WO2019052329A1

WO2019052329A1 - Facial recognition method and related product

Info

Publication number: WO2019052329A1
Application number: PCT/CN2018/102278
Authority: WO
Inventors: 周海涛; 王健; 郭子青
Original assignee: Oppo广东移动通信有限公司
Priority date: 2017-09-12
Filing date: 2018-08-24
Publication date: 2019-03-21
Also published as: CN107609514B; CN107609514A

Abstract

Disclosed in embodiments of the present application are a facial recognition method and a related product. The method comprises: obtaining ambient light, and photographing a face according to the ambient light to obtain a first face image; if the color of the first face image deviates from a specified color, adjusting the display parameter of a screen to obtain a target display parameter; and according to the target display parameter, lighting the screen to supplement light to the face, and photographing the face to obtain a second face image. According to the embodiments of the present application, when the ambient light is used for capturing a face image, if a color deviation occurs, the display parameter of the screen can be adjusted, then the screen assists in supplementing light to the face, the deviation of the color of the captured face image can be reduced as much as possible, so as to improve the quality of the face image, thereby improving face unlocking efficiency.

Description

Face recognition method and related products

The present application claims priority to the priority of the application Serial No. PCT Application No.

Technical field

The present application relates to the field of electronic device technologies, and in particular, to a face recognition method and related products.

Background technique

With the widespread use of electronic devices (mobile phones, tablets, etc.), electronic devices can support more and more applications, and their functions are becoming more and more powerful. Electronic devices are developing in a diversified and personalized way, becoming a user's life. Missing electronic supplies.

At present, face unlocking is increasingly favored by electronic device generators. Since face unlocking does not require the user to touch the electronic device, face image acquisition can be realized. Therefore, face image collection is very convenient, face image The collection is the key to unlocking the face. The quality of the face image directly determines the success or failure of the face unlocking. Therefore, how to improve the collection efficiency of the face image needs to be solved.

Summary of the invention

The embodiment of the present application provides a face recognition method and related products, so as to improve face recognition efficiency.

In a first aspect, an embodiment of the present application provides an electronic device, including an application processor (AP), and a facial recognition device connected to the AP, where

The facial recognition device is configured to acquire ambient light, and capture a face according to the ambient light to obtain a first facial image;

The AP is configured to: if a color of the first face image is color cast in a specified color, adjust a display parameter of the screen to obtain a target display parameter; and light the screen according to the target display parameter, to The face is filled with light;

The face recognition device is configured to perform shooting to obtain a second face image.

In a second aspect, the embodiment of the present application provides a face recognition method, which is applied to an electronic device including an application processor AP and a face recognition device connected to the AP, and the method includes:

The facial recognition device acquires ambient light, and photographs a human face according to the ambient light to obtain a first facial image;

The AP adjusts a display parameter of the screen to obtain a target display parameter when the color of the first face image is color cast to a specified color; and illuminates the screen according to the target display parameter to face the face Fill light

The face recognition device performs shooting to obtain a second face image.

In a third aspect, an embodiment of the present application provides a method for recognizing a face, including:

Obtaining ambient light, and capturing a face according to the ambient light to obtain a first face image;

If the color of the first face image is color cast in a specified color, adjusting a display parameter of the screen to obtain a target display parameter;

The screen is illuminated according to the target display parameter to fill the face and perform shooting to obtain a second face image.

In a fourth aspect, the embodiment of the present application provides a face recognition device, including:

a first photographing unit, configured to acquire ambient light, and photograph a human face according to the ambient light to obtain a first facial image;

An adjusting unit, configured to adjust a display parameter of the screen to obtain a target display parameter if the color of the first face image is color cast in a specified color;

The second photographing unit is configured to illuminate the screen according to the target display parameter to fill the face and perform shooting to obtain a second face image.

In a fifth aspect, an embodiment of the present application provides an electronic device, including: an application processor AP and a memory; and one or more programs, where the one or more programs are stored in the memory, and configured to Executed by the AP, the program includes instructions for some or all of the steps as described in the third aspect.

In a sixth aspect, the embodiment of the present application provides a computer readable storage medium, where the computer readable storage medium is used to store a computer program, wherein the computer program causes the computer to perform the third aspect of the embodiment of the present application. Instructions for some or all of the steps described in the section.

In a seventh aspect, an embodiment of the present application provides a computer program product, where the computer program product includes a non-transitory computer readable storage medium storing a computer program, the computer program being operative to cause a computer to execute Apply some or all of the steps described in the third aspect of the embodiment. The computer program product can be a software installation package.

The implementation of the embodiment of the present application has the following beneficial effects:

It can be seen that the face recognition method described in the embodiment of the present application can obtain ambient light, and the face is photographed according to the ambient light to obtain the first face image, and if the color of the first face image is color cast in the specified Color, adjust the display parameters of the screen, get the target display parameters, light up the screen according to the target display parameters, fill the face with the light, and shoot to obtain the second face image, so that the face can be used in the ambient light When the image is shot, if the color cast phenomenon occurs, the display parameters of the screen can be adjusted, and then the face is complemented by the screen assist, and the face image after the shooting can have the color cast as little as possible, and the face image is improved. The quality, in turn, improves the efficiency of face unlocking.

DRAWINGS

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the embodiments or the prior art description will be briefly described below. Obviously, the drawings in the following description are only It is a certain embodiment of the present application, and other drawings can be obtained according to the drawings without any creative work for those skilled in the art.

1A is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application;

1B is a schematic structural diagram of an electronic device according to an embodiment of the present application;

1C is a schematic flowchart of a face recognition method disclosed in an embodiment of the present application;

FIG. 1D is another schematic flowchart of a face recognition method according to an embodiment of the present application; FIG.

2 is a schematic flowchart diagram of another face recognition method disclosed in an embodiment of the present application;

3 is another schematic structural diagram of an electronic device according to an embodiment of the present application;

4A is a schematic structural diagram of a face recognition device according to an embodiment of the present application;

FIG. 4B is still another schematic structural diagram of the face recognition device described in FIG. 4A provided by the embodiment of the present application; FIG.

4C is a schematic structural diagram of an adjusting unit of the face recognition device described in FIG. 4B according to an embodiment of the present application;

FIG. 5 is a schematic structural diagram of another electronic device disclosed in the embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application are clearly and completely described in the following with reference to the accompanying drawings in the embodiments of the present application. It is a part of the embodiments of the present application, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present application without departing from the inventive scope are the scope of the present application.

The terms "first", "second" and the like in the specification and claims of the present application and the above drawings are used to distinguish different objects, and are not intended to describe a specific order. Furthermore, the terms "comprises" and "comprising" and "comprising" are intended to cover a non-exclusive inclusion. For example, a process, method, system, product, or device that comprises a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units not listed, or, optionally, Other steps or units inherent to these processes, methods, products, or equipment.

References to "an embodiment" herein mean that a particular feature, structure, or characteristic described in connection with the embodiments can be included in at least one embodiment of the present application. The appearances of the phrases in various places in the specification are not necessarily referring to the same embodiments, and are not exclusive or alternative embodiments that are mutually exclusive. Those skilled in the art will understand and implicitly understand that the embodiments described herein can be combined with other embodiments.

The electronic device involved in the embodiments of the present application may include various handheld devices having wireless communication functions, in-vehicle devices, wearable devices, computing devices, or other processing devices connected to the wireless modem, and various forms of user devices (user Equipment, UE), mobile station (MS), terminal device, etc. For convenience of description, the devices mentioned above are collectively referred to as electronic devices.

The embodiments of the present application are described in detail below. As shown in FIG. 1A, an example of the electronic device 1000, the facial recognition device of the electronic device 1000 may include a front camera 21, and the front camera may be at least one of the following: an infrared camera, a dual camera, a visible light camera, etc., a dual camera It can be at least one of the following: an infrared camera + an optical camera, a dual-visible camera, etc., in the face recognition process, the face image can be collected by the face recognition device, and the front camera can have a zoom function, which can be based on different The focal length captures the same target, and multiple images are obtained. The above target can be a human face.

Referring to FIG. 1B , FIG. 1B is a schematic structural diagram of an electronic device 100. The electronic device 100 includes an application processor AP110 and a facial recognition device 130. The AP 110 is connected to the facial recognition device 130 via a bus 150. .

The electronic device described based on FIG. 1A or FIG. 1B can be used to implement the following functions:

The facial recognition device 130 is configured to acquire ambient light, and capture a human face according to the ambient light to obtain a first facial image;

The AP 110 is configured to: if a color of the first face image is color cast in a specified color, adjust a display parameter of the screen to obtain a target display parameter; and light the screen according to the target display parameter, to The face is filled with light;

The face recognition device 130 is configured to perform shooting to obtain a second face image.

Optionally, the AP 110 is further specifically configured to:

Performing spectrum analysis on the first face image to obtain a color component of the first face image;

Comparing the color component with a preset color component to obtain a color deviation degree;

When the color deviation degree is within a preset range, it is confirmed that the color of the first face image is color cast to the specified color.

Optionally, in the aspect of the display parameter of the adjustment screen, the target display parameter, the AP 110 is specifically configured to:

Determining the target display parameter corresponding to the color deviation degree according to a mapping relationship between a preset degree of deviation and a display parameter of the screen.

Optionally, in the aspect of the display parameter of the adjustment screen, the AP 110 is specifically configured to:

Obtaining a first color spectrum map of the ambient light;

Obtaining a preset second color spectrum map;

Determining a spectrum difference map between the second color spectrogram and the first color spectrogram;

A display parameter corresponding to the spectrum difference map is determined as the target display parameter.

Optionally, in the lighting the screen according to the target display parameter, the AP 110 is specifically configured to:

Obtaining display parameters of pre-stored N pieces of wallpaper, and obtaining N sets of display parameters, wherein N is an integer greater than 1;

Selecting a set of display parameters that are closest to the target display parameter from the N sets of display parameters, and acquiring a wallpaper corresponding to the closest set of display parameters to obtain a target wallpaper;

The screen is illuminated according to the target wallpaper.

Further optionally, based on the electronic device described above with reference to FIG. 1A or FIG. 1B, a face recognition method as described below may be performed, as follows:

The facial recognition device 130 acquires ambient light, and photographs a human face according to the ambient light to obtain a first facial image;

The AP 110 adjusts display parameters of the screen when the color of the first face image is color cast to a specified color to obtain a target display parameter; and illuminates the screen according to the target display parameter to face the face Fill light

The face recognition device 130 performs photographing to obtain a second face image.

1C is a schematic flowchart of an embodiment of a face recognition method according to an embodiment of the present application. The face recognition method described in this embodiment is applied to an electronic device including a face recognition device and an application processor AP. The physical map and the structure diagram can be seen in FIG. 1A or FIG. 1B, which includes the following steps:

101. Acquire ambient light, and photograph a face according to the ambient light to obtain a first face image.

Among them, because there are different illuminating objects in the environment, and different reflected light, the facial recognition device can acquire these ambient lights, and fill the face based on the ambient light, and then, the face is photographed, and First face image. Due to the complexity of the light in the environment, it may cause color cast of the face image. Especially in complex environments, it is easy to cause color cast of face images, for example, in a KTV environment, a dark visual environment, or an exposure environment.

102. If the color of the first face image is color cast in a specified color, adjust a display parameter of the screen to obtain a target display parameter.

Among them, the specified color can be one of the following: red, green or blue, and so on. If the color of the first face image is color cast in the specified color, the display parameters of the screen can be adjusted to neutralize the color cast phenomenon, and then, the photographing is performed again, and the color cast phenomenon in the obtained face image is alleviated. The color cast of the first face image described above may be understood as the color cast of the entire first face image in a specified color, or the color corresponding to the face region in the first face image is colored to a specified color. .

Optionally, the display parameter of the screen may be at least one of the following: a color temperature of the screen, a brightness of the screen, a color of the screen, a resolution of the screen, and the like. For example, if the color of the first face image is color cast to a specified color, the color temperature and color of the screen can be adjusted.

Optionally, in the foregoing step 102, adjusting display parameters of the screen may include the following steps:

21. Obtaining a first color spectrum diagram of the ambient light;

22. Obtain a preset second color spectrum map;

23. Determine a spectrum difference diagram between the second color spectrum map and the first color spectrum map;

24. Determine a display parameter corresponding to the spectrum difference map as the target display parameter.

Wherein, the ambient light can be acquired by the facial recognition device, and the ambient light is analyzed to obtain a first color spectrum map. The preset second color spectrum map may be a color spectrum map in the case of non-color cast, and further, a spectrum difference map between the second color spectrogram and the first color spectrogram may be determined, for example, the second color may be A difference operation is performed between the spectrogram and the first color spectrogram, or an absolute value operation is performed to obtain a spectrum difference map. The electronic device can pre-store the correspondence between the spectrogram and the display parameter. Further, after the spectrum difference map is determined, the display parameter corresponding to the spectrum difference map can be determined according to the correspondence as the target display parameter.

103. Light the screen according to the target display parameter, fill the face with a light, and perform shooting to obtain a second face image.

Wherein, the screen can be illuminated according to the target display parameter, and then the face is filled with light through the screen. At this time, the screen is combined with the ambient light to fill the face at the same time, and the face recognition device is used to shoot, and the second is obtained. Face image.

Optionally, in the foregoing step 103, the illuminating the screen according to the target display parameter may include the following steps:

31. Obtain display parameters of pre-stored N wallpapers, and obtain N sets of display parameters, where N is an integer greater than 1.

32. Select a set of display parameters that are closest to the target display parameter from the N sets of display parameters, and obtain a wallpaper corresponding to the closest set of display parameters to obtain a target wallpaper.

33. Lighting the screen according to the target wallpaper.

In the electronic device, N wallpapers may be pre-stored, and each wallpaper corresponds to a set of display parameters, and N sets of display parameters are obtained, where N is an integer greater than 1.

For example, in the process of performing step 32 above, a set of display parameters whose color temperature is closest to the target display parameter in the N sets of display parameters may be selected, and a wallpaper corresponding to the closest set of display parameters, that is, a target wallpaper, may be acquired. Light up the screen to display the target wallpaper.

For example, in the process of performing step 32 above, a set of display parameters whose color is closest to the target display parameter in the N sets of display parameters may be selected, and a wallpaper corresponding to the closest set of display parameters, that is, a target wallpaper, is acquired. Light up the screen to display the target wallpaper.

For example, determining a weight value of each display parameter in the N sets of display parameters, and further, determining a display effect value corresponding to each set of display parameters, and obtaining N display effect values, and similarly determining each display parameter in the target display parameter. The weight value obtains a first target display effect value corresponding to the target display parameter. Selecting a display effect value that is closest to the first target display effect value from the N display effect values, obtaining a second target display effect value, obtaining a corresponding wallpaper, and obtaining a target wallpaper.

Optionally, as shown in FIG. 1D, FIG. 1D is another embodiment of the face recognition method described in FIG. 1C according to the embodiment of the present application, which is compared with the face recognition method described in FIG. 1C. Can include steps:

104. Match the second face image with a preset face template, and perform an unlocking operation when the second face image and the preset face template are successfully matched.

The preset face template may be pre-stored before the foregoing step 101, and the face recognition device is used to collect the face image of the user, and the preset face template may be saved in the face template library.

Optionally, in the process of performing the foregoing step 104, the second face image is matched with the preset face template, and when the matching value between the face image and the preset face template is greater than the face recognition threshold, If the matching is successful, the following unlocking process is performed. When the matching value between the second face image and the preset face template is less than or equal to the face recognition threshold, the entire process of the face recognition may be ended, or the user may be prompted. Perform face recognition again.

Specifically, in the process of performing the foregoing step 104, feature extraction may be performed on the second face image and the preset face template respectively, and then the features obtained after the feature extraction are feature-matched. The above feature extraction can be implemented by using an algorithm such as a Harris corner detection algorithm, a scale invariant feature transform (SIFT), a SUSAN corner detection algorithm, and the like, and details are not described herein.

During the execution of step 104, the face image may be pre-processed, and the pre-processing may include, but is not limited to, image enhancement processing, binarization processing, smoothing processing, color image conversion into grayscale image, etc. Performing feature extraction on the processed second face image to obtain a feature set of the face image, and then selecting at least one face template from the face template library, the face template may be the original face image, or a group The feature set, in turn, performs feature matching on the feature set of the face image and the feature set of the face template to obtain a matching result, and determines whether the matching is successful according to the matching result.

Wherein, when the matching value between the second face image and the preset face template is greater than the face recognition threshold, the next unlocking process may be performed, and the next unlocking process may include, but is not limited to, implementing unlocking to enter the homepage. Face, or, the specified page of an app, or, go to the next biometric step.

Optionally, in the foregoing step 104, matching the second face image with the preset face template may include the following steps:

D1, performing multi-scale decomposition on the second human face image by using a multi-scale decomposition algorithm to obtain a first high-frequency component image of the second human face image, and performing feature extraction on the first high-frequency component image. Obtaining a first feature set;

D2, performing multi-scale decomposition on the preset face template by using the multi-scale decomposition algorithm, obtaining a second high-frequency component image of the preset face template, and performing features on the second high-frequency component image Extracting to obtain a second feature set;

D3. Perform screening on the first feature set and the second feature set to obtain a first stable feature set and the second stable feature set.

D4. Perform feature matching on the first stable feature set and the second stable feature set, and match the number of feature points between the first stable feature set and the second stable feature set to be greater than a preset number. At the threshold, it is confirmed that the second face image is successfully matched with the preset face template.

Wherein, the multi-scale decomposition algorithm may be used to perform multi-scale decomposition on the second face image to obtain a low-frequency component image and a plurality of high-frequency component images, and the first high-frequency component image may be one of a plurality of high-frequency component images. The multi-scale decomposition algorithm described above may include, but is not limited to, wavelet transform, Laplace transform, contourlet transform (CT), non-subsampled contourlet transform (NSCT), shear wave transform. Etc. Taking the contour wave as an example, multi-scale decomposition of the face image by contour wave transform can obtain a low-frequency component image and a plurality of high-frequency component images, and the size of each of the plurality of high-frequency component images Different sizes, taking NSCT as an example, using NSCT to perform multi-scale decomposition of face images, a low-frequency component image and a plurality of high-frequency component images can be obtained, and each of the plurality of high-frequency component images has the same size. . For high frequency component images, it contains more detailed information of the original image. Similarly, the multi-scale decomposition algorithm can be used to perform multi-scale decomposition on the preset face template to obtain a low-frequency component image and a plurality of high-frequency component images, and the second high-frequency component image can be one of a plurality of high-frequency component images. a first high-frequency component image corresponding to a position between the second high-frequency component, that is, a hierarchical position between the two is the same as a scale position, for example, the first high-frequency component image is located on the second layer, At the 3 scale, the second high frequency component image is also located on the 2nd and 3rd scales. In the foregoing step D3, the first feature set and the second feature set are filtered to obtain a first stable feature set and a second stable feature set. The screening process may be as follows. The first feature set may include multiple feature points, The second feature set also includes a plurality of feature points, each feature point is a vector, which includes a size and a direction. Therefore, the modulus of each feature point can be calculated. If the mode is larger than a certain threshold, the feature point is retained, and thus, The feature points can be filtered. The preset number thresholds can be set by the user or the system defaults. The number of matching feature points between the first stable feature set and the second stable feature set can be understood as a matching value between the two. The preset number threshold can be understood as the above first identification threshold. In the above steps D1-D4, the main consideration is to achieve matching of the fine features between the second face image and the preset face template, which can improve the accuracy of the face recognition. In general, the more detailed the feature, the harder it is. Forgery, this enhances the security of face unlocking.

Optionally, between the foregoing step 103 and step 104, the following steps may be further included:

Image enhancement processing is performed on the second face image.

Wherein, the image enhancement processing may include, but is not limited to, image denoising (eg, wavelet transform for image denoising), image restoration (eg, Wiener filtering), dark visual enhancement algorithm (eg, histogram equalization, grayscale pull) Stretching, etc.), after the image enhancement processing of the face image, the quality of the face image can be improved to some extent.

With reference to FIG. 2, a schematic flowchart of an embodiment of a face recognition method according to an embodiment of the present application is provided. The face recognition method described in this embodiment is applied to an electronic device including a face recognition device and an application processor AP. The physical map and the structure diagram can be seen in FIG. 1A or FIG. 1B, which includes the following steps:

201. Acquire ambient light, and capture a face according to the ambient light to obtain a first face image.

202. Perform spectrum analysis on the first face image to obtain a color component of the first face image.

The performing spectrum analysis on the first face image may include: performing spectrum analysis on the entire image of the first face image; or performing spectrum analysis on the face region in the first face image. In this way, the color component of the first face image can be obtained.

203. Compare the color component with a preset color component to obtain a color deviation degree.

Among them, the color component can see whether the image is color cast to a certain extent. The above-described preset color component may be stored in advance in an electronic device, which is a color component in the case of non-color cast. The color component of the first face image can be compared with the preset color component to obtain a color deviation degree. Since the color component can be expressed by the ratio, the color deviation can be easily calculated.

204. When the color deviation degree is in a preset range, confirm that the color of the first face image is color cast in a specified color, adjust a display parameter of the screen, and obtain a target display parameter.

Wherein, the preset range may be set by the system default, or the user may set the user, and further, when the color deviation degree is in the preset range, confirm that the color of the first face image is color cast in the specified color, and further, adjust the display parameter of the screen. , get the target display parameters.

Optionally, in the above step 204, adjusting the display parameters of the screen and the target display parameters may be implemented as follows:

Each of the degrees of deviation corresponds to a display parameter of a screen, which can be obtained in advance by experiments. Further, before the implementation of the embodiment of the present application, a mapping relationship between the preset degree of deviation and the display parameter of the screen can be obtained. Further, according to the mapping relationship, the target display parameter corresponding to the color deviation degree in the above step 203 is determined, so that different display parameters of the screen can be adjusted in different color cast situations to specifically target the face through the screen. Fill light to improve the collection efficiency of face images.

205. Light the screen according to the target display parameter, fill the face with a light, and perform shooting to obtain a second face image.

For a detailed description of the foregoing

steps

201 and 205, reference may be made to the corresponding steps of the face recognition method described in FIG. 1C, and details are not described herein again.

Referring to FIG. 3, FIG. 3 is an electronic device according to an embodiment of the present application, including: an application processor AP and a memory; and one or more programs, where the one or more programs are stored in the memory, And configured to be executed by the AP, the program comprising instructions for performing the following steps:

In one possible example, the program further includes instructions for performing the following steps:

In one possible example, in terms of the display parameters of the adjustment screen, the target display parameters, the program includes instructions for performing the following steps:

In one possible example, in terms of the display parameters of the adjustment screen, the program includes instructions for performing the following steps:

Obtaining a first color spectrum map of the ambient light;

Obtaining a preset second color spectrum map;

In one possible example, in the illuminating the screen according to the target display parameter, the program includes instructions for performing the following steps:

The screen is illuminated according to the target wallpaper.

Referring to FIG. 4A, FIG. 4A is a schematic structural diagram of a face recognition device according to the embodiment. The face recognition device is applied to an electronic device, and the face recognition device includes a first imaging unit 401, an adjustment unit 402, and a second imaging unit 403, where

The first photographing unit 401 is configured to acquire ambient light, and photograph the human face according to the ambient light to obtain a first human face image;

The adjusting unit 402 is configured to adjust a display parameter of the screen to obtain a target display parameter if the color of the first face image is color cast in a specified color;

The second photographing unit 403 is configured to illuminate the screen according to the target display parameter to fill the human face and perform photographing to obtain a second human face image.

Optionally, as shown in FIG. 4B, FIG. 4B is a modified structure of the face recognition device described in FIG. 4A, and the device may further include: an analysis unit 404 and a comparison unit 405, as follows:

The analyzing unit 404 is configured to perform spectrum analysis on the first face image to obtain a color component of the first face image;

The comparison unit 405 is configured to compare the color component with a preset color component to obtain a color deviation degree, and confirm the color deviation of the first face image when the color deviation degree is in a preset range Colors the specified color.

Optionally, the adjusting unit 402 adjusts display parameters of the screen, and the specific implementation manner of the target display parameter is:

Optionally, as shown in FIG. 4C, FIG. 4C is a specific detailed structure of the adjusting unit 402 of the face recognition device described in FIG. 4A, and the adjusting unit 402 may include: an obtaining module 4021 and a determining module 4022, as follows:

The acquiring module 4021 is configured to acquire a first color spectrum map of the ambient light, and acquire a preset second color spectrum map;

a determining module 4022, configured to determine a spectrum difference map between the second color spectrogram and the first color spectrogram; and determine a display parameter corresponding to the spectrum difference map as the target display parameter.

Optionally, the specific implementation manner that the second shooting unit 402 illuminates the screen according to the target display parameter is:

The screen is illuminated according to the target wallpaper.

It can be seen that the face recognition device described in the embodiment of the present application can acquire ambient light, and capture a face according to the ambient light to obtain a first face image, if the color of the first face image is color cast in the specified Color, adjust the display parameters of the screen, get the target display parameters, light up the screen according to the target display parameters, fill the face with the light, and shoot to obtain the second face image, so that the face can be used in the ambient light When the image is shot, if the color cast phenomenon occurs, the display parameters of the screen can be adjusted, and then the face is complemented by the screen assist, and the face image after the shooting can have the color cast as little as possible, and the face image is improved. The quality, in turn, improves the efficiency of face unlocking.

It is to be understood that the functions of the program modules of the face recognition device of the present embodiment may be specifically implemented according to the method in the foregoing method embodiments, and the specific implementation process may refer to the related description of the foregoing method embodiments, and details are not described herein again. .

The embodiment of the present application further provides another electronic device. As shown in FIG. 5, for the convenience of description, only the parts related to the embodiment of the present application are shown. If the specific technical details are not disclosed, refer to the method of the embodiment of the present application. section. The electronic device may be any terminal device including a mobile phone, a tablet computer, a PDA (personal digital assistant), a POS (point of sales), an in-vehicle computer, and the like, and the electronic device is used as a mobile phone as an example:

FIG. 5 is a block diagram showing a partial structure of a mobile phone related to an electronic device provided by an embodiment of the present application. Referring to FIG. 5, the mobile phone includes: a radio frequency (RF) circuit 910, a memory 920, an input unit 930, a sensor 950, an audio circuit 960, a wireless fidelity (WiFi) module 970, an application processor AP980, and a power supply. 990 and other components. It will be understood by those skilled in the art that the structure of the handset shown in FIG. 5 does not constitute a limitation to the handset, and may include more or less components than those illustrated, or some components may be combined, or different components may be arranged. The following describes the components of the mobile phone in detail with reference to FIG. 5:

The input unit 930 can be configured to receive input numeric or character information and to generate key signal inputs related to user settings and function controls of the handset. Specifically, the input unit 930 may include a touch display screen 933, a face recognition device 931, and other input devices 932. The specific structural composition of the face recognition device 931 can be referred to the above description, and will not be described here. The input unit 930 can also include other input devices 932. Specifically, other input devices 932 may include, but are not limited to, one or more of physical buttons, function keys (such as volume control buttons, switch buttons, etc.), trackballs, mice, joysticks, and the like.

The AP 980 is configured to perform the following steps:

The AP 980 is the control center of the handset, which utilizes various interfaces and lines to connect various portions of the entire handset, and executes the handset by running or executing software programs and/or modules stored in the memory 920, as well as invoking data stored in the memory 920. A variety of functions and processing data to monitor the phone as a whole. Optionally, the AP 980 may include one or more processing units, where the processing unit may be an artificial intelligence chip or a quantum chip; preferably, the AP 980 may integrate an application processor and a modem processor, where the application processor mainly processes operations. The system, user interface, application, etc., the modem processor primarily handles wireless communications. It can be understood that the above modem processor may not be integrated into the AP 980.

Moreover, memory 920 can include high speed random access memory, and can also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

The RF circuit 910 can be used for receiving and transmitting information. Generally, RF circuit 910 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier (LNA), a duplexer, and the like. In addition, RF circuitry 910 can also communicate with the network and other devices via wireless communication. The above wireless communication may use any communication standard or protocol, including but not limited to global system of mobile communication (GSM), general packet radio service (GPRS), code division multiple access (code division) Multiple access (CDMA), wideband code division multiple access (WCDMA), long term evolution (LTE), e-mail, short messaging service (SMS), and the like.

The handset may also include at least one type of sensor 950, such as a light sensor, motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor can adjust the brightness of the touch display screen according to the brightness of the ambient light, and the proximity sensor can turn off the touch display when the mobile phone moves to the ear. And / or backlight. As a kind of motion sensor, the accelerometer sensor can detect the magnitude of acceleration in all directions (usually three axes). When it is stationary, it can detect the magnitude and direction of gravity. It can be used to identify the gesture of the mobile phone (such as horizontal and vertical screen switching, related Game, magnetometer attitude calibration), vibration recognition related functions (such as pedometer, tapping), etc.; as for the mobile phone can also be configured with gyroscopes, barometers, hygrometers, thermometers, infrared sensors and other sensors, no longer Narration.

An audio circuit 960, a speaker 961, and a microphone 962 can provide an audio interface between the user and the handset. The audio circuit 960 can transmit the converted electrical data of the received audio data to the speaker 961 for conversion to the sound signal by the speaker 961; on the other hand, the microphone 962 converts the collected sound signal into an electrical signal by the audio circuit 960. After receiving, it is converted into audio data, and then the audio data is played by the AP 980, sent to the other mobile phone via the RF circuit 910, or the audio data is played to the memory 920 for further processing.

WiFi is a short-range wireless transmission technology, and the mobile phone can help users to send and receive emails, browse web pages, and access streaming media through the WiFi module 970, which provides users with wireless broadband Internet access. Although FIG. 5 shows the WiFi module 970, it can be understood that it does not belong to the essential configuration of the mobile phone, and may be omitted as needed within the scope of not changing the essence of the invention.

The mobile phone also includes a power source 990 (such as a battery) that supplies power to various components. Preferably, the power source can be logically connected to the AP980 through a power management system to manage functions such as charging, discharging, and power management through the power management system. Although not shown, the mobile phone may further include a camera, a Bluetooth module, and the like, and details are not described herein again.

In the foregoing embodiment shown in FIG. 1C, FIG. 1D or FIG. 2, each step method flow can be implemented based on the structure of the mobile phone.

In the embodiments shown in FIG. 3 and FIG. 4A to FIG. 4C, each unit function can be implemented based on the structure of the mobile phone.

The embodiment of the present application further provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, the computer program causing the computer to execute any one of the face recognition methods described in the foregoing method embodiments. Some or all of the steps.

The embodiment of the present application further provides a computer program product, comprising: a non-transitory computer readable storage medium storing a computer program, the computer program being operative to cause a computer to perform the operations as recited in the foregoing method embodiments Part or all of the steps of any face recognition method.

It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should understand that the present application is not limited by the described action sequence. Because certain steps may be performed in other sequences or concurrently in accordance with the present application. In the following, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

In the above embodiments, the descriptions of the various embodiments are different, and the details that are not detailed in a certain embodiment can be referred to the related descriptions of other embodiments.

In the several embodiments provided herein, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the unit is only a logical function division. In actual implementation, there may be another division manner, for example, multiple units or components may be combined or may be Integrate into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be electrical or otherwise.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software program module.

The integrated unit, if implemented in the form of a software program module and sold or used as a standalone product, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application, in essence or the contribution to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a memory. A number of instructions are included to cause a computer device (which may be a personal computer, server or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present application. The foregoing memory includes: a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk, or an optical disk, and the like, which can store program codes.

A person skilled in the art can understand that all or part of the steps of the foregoing embodiments can be completed by a program to instruct related hardware, and the program can be stored in a computer readable memory, and the memory can include: a flash drive , ROM, RAM, disk or CD.

The embodiments of the present application have been described in detail above. The principles and implementations of the present application are described in the specific examples. The description of the above embodiments is only used to help understand the method and core ideas of the present application. A person skilled in the art will have a change in the specific embodiments and the scope of the application according to the idea of the present application. In summary, the content of the present specification should not be construed as limiting the present application.

Claims

An electronic device, comprising: an application processor AP, and a face recognition device connected to the AP, wherein

The facial recognition device is configured to acquire ambient light, and capture a face according to the ambient light to obtain a first facial image;

The AP is configured to: if a color of the first face image is color cast in a specified color, adjust a display parameter of the screen to obtain a target display parameter; and light the screen according to the target display parameter, to The face is filled with light;

The face recognition device is configured to perform shooting to obtain a second face image.
The electronic device according to claim 1, wherein the AP is further configured to:

Performing spectrum analysis on the first face image to obtain a color component of the first face image;

Comparing the color component with a preset color component to obtain a color deviation degree;

When the color deviation degree is within a preset range, it is confirmed that the color of the first face image is color cast to the specified color.
The electronic device according to claim 2, wherein in the aspect of the display screen of the adjustment screen, the target display parameter, the AP is specifically used to:

Determining the target display parameter corresponding to the color deviation degree according to a mapping relationship between a preset degree of deviation and a display parameter of the screen.
The electronic device according to claim 1, wherein the AP is specifically configured to:

Obtaining a first color spectrum map of the ambient light;

Obtaining a preset second color spectrum map;

Determining a spectrum difference map between the second color spectrogram and the first color spectrogram;

A display parameter corresponding to the spectrum difference map is determined as the target display parameter.
The electronic device according to any one of claims 1 to 4, wherein the AP is specifically used to: illuminate the screen according to the target display parameter:

Obtaining display parameters of pre-stored N pieces of wallpaper, and obtaining N sets of display parameters, wherein N is an integer greater than 1;

Selecting a set of display parameters that are closest to the target display parameter from the N sets of display parameters, and acquiring a wallpaper corresponding to the closest set of display parameters to obtain a target wallpaper;

The screen is illuminated according to the target wallpaper.
A face recognition method, which is applied to an electronic device including an application processor AP and a face recognition device connected to the AP, the method comprising:

The facial recognition device acquires ambient light, and photographs a human face according to the ambient light to obtain a first facial image;

The AP adjusts a display parameter of the screen to obtain a target display parameter when the color of the first face image is color cast to a specified color; and illuminates the screen according to the target display parameter to face the face Fill light

The face recognition device performs shooting to obtain a second face image.
A face recognition method, comprising:

Obtaining ambient light, and capturing a face according to the ambient light to obtain a first face image;

If the color of the first face image is color cast in a specified color, adjusting a display parameter of the screen to obtain a target display parameter;

The screen is illuminated according to the target display parameter to fill the face and perform shooting to obtain a second face image.
The method of claim 7, wherein the method further comprises:

Performing spectrum analysis on the first face image to obtain a color component of the first face image;

Comparing the color component with a preset color component to obtain a color deviation degree;

When the color deviation degree is within a preset range, it is confirmed that the color of the first face image is color cast to the specified color.
The method according to claim 8, wherein the adjusting the display parameters of the screen, the target display parameters, comprises:

Determining the target display parameter corresponding to the color deviation degree according to a mapping relationship between a preset degree of deviation and a display parameter of the screen.
The method according to claim 7, wherein the adjusting display parameters of the screen comprises:

Obtaining a first color spectrum map of the ambient light;

Obtaining a preset second color spectrum map;

Determining a spectrum difference map between the second color spectrogram and the first color spectrogram;

A display parameter corresponding to the spectrum difference map is determined as the target display parameter.
The method according to any one of claims 7 to 10, wherein the lighting the screen according to the target display parameter comprises:

Obtaining display parameters of pre-stored N pieces of wallpaper, and obtaining N sets of display parameters, wherein N is an integer greater than 1;

Selecting a set of display parameters that are closest to the target display parameter from the N sets of display parameters, and acquiring a wallpaper corresponding to the closest set of display parameters to obtain a target wallpaper;

The screen is illuminated according to the target wallpaper.
The method according to any one of claims 7 to 11, wherein the method further comprises:

And matching the second face image with the preset face template, and performing an unlocking operation when the second face image and the preset face template are successfully matched.
A face recognition device, comprising:

a first photographing unit, configured to acquire ambient light, and photograph a human face according to the ambient light to obtain a first facial image;

An adjusting unit, configured to adjust a display parameter of the screen to obtain a target display parameter if the color of the first face image is color cast in a specified color;

The second photographing unit is configured to illuminate the screen according to the target display parameter to fill the face and perform shooting to obtain a second face image.
The device according to claim 13, wherein the device further comprises:

An analyzing unit, configured to perform spectrum analysis on the first face image to obtain a color component of the first face image;

Aligning unit, configured to compare the color component with a preset color component to obtain a color deviation degree; and when the color deviation degree is in a preset range, confirming a color color cast of the first human face image The specified color.
The device according to claim 14, wherein in the aspect of the display parameter of the adjustment screen, the target display parameter, the adjusting unit is specifically configured to:

Determining the target display parameter corresponding to the color deviation degree according to a mapping relationship between a preset degree of deviation and a display parameter of the screen.
The apparatus according to claim 13, wherein in the adjusting parameters of the adjustment screen, the adjusting unit comprises:

An acquiring module, configured to acquire a first color spectrum map of the ambient light; and obtain a preset second color spectrum map;

a determining module, configured to determine a spectrum difference map between the second color spectrogram and the first color spectrogram; and determine a display parameter corresponding to the spectrum difference map as the target display parameter.
The device according to any one of claims 13 to 16, wherein the second photographing unit is specifically configured to: in the lighting the screen according to the target display parameter:

Obtaining display parameters of pre-stored N pieces of wallpaper, and obtaining N sets of display parameters, wherein N is an integer greater than 1;

Selecting a set of display parameters that are closest to the target display parameter from the N sets of display parameters, and acquiring a wallpaper corresponding to the closest set of display parameters to obtain a target wallpaper;

The screen is illuminated according to the target wallpaper.
An electronic device, comprising: an application processor AP and a memory; and one or more programs, the one or more programs being stored in the memory and configured to be executed by the AP, The program includes instructions for use in a method according to any of claims 7-12.
A computer readable storage medium for storing a computer program, wherein the computer program causes a computer to perform the method of any of claims 7-12.
A computer program product, comprising: a non-transitory computer readable storage medium storing a computer program, the computer program being operative to cause a computer to perform as claimed in any one of claims 7-12 The method described.