computer program product can be one
A software installation packet.
Implement the embodiment of the present application, has the following beneficial effects:
By face identification method described in the embodiment of the present application and relevant apparatus, under noctovision environment, by red
Outer camera obtains the infrared face image of target user, analyzes infrared face image, obtain target human face region and
Target environment parameter determines focusing position according to target human face region, and determines target shooting ginseng according to target environment parameter
Number is shot according to focusing position, target acquisition parameters control visible image capturing head, target facial image is obtained, by target
Facial image is matched with default face template, in target facial image and default face template successful match, is solved
Lock operation, thus, the acquisition parameters of visible image capturing head are adjusted according to infrared camera, obtain the preferable visible light face of quality
Image is conducive to promote face identification rate.
Detailed description of the invention
In order to more clearly explain the technical solutions in the embodiments of the present application, make required in being described below to embodiment
Attached drawing is briefly described, it should be apparent that, the accompanying drawings in the following description is some embodiments of the present application, for ability
For the those of ordinary skill of domain, without creative efforts, it can also be obtained according to these attached drawings other attached
Figure.
Fig. 1 is a kind of embodiment flow diagram of face identification method provided by the embodiments of the present application；
Fig. 2 is a kind of another embodiment flow diagram of face identification method provided by the embodiments of the present application；
Fig. 3 A is a kind of example structure schematic diagram of face identification device provided by the embodiments of the present application；
Fig. 3 B is a kind of another example structure schematic diagram of face identification device provided by the embodiments of the present application；
Fig. 4 is the example structure schematic diagram of a kind of electronic equipment provided by the embodiments of the present application；
Fig. 5 is the example structure schematic diagram of a kind of electronic equipment provided by the embodiments of the present application.
Specific embodiment
Below in conjunction with the attached drawing in the embodiment of the present application, technical solutions in the embodiments of the present application carries out clear, complete
Site preparation description, it is clear that described embodiment is some embodiments of the present application, instead of all the embodiments.Based on this Shen
Please in embodiment, every other implementation obtained by those of ordinary skill in the art without making creative efforts
Example, shall fall in the protection scope of this application.
The description and claims of this application and term " first ", " second ", " third " and " in the attached drawing
Four " etc. are not use to describe a particular order for distinguishing different objects.In addition, term " includes " and " having " and it
Any deformation, it is intended that cover and non-exclusive include.Such as it contains the process, method of a series of steps or units, be
System, product or equipment are not limited to listed step or unit, but optionally further comprising the step of not listing or list
Member, or optionally further comprising other step or units intrinsic for these process, methods, product or equipment.
Referenced herein " embodiment " is it is meant that a particular feature, structure, or characteristic described can wrap in conjunction with the embodiments
It is contained at least one embodiment of the application.It is identical that each position in the description shows that the phrase might not be each meant
Embodiment, nor the independent or alternative embodiment with other embodiments mutual exclusion.Those skilled in the art explicitly and
Implicitly understand, embodiment described herein can be combined with other embodiments.
Face identification device described in the embodiment of the present application may include smart phone (such as Android phone, iOS hand
Machine, Windows Phone mobile phone etc.), tablet computer, palm PC, laptop, mobile internet device (MID,
Mobile Internet Devices) or wearable device (for example, bluetooth headset, VR equipment or IR equipment) etc., it is above-mentioned only
It is citing, and it is non exhaustive, including but not limited to above-mentioned face identification device.
Referring to Fig. 1, being a kind of embodiment flow diagram of face identification method provided by the embodiments of the present application.This reality
Apply face identification method described in example, comprising the following steps:
101, under noctovision environment, the infrared face image of target user is obtained by infrared camera.
Wherein, in the embodiment of the present application, noctovision environment refers to that ambient brightness is lower than the environment of preset threshold, preset threshold
It can be by system default, alternatively, user's self-setting.Under noctovision environment, since ambient light is less, electronics is set
The standby infrared face image that target user can be obtained by infrared camera.Infrared face image is the image for including face.It is red
Outer camera due to by temperature imaging, even if still may be implemented to be imaged in the case where dull thread.
102, the infrared face image is analyzed, obtains target human face region and target environment parameter.
Wherein, in the embodiment of the present application, electronic equipment can be analyzed infrared face image, obtain target face area
Domain and target environment parameter, wherein environmental parameter can be following at least one: environmental light brightness, environment colour temperature, environment
Temperature, ambient humidity, environment electromagnetics interference strength etc., it is not limited here.
Optionally, above-mentioned steps 102 analyze the infrared face image, obtain target human face region and target
Environmental parameter, it may include following steps:
21, image segmentation is carried out to the infrared face image, obtains human face region；
22, the target contrast of the human face region is obtained；
23, according to the mapping relations between preset contrast and environmental parameter, determine that the target contrast is corresponding
Target environment parameter.
Wherein, electronic equipment can carry out image segmentation to infrared face image, obtain human face region, specifically, face point
Cutting algorithm can be with are as follows: the image segmentation algorithm based on region, alternatively, the image segmentation algorithm based on edge, it is not limited here.
Electronic equipment can also calculate the contrast of human face region, obtain target contrast, under different contrasts, corresponding environment
Parameter is different, and the mapping relations between preset contrast and environmental parameter therefore, in electronic equipment can be stored in advance, into
And the corresponding target environment parameter of target contrast is determined according to the mapping relations, in this way, can be by infrared face image
It is analyzed, to obtain environmental parameter.
103, focusing position is determined according to the target human face region, and determine target according to the target environment parameter
Acquisition parameters.
Wherein, electronic equipment can determine focusing position according to target human face region, for example, can be by target human face region
Geometric center as focusing position.Acquisition parameters may include following at least one: focal length, exposure time, sensitivity, aperture
Size, light filling parameter of light compensating lamp etc., are not limited thereto, and in the embodiment of the present application, electronic equipment can also include light filling
Lamp, light filling parameter can be following at least one: operating current, operating voltage, operating power, light filling duration, light filling direction etc.
Deng it is not limited here.The mapping relations between environmental parameter and acquisition parameters can be stored in advance in electronic equipment, in turn, can
To determine the corresponding target acquisition parameters of target environment parameter according to the mapping relations, and clapped according to target acquisition parameters
According to.A kind of mapping relations between environmental parameter and acquisition parameters are provided as follows, specific as follows:
| Environmental parameter | Acquisition parameters |
| Environmental parameter 1 | Acquisition parameters 1 |
| Environmental parameter 2 | Acquisition parameters 2 |
| … | … |
| Environmental parameter n | Acquisition parameters n |
104, it is shot according to the focusing position, target acquisition parameters control visible image capturing head, obtains mesh
Mark facial image.
Wherein, electronic equipment can be obtained according to focusing position, the control visible image capturing head shooting of target acquisition parameters
Target facial image.In the embodiment of the present application, electronic equipment may include infrared camera and visible image capturing head, infrared camera
It can be registrated with visible image capturing head, i.e., infrared camera is as the field range of visible image capturing head.
105, the target facial image is matched with default face template.
Wherein, electronic equipment can match target facial image with default face template, in the two successful match
When, then unlock operation can be executed, if unlock failure, can resurvey facial image.
Optionally, above-mentioned steps 105 match the target facial image with default face template, it may include such as
Lower step:
51, image quality evaluation is carried out to the target facial image, obtains objective image quality evaluation of estimate；
52, according to the mapping relations between preset image quality evaluation values and matching threshold, the target image is determined
Quality evaluation is worth corresponding object matching threshold value；
53, contours extract is carried out to the target facial image, obtains the first circumference；
54, feature point extraction is carried out to the target facial image, obtains fisrt feature point set；
55, first circumference is matched with the second circumference of the default face template, obtains
One matching value；
56, the fisrt feature point set is matched with the second feature point set of the default face template, obtains
Two matching values；
57, object matching value is determined according to first matching value, second matching value；
58, the object matching value be greater than the object matching threshold value when, confirm the target facial image with it is described
Default face template successful match.
Wherein, default face template can be stored in advance in electronic equipment, in face recognition process, success or not very great Cheng
Quality of human face image is depended on degree, therefore, in the embodiment of the present application, then it is contemplated that Dynamic Matching threshold value, even high-quality,
Then matching threshold then can be improved, of poor quality, then matching threshold can reduce, since under noctovision environment, the image of shooting is not
Must picture quality it is good, therefore, can suitably adjust matching threshold.It can store preset image quality evaluation values in electronic equipment
Mapping relations between matching threshold determine the corresponding target of objective image quality evaluation of estimate according to the mapping relations in turn
Matching threshold, on this basis, electronic equipment can carry out contours extract to target facial image, obtain the first circumference, right
Target facial image carries out feature point extraction, obtains fisrt feature point set, by the of the first circumference and default face template
Two circumferences are matched, and the first matching value is obtained, by the second feature point set of fisrt feature point set and default face template
It is matched, obtains the second matching value, in turn, object matching value is determined according to the first matching value, the second matching value, for example, electric
The mapping relations between environmental parameter and weighted value pair can be stored in advance in sub- equipment, obtain the first matching value corresponding first
Weight coefficient and corresponding second weight coefficient of the second matching value, object matching value=first the first weight coefficient of matching value *
+ the second the second weight coefficient of matching value *, finally, confirming target face when object matching value is greater than the object matching threshold value
Image and the default face template successful match, otherwise, confirmation recognition of face failure, in this way, dynamic regulation face matched
Journey is conducive to promote recognition of face efficiency for specific environment.
In addition, the algorithm of contours extract can be following at least one: Hough transformation, canny operator etc. are not done herein
Limit, the algorithm of feature point extraction can be following at least one: Harris angle point, scale invariant feature extract transformation (scale
Invariant feature transform, SIFT) etc., it is not limited here.
Optionally, above-mentioned steps 51 carry out image quality evaluation to the target facial image, obtain objective image quality
Evaluation of estimate can be implemented as follows:
Image quality evaluation is carried out to target facial image using at least one image quality evaluation index, obtains target figure
Image quality amount evaluation of estimate.
Wherein, image quality evaluation index may include, but are not limited to: average gray, mean square deviation, entropy, edge conservation degree,
Signal-to-noise ratio etc..The image quality evaluation values that may be defined as are bigger, then picture quality is better.
It should be noted that there is certain limitation when due to evaluating using single evaluation index picture quality
Property, therefore, multiple images quality evaluation index, which can be used, evaluates picture quality, certainly, evaluates picture quality
When, not image quality evaluation index is The more the better, because image quality evaluation index is more, the meter of image quality assessment process
Calculation complexity is higher, and also not necessarily image quality evaluation effect is better, therefore, in the situation more demanding to image quality evaluation
Under, 2~10 image quality evaluation indexs can be used, picture quality is evaluated.Specifically, image quality evaluation is chosen to refer to
Target number and which index, depending on specific implementation situation.Certainly, it also obtains and is commented in conjunction with specifically scene selection picture quality
Valence index carries out the image quality index that image quality evaluation selection is carried out under image quality evaluation and bright ring border under dark situation
It can be different.
Optionally, in the case where not high to image quality evaluation required precision, an image quality evaluation index can be used
It is evaluated, for example, carrying out image quality evaluation values to image to be processed with entropy, it is believed that entropy is bigger, then illustrates picture quality
It is better, on the contrary, entropy is smaller, then illustrate that picture quality is poorer.
Optionally, in the higher situation of image quality evaluation required precision, multiple images quality evaluation can be used
Index evaluates image to be evaluated, carries out image quality evaluation to image to be evaluated in multiple images quality evaluation index
When, the weight of each image quality evaluation index, can be obtained multiple images matter in settable multiple image quality evaluation index
Evaluation of estimate is measured, final image quality evaluation values, example can be obtained according to multiple image quality evaluation values and its corresponding weight
Such as, three image quality evaluation indexs are respectively as follows: A index, B index and C index, and the weight of A is a1, and the weight of B is a2, C's
Weight is a3, and when carrying out image quality evaluation to a certain image using A, B and C, the corresponding image quality evaluation values of A are b1, B
Corresponding image quality evaluation values are b2, and the corresponding image quality evaluation values of C are b3, then, last image quality evaluation values
=a1b1+a2b2+a3b3.Under normal conditions, image quality evaluation values are bigger, illustrate that picture quality is better.
106, in the target facial image and the default face template successful match, it is unlocked operation.
Wherein, unlock operation can be following at least one: enter homepage, into specified page, starting it is specified apply,
Delivery operation etc., it is not limited here.Electronic equipment in target facial image and when default face template successful match, then into
Row unlock operation, otherwise promotes unlock failure.
Wherein, between above-mentioned steps 104- step 105, can also include the following steps:
A1, the characteristic point distribution density for determining the target facial image；
A2, the characteristic point distribution density be less than pre-set density threshold value when, by the target facial image with it is described red
Outer facial image carries out image co-registration, obtains fusion facial image；
Then, above-mentioned steps 105 match the target facial image with default face template, can be according to such as lower section
Formula is implemented:
The fusion facial image is matched with the default face template.
Wherein, electronic equipment can carry out feature point extraction to target facial image, obtain feature point set, calculate characteristic point
The face area of characteristic point total number and target facial image that collection includes, characteristic point distribution density=characteristic point total number/
Face area.Above-mentioned pre-set density threshold value can be by user's self-setting or system default.It is less than in characteristic point distribution density
When pre-set density threshold value, then illustrate that target features of human face images is less, picture quality is poor, then can be by target facial image
Image co-registration is carried out with infrared face image, obtains fusion facial image, in turn, by fusion facial image and default face template
It is matched.
Optionally, the target facial image and the infrared face image are carried out image co-registration, obtained by above-mentioned steps A2
To fusion facial image, it may include following steps:
A21, the infrared face image is zoomed in and out into processing, obtains Infrared Targets facial image, the Infrared Targets
The size of facial image is consistent with the size of the target facial image；
A22, multi-resolution decomposition is carried out to the Infrared Targets facial image, obtains the first low frequency component image and second high
Frequency component image；
A23, the multi-resolution decomposition is carried out to the target facial image, obtains the second low frequency component image and second high
Frequency component image；
A24, according to the mapping relations between preset environmental parameter and the first weight, determine the Infrared Targets face figure
As corresponding first object weighted value；
A25, the corresponding second target weight value of the target facial image is calculated according to the first object weighted value；
A26, for the first low frequency component image, the second low frequency component image, the first object weighted value,
The second target weight value is weighted, and obtains target low frequency component image；
A27, taken for the first high fdrequency component image, the second high fdrequency component image absolute value take big principle into
Row operation obtains targeted high frequency component image；
A28, the target low frequency component image, the targeted high frequency component image are carried out and the multi-resolution decomposition pair
The inverse transformation answered obtains the fusion facial image.
Wherein, since infrared face image is possible to not of uniform size with target facial image, it can be to infrared face
Image zooms in and out processing, obtains Infrared Targets facial image, the size and target face figure of Infrared Targets facial image
The size of picture is consistent, and the multi-resolution decomposition algorithm that above-mentioned multi-resolution decomposition uses can be following at least one: profile wave
Transformation, non-down sampling contourlet transform, shearing wave conversion, pyramid transform etc., it is not limited here.In the specific implementation, electric
Sub- equipment can carry out multi-resolution decomposition to Infrared Targets facial image, obtain the first low frequency component image and the second high fdrequency component figure
Picture carries out multi-resolution decomposition to target facial image, obtains the second low frequency component image and the second high fdrequency component image.In addition,
The mapping relations between preset environmental parameter and the first weight can be stored in advance in electronic equipment, in turn, according to preset
Mapping relations between environmental parameter and the first weight determine the corresponding first object weighted value of Infrared Targets facial image, according to
The corresponding second target weight value of target facial image, the second target weight value=the first mesh of 1- are calculated according to first object weighted value
Mark weighted value, target low frequency component image=first low frequency component image * first object weighted value the+the second low frequency component image *
Second target weight value if targeted high frequency component image, then can be directed to the first high fdrequency component image, the second high fdrequency component figure
As taking absolute value that big principle is taken to carry out operation, targeted high frequency component image is obtained, by target low frequency component image, targeted high frequency
Component image carries out inverse transformation corresponding with multi-resolution decomposition, obtains fusion facial image.
It is obtained under noctovision environment by infrared camera by face identification method described in the embodiment of the present application
The infrared face image for taking target user, analyzes infrared face image, obtains target human face region and target environment ginseng
Number determines focusing position according to target human face region, and determines target acquisition parameters according to target environment parameter, according to focusing
Position, target acquisition parameters control visible image capturing head are shot, and target facial image are obtained, by target facial image and in advance
If face template is matched, in target facial image and default face template successful match, it is unlocked operation, thus,
The acquisition parameters that visible image capturing head is adjusted according to infrared camera, obtain the preferable visible light facial image of quality, are conducive to
Promote face identification rate.
Consistent with the abovely, referring to Fig. 2, for a kind of second implementation of face identification method provided by the embodiments of the present application
Example flow diagram.Face identification method as described in this embodiment, comprising the following steps:
201, under noctovision environment, the infrared face image of target user is obtained by infrared camera.
202, the infrared face image is analyzed, obtains target human face region and target environment parameter.
203, focusing position is determined according to the target human face region, and determine target according to the target environment parameter
Acquisition parameters.
204, it is shot according to the focusing position, target acquisition parameters control visible image capturing head, obtains mesh
Mark facial image.
205, the characteristic point distribution density of the target facial image is determined.
206, the characteristic point distribution density be less than pre-set density threshold value when, by the target facial image with it is described red
Outer facial image carries out image co-registration, obtains fusion facial image.
207, the fusion facial image is matched with default face template.
208, in the fusion facial image and the default face template successful match, it is unlocked operation.
Wherein, the specific descriptions of above-mentioned steps 201-208 are referred to accordingly retouching for face identification method described in Fig. 1
It states, details are not described herein.
It is obtained under noctovision environment by infrared camera by face identification method described in the embodiment of the present application
The infrared face image for taking target user, analyzes infrared face image, obtains target human face region and target environment ginseng
Number determines focusing position according to target human face region, and determines target acquisition parameters according to target environment parameter, according to focusing
Position, target acquisition parameters control visible image capturing head are shot, and are obtained target facial image, are determined target facial image
Characteristic point distribution density, when characteristic point distribution density is less than pre-set density threshold value, by target facial image and infrared face figure
As carrying out image co-registration, fusion facial image is obtained, fusion facial image is matched with default face template, in fusion people
When face image and default face template successful match, it is unlocked operation, thus, visible image capturing is adjusted according to infrared camera
The acquisition parameters of head, obtain the preferable visible light facial image of quality, are conducive to promote face identification rate.
Consistent with the abovely, specific as follows the following are the device for implementing above-mentioned face identification method:
Fig. 3 A is please referred to, is a kind of example structure schematic diagram of face identification device provided by the embodiments of the present application.This
Face identification device described in embodiment, comprising: acquiring unit 301, analytical unit 302, determination unit 303, shooting are single
Member 304, matching unit 305 and unlocking unit 306, specific as follows:
Acquiring unit 301, for obtaining the infrared face figure of target user by infrared camera under noctovision environment
Picture；
Analytical unit 302 obtains target human face region and target environment for analyzing the infrared face image
Parameter；
Determination unit 303, for determining focusing position according to the target human face region, and according to the target environment
Parameter determines target acquisition parameters；
Shooting unit 304, for being carried out according to the focusing position, target acquisition parameters control visible image capturing head
Shooting, obtains target facial image；
Matching unit 305, for matching the target facial image with default face template；
Unlocking unit 306, for being solved in the target facial image and the default face template successful match
Lock operation.
Optionally, the infrared face image is analyzed described, obtains target human face region and target environment ginseng
Number aspect, the analytical unit 302 are specifically used for:
Image segmentation is carried out to the infrared face image, obtains human face region；
Obtain the target contrast of the human face region；
According to the mapping relations between preset contrast and environmental parameter, the corresponding target of the target contrast is determined
Environmental parameter.
Optionally, it is described the target facial image is matched with default face template in terms of, the matching is single
Member 305 is specifically used for:
Image quality evaluation is carried out to the target facial image, obtains objective image quality evaluation of estimate；
According to the mapping relations between preset image quality evaluation values and matching threshold, the objective image quality is determined
The corresponding object matching threshold value of evaluation of estimate；
Contours extract is carried out to the target facial image, obtains the first circumference；
Feature point extraction is carried out to the target facial image, obtains fisrt feature point set；
First circumference is matched with the second circumference of the default face template, obtains first
With value；
The fisrt feature point set is matched with the second feature point set of the default face template, obtains second
With value；
Object matching value is determined according to first matching value, second matching value；
When the object matching value is greater than the object matching threshold value, confirm that the target facial image is preset with described
Face template successful match.
Optionally, such as Fig. 3 B, Fig. 3 B is the another modification structures of face identification device described in Fig. 3 A, with Fig. 3 A phase
Compare, can also include: image fusion unit 307, specific as follows:
The determination unit 303, also particularly useful for the characteristic point distribution density of the determination target facial image；
Described image integrated unit 307 is used for when the characteristic point distribution density is less than pre-set density threshold value, will be described
Target facial image and the infrared face image carry out image co-registration, obtain fusion facial image；
It is described the target facial image is matched with default face template in terms of, the matching unit 305 has
Body is used for:
The fusion facial image is matched with the default face template.
Optionally, the target facial image and the infrared face image are subjected to image co-registration described, are melted
In terms of closing facial image, the matching unit 305 is specifically used for:
The infrared face image is zoomed in and out into processing, obtains Infrared Targets facial image, the Infrared Targets face
The size of image is consistent with the size of the target facial image；
Multi-resolution decomposition is carried out to the Infrared Targets facial image, obtains the first low frequency component image and the second high frequency division
Spirogram picture；
The multi-resolution decomposition is carried out to the target facial image, obtains the second low frequency component image and the second high frequency division
Spirogram picture；
According to the mapping relations between preset environmental parameter and the first weight, the Infrared Targets facial image pair is determined
The first object weighted value answered；
The corresponding second target weight value of the target facial image is calculated according to the first object weighted value；
For the first low frequency component image, the second low frequency component image, the first object weighted value, described
Second target weight value is weighted, and obtains target low frequency component image；
Take absolute value that big principle is taken to be transported for the first high fdrequency component image, the second high fdrequency component image
It calculates, obtains targeted high frequency component image；
The target low frequency component image, the targeted high frequency component image are carried out corresponding with the multi-resolution decomposition
Inverse transformation obtains the fusion facial image.
It is obtained under noctovision environment by infrared camera by face identification device described in the embodiment of the present application
The infrared face image for taking target user, analyzes infrared face image, obtains target human face region and target environment ginseng
Number determines focusing position according to target human face region, and determines target acquisition parameters according to target environment parameter, according to focusing
Position, target acquisition parameters control visible image capturing head are shot, and target facial image are obtained, by target facial image and in advance
If face template is matched, in target facial image and default face template successful match, it is unlocked operation, thus,
The acquisition parameters that visible image capturing head is adjusted according to infrared camera, obtain the preferable visible light facial image of quality, are conducive to
Promote face identification rate.
Consistent with the abovely, referring to Fig. 4, the example structure for a kind of electronic equipment provided by the embodiments of the present application is shown
It is intended to.Electronic equipment as described in this embodiment, comprising: at least one input equipment 1000；At least one output equipment
2000；At least one processor 3000, such as CPU；With memory 4000, above-mentioned input equipment 1000, output equipment 2000, place
Reason device 3000 and memory 4000 are connected by bus 5000.
Wherein, above-mentioned input equipment 1000 concretely touch panel, physical button or mouse.
Above-mentioned output equipment 2000 concretely display screen.
Above-mentioned memory 4000 can be high speed RAM memory, can also be nonvolatile storage (non-volatile
), such as magnetic disk storage memory.Above-mentioned memory 4000 is used to store a set of program code, above-mentioned input equipment 1000, defeated
Equipment 2000 and processor 3000 are used to call the program code stored in memory 4000 out, perform the following operations:
Above-mentioned processor 3000, is used for:
Under noctovision environment, the infrared face image of target user is obtained by infrared camera；
The infrared face image is analyzed, target human face region and target environment parameter are obtained；
Focusing position is determined according to the target human face region, and determines that target is shot according to the target environment parameter
Parameter；
It is shot according to the focusing position, target acquisition parameters control visible image capturing head, obtains target person
Face image；
The target facial image is matched with default face template；
In the target facial image and the default face template successful match, it is unlocked operation.
Optionally, described that the infrared face image is analyzed, target human face region and target environment parameter are obtained,
The processor 3000 is specifically used for:
Image segmentation is carried out to the infrared face image, obtains human face region；
Obtain the target contrast of the human face region；
According to the mapping relations between preset contrast and environmental parameter, the corresponding target of the target contrast is determined
Environmental parameter.
Optionally, described to match the target facial image with default face template, the processor 3000 has
Body is used for:
Image quality evaluation is carried out to the target facial image, obtains objective image quality evaluation of estimate；
According to the mapping relations between preset image quality evaluation values and matching threshold, the objective image quality is determined
The corresponding object matching threshold value of evaluation of estimate；
Contours extract is carried out to the target facial image, obtains the first circumference；
Feature point extraction is carried out to the target facial image, obtains fisrt feature point set；
First circumference is matched with the second circumference of the default face template, obtains first
With value；
The fisrt feature point set is matched with the second feature point set of the default face template, obtains second
With value；
Object matching value is determined according to first matching value, second matching value；
When the object matching value is greater than the object matching threshold value, confirm that the target facial image is preset with described
Face template successful match.
Optionally, the processor 3000 also particularly useful for:
Determine the characteristic point distribution density of the target facial image；
When the characteristic point distribution density is less than pre-set density threshold value, by the target facial image and the infrared people
Face image carries out image co-registration, obtains fusion facial image；
It is described to match the target facial image with default face template, comprising:
The fusion facial image is matched with the default face template.
Optionally, described that the target facial image and the infrared face image are subjected to image co-registration, it is merged
Facial image, the processor 3000 are specifically used for:
The infrared face image is zoomed in and out into processing, obtains Infrared Targets facial image, the Infrared Targets face
The size of image is consistent with the size of the target facial image；
Multi-resolution decomposition is carried out to the Infrared Targets facial image, obtains the first low frequency component image and the second high frequency division
Spirogram picture；
The multi-resolution decomposition is carried out to the target facial image, obtains the second low frequency component image and the second high frequency division
Spirogram picture；
According to the mapping relations between preset environmental parameter and the first weight, the Infrared Targets facial image pair is determined
The first object weighted value answered；
The corresponding second target weight value of the target facial image is calculated according to the first object weighted value；
For the first low frequency component image, the second low frequency component image, the first object weighted value, described
Second target weight value is weighted, and obtains target low frequency component image；
Take absolute value that big principle is taken to be transported for the first high fdrequency component image, the second high fdrequency component image
It calculates, obtains targeted high frequency component image；
The target low frequency component image, the targeted high frequency component image are carried out corresponding with the multi-resolution decomposition
Inverse transformation obtains the fusion facial image.
The embodiment of the present application also provides a kind of electronic equipment, as shown in figure 5, for ease of description, illustrating only and this
Apply for the relevant part of embodiment, it is disclosed by specific technical details, please refer to the embodiment of the present application method part.The electronics is set
It include mobile phone, tablet computer, PDA (personal digital assistant, personal digital assistant), POS for that can be
Any terminal device such as (point of sales, point-of-sale terminal), vehicle-mounted computer, by taking electronic equipment is mobile phone as an example:
Fig. 5 shows the block diagram of the part-structure of mobile phone relevant to electronic equipment provided by the embodiments of the present application.Ginseng
Fig. 5 is examined, mobile phone includes: radio frequency (radio frequency, RF) circuit 910, memory 920, input unit 930, sensor
950, voicefrequency circuit 960, Wireless Fidelity (wireless fidelity, WiFi) module 970, processor 980 and power supply
990 equal components.It will be understood by those skilled in the art that handset structure shown in Fig. 5 does not constitute the restriction to mobile phone, it can
To include perhaps combining certain components or different component layouts than illustrating more or fewer components.
It is specifically introduced below with reference to each component parts of the Fig. 5 to mobile phone:
Input unit 930 can be used for receiving the number or character information of input, and generate with the user setting of mobile phone with
And the related key signals input of function control.Specifically, input unit 930 may include touching display screen 933, face identification device
931 and other input equipments 932.Face identification device 931 can be camera, for example, infrared camera, it is seen that light camera shooting
Head or dual camera etc..Input unit 930 can also include other input equipments 932.Specifically, other input equipments
932 can include but is not limited to physical button, function key (such as volume control button, switch key etc.), trace ball, mouse,
One of operating stick etc. is a variety of.
Wherein, the processor 980, for executing following steps:
Under noctovision environment, the infrared face image of target user is obtained by infrared camera；
The infrared face image is analyzed, target human face region and target environment parameter are obtained；
Focusing position is determined according to the target human face region, and determines that target is shot according to the target environment parameter
Parameter；
It is shot according to the focusing position, target acquisition parameters control visible image capturing head, obtains target person
Face image；
The target facial image is matched with default face template；
In the target facial image and the default face template successful match, it is unlocked operation.
Processor 980 is the control centre of mobile phone, using the various pieces of various interfaces and connection whole mobile phone, is led to
It crosses operation or executes the software program and/or module being stored in memory 920, and call and be stored in memory 920
Data execute the various functions and processing data of mobile phone, to carry out integral monitoring to mobile phone.Optionally, processor 980 can wrap
Include one or more processing units；Preferably, processor 980 can integrated processor and modem processor, wherein processing
The main processing operation system of device, user interface and application program etc., modem processor mainly handles wireless communication.It can manage
Solution, above-mentioned modem processor can not also be integrated into processor 980.
In addition, memory 920 may include high-speed random access memory, it can also include nonvolatile memory, example
Such as at least one disk memory, flush memory device or other volatile solid-state parts.
RF circuit 910 can be used for sending and receiving for information.In general, RF circuit 910 includes but is not limited to antenna, at least one
A amplifier, transceiver, coupler, low-noise amplifier (low noise amplifier, LNA), duplexer etc..This
Outside, RF circuit 910 can also be communicated with network and other equipment by wireless communication.Above-mentioned wireless communication can be used any logical
Beacon standard or agreement, including but not limited to global system for mobile communications (global system of mobile
Communication, GSM), general packet radio service (general packet radio service, GPRS), code point
Multiple access (code division multiple access, CDMA), wideband code division multiple access (wideband code division
Multiple access, WCDMA), long term evolution (long term evolution, LTE), Email, short message service
(short messaging service, SMS) etc..
Mobile phone may also include at least one sensor 950, such as optical sensor, motion sensor and other sensors.
Specifically, optical sensor may include ambient light sensor and proximity sensor, wherein ambient light sensor can be according to ambient light
Light and shade adjust the brightness of touching display screen, proximity sensor can when mobile phone is moved in one's ear, close touching display screen and/
Or backlight.As a kind of motion sensor, accelerometer sensor can detect (generally three axis) acceleration in all directions
Size can detect that size and the direction of gravity when static, can be used to identify mobile phone posture application (such as horizontal/vertical screen switching,
Dependent game, magnetometer pose calibrating), Vibration identification correlation function (such as pedometer, tap) etc.；It can also configure as mobile phone
The other sensors such as gyroscope, barometer, hygrometer, thermometer, infrared sensor, details are not described herein.
Voicefrequency circuit 960, loudspeaker 961, microphone 962 can provide the audio interface between user and mobile phone.Audio-frequency electric
Electric signal after the audio data received conversion can be transferred to loudspeaker 961, be converted to sound by loudspeaker 961 by road 960
Signal plays；On the other hand, the voice signal of collection is converted to electric signal by microphone 962, is turned after being received by voicefrequency circuit 960
Audio data is changed to, then by after the processing of audio data playback process device 980, through RF circuit 910 to be sent to such as the other hand
Machine, or audio data is played to memory 920 to be further processed.
WiFi belongs to short range wireless transmission technology, and mobile phone can help user's transceiver electronics postal by WiFi module 970
Part, browsing webpage and access streaming video etc., it provides wireless broadband internet access for user.Although Fig. 5 is shown
WiFi module 970, but it is understood that, and it is not belonging to must be configured into for mobile phone, it can according to need do not changing completely
Become in the range of the essence of invention and omits.
Mobile phone further includes the power supply 990 (such as battery) powered to all parts, it is preferred that power supply can pass through power supply pipe
Reason system and processor 980 are logically contiguous, to realize management charging, electric discharge and power managed by power-supply management system
Etc. functions.
Although being not shown, mobile phone can also include camera, bluetooth module etc., and details are not described herein.
In earlier figures 1, embodiment shown in Fig. 2, each step method process can be realized based on the structure of the mobile phone.
In earlier figures 3A, Fig. 3 B, embodiment shown in Fig. 4, each unit function can be realized based on the structure of the mobile phone.
The embodiment of the present application also provides a kind of computer storage medium, wherein computer storage medium storage is for electricity
The computer program of subdata exchange, the computer program make computer execute any as recorded in above method embodiment
Some or all of method step.
The embodiment of the present application also provides a kind of computer program product, and above-mentioned computer program product includes storing calculating
The non-transient computer readable storage medium of machine program, above-mentioned computer program are operable to that computer is made to execute such as above-mentioned side
Some or all of either record method step in method embodiment.The computer program product can be a software installation
Packet.
Although the application is described in conjunction with each embodiment herein, however, implementing the application claimed
In the process, those skilled in the art are by checking the attached drawing, disclosure and the appended claims, it will be appreciated that and it is real
Other variations of the existing open embodiment.In the claims, " comprising " (comprising) word is not excluded for other compositions
Part or step, "a" or "an" are not excluded for multiple situations.Claim may be implemented in single processor or other units
In several functions enumerating.Mutually different has been recited in mutually different dependent certain measures, it is not intended that these are arranged
It applies to combine and generates good effect.
It will be understood by those skilled in the art that embodiments herein can provide as method, apparatus (equipment) or computer journey
Sequence product.Therefore, complete hardware embodiment, complete software embodiment or combining software and hardware aspects can be used in the application
The form of embodiment.Moreover, it wherein includes the calculating of computer usable program code that the application, which can be used in one or more,
The computer program implemented in machine usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of product.Computer program is stored/distributed in suitable medium, is provided together with other hardware or as hardware
A part can also use other distribution forms, such as pass through the wired or wireless telecommunication system of Internet or other.
The application be referring to the embodiment of the present application method, apparatus (equipment) and computer program product flow chart with/
Or block diagram describes.It should be understood that each process that can be realized by computer program instructions in flowchart and/or the block diagram and/
Or the combination of the process and/or box in box and flowchart and/or the block diagram.It can provide these computer program instructions
To general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices processor to generate one
A machine so that by the instruction that the processor of computer or other programmable data processing devices executes generate for realizing
The device for the function of being specified in one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Although the application is described in conjunction with specific features and embodiment, it is clear that, do not departing from this Shen
In the case where spirit and scope please, it can be carry out various modifications and is combined.Correspondingly, the specification and drawings are only institute
The exemplary illustration for the application that attached claim is defined, and be considered as covered within the scope of the application any and all and repair
Change, change, combining or equivalent.Obviously, those skilled in the art the application can be carried out various modification and variations without
It is detached from spirit and scope.If in this way, these modifications and variations of the application belong to the claim of this application and its
Within the scope of equivalent technologies, then the application is also intended to include these modifications and variations.
Claims (10)
1. a kind of face identification method characterized by comprising
Under noctovision environment, the infrared face image of target user is obtained by infrared camera；
The infrared face image is analyzed, target human face region and target environment parameter are obtained；
Focusing position is determined according to the target human face region, and determines target shooting ginseng according to the target environment parameter
Number；
It is shot according to the focusing position, target acquisition parameters control visible image capturing head, obtains target face figure
Picture；
The target facial image is matched with default face template；
In the target facial image and the default face template successful match, it is unlocked operation.
2. being obtained the method according to claim 1, wherein described analyze the infrared face image
Target human face region and target environment parameter, comprising:
Image segmentation is carried out to the infrared face image, obtains human face region；
Obtain the target contrast of the human face region；
According to the mapping relations between preset contrast and environmental parameter, the corresponding target environment of the target contrast is determined
Parameter.
3. method according to claim 1 or 2, which is characterized in that described by the target facial image and default face
Template is matched, comprising:
Image quality evaluation is carried out to the target facial image, obtains objective image quality evaluation of estimate；
According to the mapping relations between preset image quality evaluation values and matching threshold, the objective image quality evaluation is determined
It is worth corresponding object matching threshold value；
Contours extract is carried out to the target facial image, obtains the first circumference；
Feature point extraction is carried out to the target facial image, obtains fisrt feature point set；
First circumference is matched with the second circumference of the default face template, obtains the first matching
Value；
The fisrt feature point set is matched with the second feature point set of the default face template, obtains the second matching
Value；
Object matching value is determined according to first matching value, second matching value；
When the object matching value is greater than the object matching threshold value, the target facial image and the default face are confirmed
Template matching success.
4. method according to claim 1-3, which is characterized in that the method also includes:
Determine the characteristic point distribution density of the target facial image；
When the characteristic point distribution density is less than pre-set density threshold value, by the target facial image and the infrared face figure
As carrying out image co-registration, fusion facial image is obtained；
It is described to match the target facial image with default face template, comprising:
The fusion facial image is matched with the default face template.
5. according to the method described in claim 4, it is characterized in that, described by the target facial image and the infrared face
Image carries out image co-registration, obtains fusion facial image, comprising:
The infrared face image is zoomed in and out into processing, obtains Infrared Targets facial image, the Infrared Targets facial image
Size it is consistent with the size of the target facial image；
Multi-resolution decomposition is carried out to the Infrared Targets facial image, obtains the first low frequency component image and the second high fdrequency component figure
Picture；
The multi-resolution decomposition is carried out to the target facial image, obtains the second low frequency component image and the second high fdrequency component figure
Picture；
According to the mapping relations between preset environmental parameter and the first weight, determine that the Infrared Targets facial image is corresponding
First object weighted value；
The corresponding second target weight value of the target facial image is calculated according to the first object weighted value；
For the first low frequency component image, the second low frequency component image, the first object weighted value, described second
Target weight value is weighted, and obtains target low frequency component image；
Take absolute value that big principle is taken to carry out operation for the first high fdrequency component image, the second high fdrequency component image,
Obtain targeted high frequency component image；
The target low frequency component image, the targeted high frequency component image are subjected to contravariant corresponding with the multi-resolution decomposition
It changes, obtains the fusion facial image.
6. a kind of face identification device characterized by comprising
Acquiring unit, for obtaining the infrared face image of target user by infrared camera under noctovision environment；
Analytical unit obtains target human face region and target environment parameter for analyzing the infrared face image；
Determination unit, for determining focusing position according to the target human face region, and it is true according to the target environment parameter
Set the goal acquisition parameters；
Shooting unit is obtained for being shot according to the focusing position, target acquisition parameters control visible image capturing head
To target facial image；
Matching unit, for matching the target facial image with default face template；
Unlocking unit, for being unlocked operation in the target facial image and the default face template successful match.
7. device according to claim 6, which is characterized in that analyze described the infrared face image, obtain
In terms of target human face region and target environment parameter, the analytical unit is specifically used for:
Image segmentation is carried out to the infrared face image, obtains human face region；
Obtain the target contrast of the human face region；
According to the mapping relations between preset contrast and environmental parameter, the corresponding target environment of the target contrast is determined
Parameter.
8. device according to claim 6 or 7, which is characterized in that described by the target facial image and default people
In terms of face template is matched, the matching unit is specifically used for:
Image quality evaluation is carried out to the target facial image, obtains objective image quality evaluation of estimate；
According to the mapping relations between preset image quality evaluation values and matching threshold, the objective image quality evaluation is determined
It is worth corresponding object matching threshold value；
Contours extract is carried out to the target facial image, obtains the first circumference；
Feature point extraction is carried out to the target facial image, obtains fisrt feature point set；
First circumference is matched with the second circumference of the default face template, obtains the first matching
Value；
The fisrt feature point set is matched with the second feature point set of the default face template, obtains the second matching
Value；
Object matching value is determined according to first matching value, second matching value；
When the object matching value is greater than the object matching threshold value, the target facial image and the default face are confirmed
Template matching success.
9. a kind of electronic equipment characterized by comprising processor and memory；And one or more programs, it is one
Or multiple programs are stored in the memory, and are configured to be executed by the processor, described program includes being used for
Such as the instruction of any one of claim 1-5 method.
10. a kind of computer readable storage medium, which is characterized in that it is used to store computer program, wherein the computer
Program makes computer execute the method according to claim 1 to 5.
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