HK1245951B - Face living body identification method and related product - Google Patents

Description

Face liveness recognition method and related products

Technical Field

The present invention relates to the technical field of mobile terminals, and in particular to a live face recognition method and related products.

Background Art

With the widespread adoption of mobile devices like cell phones and tablets, almost every modern consumer now has a mobile phone. To ensure security, current mobile phones generally utilize biometric technologies such as fingerprint and facial recognition. Facial recognition, with its advantages such as fast recognition speed, has become widely used in various applications, including phone unlocking and mobile payments.

However, faces are easily forged and therefore less secure. For example, if a criminal obtains a photo of a phone owner, they can use it to perform facial recognition. This shows that current facial recognition systems are relatively insecure.

Summary of the Invention

The embodiments of the present invention provide a human face liveness recognition method and related products, which can quickly detect whether a human face is alive.

A first aspect of an embodiment of the present invention provides a method for live face recognition.

The method comprises:

When a face collection instruction is received, a first face image is collected by the front camera when the front light source is turned off;

Capturing a second facial image by the front camera when the front light source is turned on;

Determining whether an absolute value of a difference between a proportion of an eyeball area in the first facial image and a proportion of an eyeball area in the second facial image is greater than a preset threshold;

If so, it is determined that the collected face image is a living face image.

A second aspect of an embodiment of the present invention provides a mobile terminal, including a front light source, a front camera, and an application processor AP, wherein:

The front camera is configured to capture a first face image when the front light source is turned off upon receiving a face capture instruction;

The front camera is further configured to capture a second facial image when the front light source is turned on;

The AP is configured to determine whether an absolute value of a difference between a proportion of an eyeball area in the first facial image and a proportion of an eyeball area in the second facial image is greater than a preset threshold;

The AP is further used to determine that the collected facial image is a living facial image when the absolute value of the difference between the eye area ratio in the first facial image and the eye area ratio in the second facial image is greater than the preset threshold.

A third aspect of an embodiment of the present invention provides a mobile terminal, including a front light source, a front camera, an application processor (AP), and a memory, wherein the memory is used to store one or more programs, the one or more programs being configured to be executed by the AP, the programs including instructions for performing the following steps:

When a face collection instruction is received, collecting a first face image by the front camera when the front light source is turned off;

Capturing a second facial image by the front camera when the front light source is turned on;

Determining whether an absolute value of a difference between a proportion of an eyeball area in the first facial image and a proportion of an eyeball area in the second facial image is greater than a preset threshold;

If so, it is determined that the collected face image is a living face image.

A fourth aspect of an embodiment of the present invention provides a mobile terminal, comprising a collecting unit, a judging unit, and a determining unit, wherein:

The acquisition unit is configured to, upon receiving a face acquisition instruction, acquire a first face image via the front camera when the front light source is turned off;

The acquisition unit is further configured to acquire a second facial image through the front camera when the front light source is turned on;

The judging unit is configured to judge whether an absolute value of a difference between a proportion of an eyeball area in the first facial image and a proportion of an eyeball area in the second facial image is greater than a preset threshold;

The determining unit is configured to determine that the collected facial image is a living facial image when the determination result of the determining unit is yes.

A fifth aspect of an embodiment of the present invention provides a computer-readable storage medium, which is used to store a computer program for electronic data exchange, wherein the computer program enables a computer to execute some or all of the steps described in any method of the first aspect of an embodiment of the present invention.

A sixth aspect of an embodiment of the present invention provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute some or all of the steps described in any method of the first aspect of an embodiment of the present invention.

In the face liveness recognition method in the embodiment of the present invention, when the mobile terminal performs face liveness recognition, it can use the front light source to collect the first face image and the second face image when it is turned off and on respectively, and use the characteristics of the human eye squinting or closing the eyes under strong light to determine whether the collected face image is a live face image. The recognition algorithm is simple, and it can quickly detect whether the face is alive, thereby improving the security of face recognition.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

FIG1a is a schematic diagram of the working principle of face recognition disclosed in an embodiment of the present invention;

FIG1b is a schematic structural diagram of a mobile terminal disclosed in an embodiment of the present invention;

FIG2 is a flow chart of a method for live face recognition disclosed in an embodiment of the present invention;

FIG3 is a flow chart of another method for face liveness recognition disclosed in an embodiment of the present invention;

FIG4 is a flow chart of another method for face liveness recognition disclosed in an embodiment of the present invention;

FIG5 is a schematic structural diagram of another mobile terminal disclosed in an embodiment of the present invention;

FIG6 is a schematic structural diagram of another mobile terminal disclosed in an embodiment of the present invention;

FIG7 is a schematic structural diagram of another mobile terminal disclosed in an embodiment of the present invention.

DETAILED DESCRIPTION

In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

The terms "first," "second," and so on, in the description and claims of the present invention and the accompanying drawings are used to distinguish between different objects, not to describe a specific order. Furthermore, the terms "including," "having," and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

The mobile terminals involved in the embodiments of the present invention may include various handheld devices with wireless communication functions, vehicle-mounted devices, wearable devices, computing devices, or other processing devices connected to a wireless modem, as well as various forms of user equipment (UE), mobile stations (MS), terminal devices, etc. For the convenience of description, the above-mentioned devices are collectively referred to as mobile terminals.

The embodiments of the present invention are described in detail below.

To better understand the embodiments of the present invention, the working principle of facial recognition in the embodiments of the present invention will first be introduced. Please refer to Figure 1a, which is a schematic diagram of the working principle of facial recognition disclosed in the embodiments of the present invention. The facial recognition in Figure 1a is applied to a mobile terminal, taking a mobile phone as an example. As shown in Figure 1a, a front light source 110 and a front camera 120 are both located on the front of the mobile phone 10, wherein the front camera 120 is used to capture facial images. The application processor (AP) 130 processes the captured facial image and matches it with a pre-stored facial image template. When the match is successful, the facial recognition verification is considered to have passed. The front light source 110 can be a front flash, which is used to assist in determining whether the captured facial image is a live facial image. The AP 130 cannot be directly seen from the exterior of the mobile phone 10, so it is represented by a dotted line in Figure 1a.

Please refer to Figure 1b, which is a structural diagram of a mobile terminal disclosed in an embodiment of the present invention. As shown in Figure 1b, the mobile terminal 100 includes an application processor (AP) 101, a front light source 102 and a front camera 103, wherein the AP 101 is connected to the front light source 102 and the front camera 103 through a bus 104.

The front camera 103 is used to capture a first face image when the mobile terminal 100 receives a face capture instruction and the front light source 102 is turned off.

The mobile terminal 100 can receive a face collection instruction triggered based on the user's input operation on the touch screen. For example, when the application scenario is a screen unlocking scenario, after the touch screen is turned on, a selection prompt box may pop up on the touch screen to guide the user to select one of "iris recognition", "fingerprint recognition" and "face recognition". When the user clicks "face recognition" in the selection prompt box, the face collection instruction is triggered. The mobile terminal 100 can also trigger the generation of a face collection instruction when it detects that the user has picked up the mobile terminal 100. For example, when the application scenario is a screen unlocking scenario, when the posture sensor of the mobile terminal 100 (for example, a gravity sensor, a three-axis gyroscope, a three-axis acceleration sensor, etc.) detects that the user has lifted the mobile terminal 100, the mobile terminal 100 can be triggered to generate a face collection instruction.

The front camera 103 is also used to capture a second facial image when the front light source 102 is turned on.

The front light source 102 may be a front flash, a display backlight, or a combination of the front flash and the display backlight. The front flash may be positioned near the front camera 103 to provide fill light when the front camera is shooting. The display backlight may be an LED backlight. Upon detecting that the user has lifted the mobile terminal 100, the front camera 103 may capture a first facial image when the display is off, then illuminate the mobile terminal's display, and may capture a second facial image when the mobile terminal's display is illuminated.

The front camera 103 may send the captured first face image and the second face image to the AP 101 for processing.

AP101 is used to determine whether the absolute value of the difference between the eye area ratio in the first face image and the eye area ratio in the second face image is greater than a preset threshold.

In an embodiment of the present invention, when the front light source 102 is a front flash, the front camera 103 can capture a first face image and a second face image respectively when the front flash is turned off and on. When the front flash is turned off, the user's face will not be stimulated by strong light, and the eyes in the first face image are in a normally open state; when the front flash is turned on, the user's face is stimulated by strong light, and the eyes in the second face image are likely to be in a squinting state or a closed state.

The eyeball area ratio is the ratio of the area of the eyeball area in the face image to the area of the entire face image. AP101 determines whether the absolute value of the difference between the eyeball area ratio in the first face image and the eyeball area ratio in the second face image is greater than a preset threshold. The purpose is to determine whether the collected face image is a living face image, that is, whether the object photographed by the front camera is alive. If the photographed object is alive, since the human pupil will contract when stimulated by strong light, the eyeball area ratio in the first face image and the eyeball area ratio in the second face image will change significantly, and the absolute value of the difference between the eyeball area ratio in the first face image and the eyeball area ratio in the second face image will be greater than the preset threshold. If the photographed object is not alive (such as the eyes of a dead person or a photo), the eyeball area ratio in the first face image and the eyeball area ratio in the second face image generally will not change significantly, and the absolute value of the difference between the eyeball area ratio in the first face image and the eyeball area ratio in the second face image will be less than the preset threshold. In the embodiment of the present invention, whether the collected face image is a living face image is determined by judging whether the proportion of the eye area in the face image taken by the front camera is greater than a preset threshold when the front light source is in the off and on states. The liveness recognition algorithm is simple.

AP101 is also used to determine that the collected facial image is a living facial image when the absolute value of the difference between the eye area ratio in the first facial image and the eye area ratio in the second facial image is greater than a preset threshold.

Optionally, AP101 is also used to determine that the collected facial image is a non-living facial image when the absolute value of the difference between the eye area ratio in the first facial image and the eye area ratio in the second facial image is less than or equal to a preset threshold.

In an embodiment of the present invention, when the absolute value of the difference between the proportion of the eye area in the first facial image and the proportion of the eye area in the second facial image is less than or equal to a preset threshold, it indicates that the facial images captured by the front camera under different light intensities are little different, and it can be considered that the captured facial image is a non-living facial image.

Optionally, AP101 is further configured to, after determining that the collected facial image is a living facial image, use an image having a larger eye area in the first facial image and the second facial image as a valid facial image;

AP101 is also used to verify whether a valid face image matches a pre-stored face image template;

AP101 is also used to determine that face recognition is successful when a valid face image matches a pre-stored face image template.

In an embodiment of the present invention, the face image template may include face features, such as face eye features (e.g., eyeball size and shape, eye distance, etc.), eye and nose features (nostril distance, nose tip length, etc.), eye and mouth features (lip thickness, lip length, etc.), and combined features (the distance between the nostrils to the left eye and the right eye, the distance from the left eye to the lips, etc.).

Optionally, before AP101 verifies whether the valid face image matches a pre-stored face image template, it may convert the valid face image into a standardized image. The standardization processing here includes pixel standardization, image size standardization, etc.

Optionally, the front camera 103 captures the second facial image when the front light source 102 is turned on in the following manner:

The front camera 103 captures the second facial image when the front light source 102 is at the first power.

The front camera 103 is further configured to capture a third facial image when the front light source 102 is at a second power greater than the first power, when the absolute value of the difference between the eye area ratio in the first facial image and the eye area ratio in the second facial image is less than or equal to a preset threshold and greater than zero;

AP101 is further configured to determine whether the absolute value of the difference between the eyeball area ratio in the first face image and the eyeball area ratio in the third face image is greater than a preset threshold;

AP101 is also used to determine that the collected facial image is a living facial image when the absolute value of the difference between the eye area ratio in the first facial image and the eye area ratio in the third facial image is greater than a preset threshold.

In an embodiment of the present invention, when the absolute value of the difference between the proportion of the eye area in the first facial image and the proportion of the eye area in the second facial image is less than or equal to a preset threshold and greater than zero, it indicates that there has been a slight change in the human eyes in the first facial image captured by the front camera and the second facial image. In order to prevent misjudgment as a living object, the front camera continues to capture the third facial image when the front light source is at the second power, and the power of the front light source is increased, that is, the fill light intensity when the front camera captures the facial image is increased. The method of increasing the fill light intensity is used to further determine whether the captured facial image is a facial image, which can prevent misjudgment of a living object as a non-living object.

Optionally, the difference between the second power and the first power may be preset to prevent the front light source with excessively high power from causing significant stimulation to the human eye.

Optionally, AP101 is further configured to, after determining that the collected facial image is a living facial image, set the power of the front camera during subsequent facial recognition to the second power.

In the embodiment of the present invention, the operating power of the front light source when the live face recognition is successful can be used as the operating power of the front light source during the next live face recognition, which can improve the accuracy of live face recognition.

Implementing the mobile terminal shown in Figure 1b, when performing face liveness recognition, the mobile terminal can use the front light source to collect the first face image and the second face image when it is turned off and on respectively, and use the characteristics of human eyes squinting or closing eyes under strong light to determine whether the collected face image is a live face image. The recognition algorithm is simple, and can quickly detect whether the face is alive, thereby improving the security of face recognition.

Please refer to Figure 2, which is a flow chart of a method for face liveness recognition disclosed in an embodiment of the present invention. The method is applied to a mobile terminal including a front-mounted light source, a front-mounted camera, and an application processor AP. As shown in Figure 2, the method includes the following steps.

201. When receiving a face collection instruction, the mobile terminal collects a first face image through a front camera when the front light source is turned off.

202. The mobile terminal collects a second facial image through a front camera when the front light source is turned on.

203 , the mobile terminal determines whether the absolute value of the difference between the eyeball area ratio in the first face image and the eyeball area ratio in the second face image is greater than a preset threshold. If so, execute step 204 ; otherwise, execute step 205 .

204. The mobile terminal determines that the collected facial image is a living facial image.

205. The mobile terminal determines that the collected facial image is a non-living facial image.

The specific implementation of the method shown in FIG2 can refer to the device embodiment shown in FIG1a-FIG1b, and will not be described in detail here.

By implementing the method shown in FIG2 , when performing live face recognition, the mobile terminal can use the front light source to collect the first face image and the second face image when it is turned off and on respectively, and use the characteristics of the human eye squinting or closing the eyes under strong light to determine whether the collected face image is a live face image. The recognition algorithm is simple and can quickly detect whether the face is alive, thereby improving the security of face recognition.

Please refer to Figure 3, which is a flow chart of another method for face liveness recognition disclosed in an embodiment of the present invention. The method is applied to a mobile terminal including a front-mounted light source, a front-mounted camera, and an application processor AP, and includes the following steps.

301. When receiving a face collection instruction, the mobile terminal collects a first face image through a front camera when the front light source is turned off.

302. The mobile terminal collects a second facial image through a front camera when the front light source is turned on.

303 , the mobile terminal determines whether the absolute value of the difference between the eyeball area ratio in the first face image and the eyeball area ratio in the second face image is greater than a preset threshold. If so, execute step 204 ; otherwise, execute step 205 .

304. The mobile terminal determines that the collected facial image is a living facial image.

305. The mobile terminal determines that the collected facial image is a non-living facial image.

306 : The mobile terminal uses the image with the larger eye area in the first face image and the second face image as a valid face image.

307, the mobile terminal verifies whether the valid face image matches the pre-stored face image template. If so, execute step 308; if not, execute step 309.

308. The mobile terminal determines that the face recognition is successful.

309. The mobile terminal determines that the face recognition fails.

The specific implementation of the method shown in FIG3 can refer to the device embodiment shown in FIG1a-FIG1b, which will not be described in detail here.

By implementing the method shown in FIG3 , when performing live face recognition, the mobile terminal can use the front light source to collect the first face image and the second face image when it is turned off and on respectively, and use the characteristics of the human eye squinting or closing the eyes under strong light to determine whether the collected face image is a live face image. The recognition algorithm is simple and can quickly detect whether the face is alive, thereby improving the security of face recognition.

Please refer to Figure 4, which is a flowchart of another method for face liveness recognition disclosed in an embodiment of the present invention. The method is applied to a mobile terminal including a front light source, a front camera, and an application processor AP, and includes the following steps.

401. When receiving a face collection instruction, the mobile terminal collects a first face image through the front camera when the front light source is turned off.

402. The mobile terminal captures a second facial image through a front camera when the front light source is at a first power.

403 , the mobile terminal determines whether the absolute value of the difference between the eyeball area ratio in the first face image and the eyeball area ratio in the second face image is greater than a preset threshold. If so, execute step 404 ; otherwise, execute step 405 .

404. The mobile terminal determines that the collected facial image is a living facial image.

405 , the mobile terminal collects a third facial image through the front camera when the front light source is at a second power, where the second power is greater than the first power.

406 , the mobile terminal determines whether the absolute value of the difference between the eyeball area ratio in the first face image and the eyeball area ratio in the third face image is greater than a preset threshold. If so, execute step 404 ; otherwise, execute step 407 .

407 : The mobile terminal determines that the collected facial image is a non-living facial image.

The specific implementation of the method shown in FIG4 can refer to the device embodiment shown in FIG1a-FIG1b, and will not be described in detail here.

By implementing the method shown in FIG4 , when the mobile terminal performs live face recognition, it can use the front light source to collect the first face image and the second face image when it is turned off and on respectively, and use the characteristics of the human eye squinting or closing the eyes under strong light to determine whether the collected face image is a live face image. The recognition algorithm is simple and can quickly detect whether the face is alive, thereby improving the security of face recognition.

Please refer to Figure 5, which is a schematic diagram of the structure of another mobile terminal disclosed in an embodiment of the present invention. The mobile terminal 500 includes a front light source 501, a front camera 502, an application processor AP503, and a memory 504. The front light source 501, the front camera 502, the application processor AP503, and the memory 504 can be connected via a communication bus 505. The memory 505 is used to store one or more programs, which are configured to be executed by the AP 504. The program includes instructions for performing the following steps:

When a face collection instruction is received, a first face image is collected by the front camera 502 when the front light source 501 is turned off;

The front camera 502 captures a second facial image when the front light source 501 is turned on;

Determining whether the absolute value of the difference between the eyeball area ratio in the first face image and the eyeball area ratio in the second face image is greater than a preset threshold;

If so, it is determined that the collected face image is a living face image.

Optionally, the program further includes instructions for executing the following steps:

The image with the larger eye area in the first face image and the second face image is taken as the valid face image;

Verify whether the valid face image matches the pre-stored face image template;

If they match, facial recognition is confirmed.

Optionally, the program further includes instructions for executing the following steps:

If the absolute value of the difference between the eye area ratio in the first face image and the eye area ratio in the second face image is less than or equal to a preset threshold, it is determined that the collected face image is a non-living face image.

Optionally, in terms of capturing the second facial image through the front camera 502 when the front light source 501 is turned on, the program is specifically configured to perform the following steps:

Capturing a second facial image by the front camera 502 when the front light source 501 is at a first power;

The program also includes instructions for performing the following steps:

After determining whether the absolute value of the difference between the eye area ratio in the first facial image and the eye area ratio in the second facial image is greater than a preset threshold, if the absolute value of the difference between the eye area ratio in the first facial image and the eye area ratio in the second facial image is less than or equal to the preset threshold and greater than zero, capturing a third facial image via the front camera 502 when the front light source 501 is at a second power, the second power being greater than the first power;

Determine whether the absolute value of the difference between the eyeball area ratio in the first face image and the eyeball area ratio in the third face image is greater than a preset threshold;

If so, it is determined that the collected face image is a living face image.

Optionally, the front light source 501 includes a front flash and/or a display screen backlight.

The mobile terminal shown in Figure 5 can be implemented to collect the first face image and the second face image by using the front light source when it is turned off and on respectively, and the characteristics of the human eye squinting or closing the eyes under strong light can be used to determine whether the collected face image is a living face image. The recognition algorithm is simple and can quickly detect whether the face is alive, thereby improving the security of face recognition.

Please refer to Figure 6, which is a schematic diagram of the structure of another mobile terminal disclosed in an embodiment of the present invention. The mobile terminal 600 includes a collection unit 601, a judgment unit 602 and a determination unit 603, wherein:

The acquisition unit 601 is configured to, upon receiving a face acquisition instruction, acquire a first face image through a front camera when the front light source is turned off;

The acquisition unit 601 is further configured to acquire a second facial image through the front camera when the front light source is turned on;

A determination unit 602 is configured to determine whether an absolute value of a difference between a proportion of an eyeball area in the first face image and a proportion of an eyeball area in the second face image is greater than a preset threshold;

The determining unit 603 is configured to determine that the collected facial image is a living facial image when the determination result of the determining unit 602 is yes.

The implementation of the mobile terminal can refer to the method embodiments shown in Figures 2-4, and the repeated parts will be omitted.

The mobile terminal shown in Figure 6 can be implemented to collect the first face image and the second face image by using the front light source when it is turned off and on respectively, and use the characteristics of the human eye squinting or closing the eyes under strong light to determine whether the collected face image is a living face image. The recognition algorithm is simple and can quickly detect whether the face is alive, thereby improving the security of face recognition.

The present invention also provides another mobile terminal, as shown in FIG7 . For ease of explanation, only the portion relevant to the present invention is shown. For specific technical details not disclosed, please refer to the method section of the present invention. The mobile terminal can be any terminal device including a mobile phone, tablet computer, PDA (Personal Digital Assistant), POS (Point of Sales), in-vehicle computer, etc. Taking a mobile phone as an example:

FIG7 is a block diagram illustrating a portion of the structure of a mobile phone related to a mobile terminal provided by an embodiment of the present invention. Referring to FIG7 , the mobile phone includes components such as a radio frequency (RF) circuit 910, a memory 920, an input unit 930, a display unit 940, a sensor 950, an audio circuit 960, a wireless fidelity (WiFi) module 970, a processor 980, and a power supply 990. Those skilled in the art will appreciate that the mobile phone structure shown in FIG7 does not limit the mobile phone, and the mobile phone may include more or fewer components than shown, or may combine certain components, or have different component arrangements.

The following is a detailed introduction to the various components of the mobile phone in conjunction with Figure 7:

The RF circuit 910 can be used for receiving and sending information. Typically, the 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, the RF circuit 910 can also communicate with a network and other devices via wireless communication. The above-mentioned wireless communication can 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 (CDMA), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), email, Short Messaging Service (SMS), and the like.

Memory 920 can be used to store software programs and modules. Processor 980 executes the various functional applications and data processing functions of the mobile phone by running the software programs and modules stored in memory 920. Memory 920 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application required for a function; the data storage area may store data generated based on the use of the mobile phone. Memory 920 may also include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state memory device.

The input unit 930 can be used to receive input digital or character information, and to generate key signal input related to the user settings and function control of the mobile phone. Specifically, the input unit 930 may include a fingerprint recognition module 931, a touch screen 932 and other input devices 933. The fingerprint recognition module 931 can collect the fingerprint data of the user thereon. In addition to the fingerprint recognition module 931, the input unit 930 may also include other input devices 932. Specifically, other input devices 932 may include but are not limited to one or more of a touch screen, a physical keyboard, function keys (such as volume control buttons, switch buttons, etc.), a trackball, a mouse, a joystick, etc.

The display unit 940 can be used to display information input by the user or information provided to the user, as well as various menus of the mobile phone. The display unit 940 may include a display screen 941. Optionally, the display screen 941 may be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like. Although in FIG7 , the fingerprint recognition module 931 and the display screen 941 are used as two independent components to implement the input and output functions of the mobile phone, in some embodiments, the fingerprint recognition module 931 and the display screen 941 can be integrated to implement the input and playback functions of the mobile phone.

The mobile phone may also include at least one sensor 950, such as an optical sensor 951, a motion sensor 952, and other sensors. Specifically, the optical sensor 951 may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor can adjust the brightness of the display screen 941 according to the brightness of the ambient light, and the proximity sensor can turn off the display screen 941 and/or the backlight when the mobile phone is moved to the ear. As a type of motion sensor 952, the accelerometer sensor can detect the magnitude of acceleration in all directions (generally three axes), and can detect the magnitude and direction of gravity when stationary. It can be used for applications that identify the posture of the mobile phone (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc.; as for other sensors that the mobile phone can also be configured with, such as gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc., they will not be described here.

Audio circuit 960, speaker 961, and microphone 962 provide an audio interface between the user and the phone. Audio circuit 960 converts received audio data into electrical signals and transmits them to speaker 961, which then converts them into sound signals for playback. Microphone 962, on the other hand, converts collected sound signals into electrical signals, which are then received by audio circuit 960 and converted into audio data. After processing by audio data playback processor 980, the audio data is transmitted via RF circuit 910 to, for example, another phone, or played to memory 920 for further processing.

WiFi is a short-range wireless transmission technology. A mobile phone uses WiFi module 970 to help users send and receive emails, browse the web, and access streaming media, providing wireless broadband Internet access. Although FIG7 shows WiFi module 970, it is understood that it is not a required component of the mobile phone and can be omitted as needed without changing the essence of the invention.

The processor 980 is the control center of the mobile phone, connecting all parts of the mobile phone using various interfaces and circuits. By running or executing software programs and/or modules stored in the memory 920 and accessing data stored in the memory 920, it performs various functions of the mobile phone and processes data, thereby providing overall monitoring of the mobile phone. Optionally, the processor 980 may include one or more processing units; preferably, the processor 980 may integrate an application processor and a modem processor, wherein the application processor primarily handles the operating system, user interface, and application programs, while the modem processor primarily handles wireless communications. It is understood that the modem processor may not be integrated into the processor 980.

The mobile phone also includes a power supply 990 (such as a battery) for supplying power to various components. Preferably, the power supply can be logically connected to the processor 980 through a power management system, thereby managing charging, discharging, and power consumption management functions through the power management system.

The mobile phone also includes a camera 9100, which may include a front camera, an iris camera, and a rear camera.

Although not shown, the mobile phone may further include a Bluetooth module, a flash, etc. The flash may include a front flash and a rear flash. The front flash may provide fill light for the front camera, and the rear flash may provide fill light for the rear camera. The front flash may include a front visible light flash and a front infrared flash. The front visible light flash is used to provide fill light for the front camera, and the front infrared flash is used to provide fill light for the iris camera.

An embodiment of the present invention also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any one of the face liveness recognition methods described in the above method embodiments.

An embodiment of the present invention also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute part or all of the steps of any one of the face liveness recognition methods described in the above method embodiments.

It should be noted that for the aforementioned method embodiments, for simplicity of description, they are all expressed as a series of action combinations. However, those skilled in the art should be aware that the present invention is not limited by the order of the actions described, because according to the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

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

In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, and other media that can store program code.

Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program. The program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

The embodiments of the present invention are described in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core ideas. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the contents of this specification should not be understood as limiting the present invention.

Claims (9)

1. A method for facial liveness recognition, characterized in that it includes: When a face capture command is received, the first face image is captured by the front-facing camera when the front-facing light source is off. The front-facing camera captures a second face image when the front-facing light source is at a first power. Determine whether the absolute value of the difference between the proportion of the eye region in the first face image and the proportion of the eye region in the second face image is greater than a preset threshold. If so, if the captured face image is determined to be a live face image, the first face image is taken as a valid face image; If the absolute value of the difference between the proportion of the eye region in the first face image and the proportion of the eye region in the second face image is less than or equal to the preset threshold and greater than zero, a third face image is acquired by the front-facing camera when the front-facing light source is at a second power, where the second power is greater than the first power; it is then determined whether the absolute value of the difference between the proportion of the eye region in the first face image and the proportion of the eye region in the third face image is greater than the preset threshold; if so, the acquired face image is determined to be a live face image, and the first face image is taken as a valid face image; Verify whether the valid face image matches the pre-stored face image template; if they match, determine that the face recognition has passed. 2. The method according to claim 1, characterized in that the method further comprises: If the absolute value of the difference between the proportion of the eye region in the first face image and the proportion of the eye region in the second face image is less than or equal to the preset threshold, the acquired face image is determined to be a non-live face image. 3. The method according to any one of claims 1-2, wherein the front light source comprises a front flash and/or a display screen backlight. 4. A mobile terminal, characterized in that it includes a front-facing light source, a front-facing camera, and an application processor (AP), wherein: The front-facing camera is used to capture a first face image when the front-facing light source is turned off upon receiving a face capture command. The front-facing camera is also used to capture a second face image when the front-facing light source is at a first power; when the absolute value of the difference between the proportion of the eye area in the first face image and the proportion of the eye area in the second face image is less than or equal to a preset threshold and greater than zero, a third face image is captured when the front-facing light source is at a second power, wherein the second power is greater than the first power. The AP is used to determine whether the absolute value of the difference between the proportion of the eye region in the first face image and the proportion of the eye region in the second face image is greater than a preset threshold. The AP is further configured to: determine that the acquired face image is a live face image and use the first face image as a valid face image when the absolute value of the difference between the proportion of the eye region in the first face image and the proportion of the eye region in the second face image is greater than the preset threshold; if the absolute value of the difference between the proportion of the eye region in the first face image and the proportion of the eye region in the second face image is less than or equal to the preset threshold and greater than zero, acquire a third face image through the front-facing camera when the front-facing light source is at a second power, where the second power is greater than the first power; determine whether the absolute value of the difference between the proportion of the eye region in the first face image and the proportion of the eye region in the third face image is greater than the preset threshold; if so, determine that the acquired face image is a live face image and use the first face image as a valid face image; verify whether the valid face image matches a pre-stored face image template; if they match, determine that face recognition has been passed. 5. The mobile terminal according to claim 4, characterized in that, The AP is further configured to determine that the acquired face image is a non-live face image when the absolute value of the difference between the proportion of the eye region in the first face image and the proportion of the eye region in the second face image is less than or equal to the preset threshold. 6. The mobile terminal according to any one of claims 4-5, wherein the front-facing light source includes a front-facing flash and/or a display screen backlight. 7. A mobile terminal, characterized in that it comprises a data acquisition unit, a judgment unit, and a determination unit, wherein: The acquisition unit is used to acquire a first face image through the front-facing camera when the front-facing light source is turned off when a face acquisition command is received. The acquisition unit is also used to acquire a second face image through the front-facing camera when the front-facing light source is at a first power. The judgment unit is used to determine whether the absolute value of the difference between the proportion of the eye region in the first face image and the proportion of the eye region in the second face image is greater than a preset threshold. The determining unit is configured to, when the determination result of the judging unit is yes, determine that the acquired face image is a live face image and take the first face image as a valid face image; if the absolute value of the difference between the proportion of the eye region in the first face image and the proportion of the eye region in the second face image is less than or equal to the preset threshold and greater than zero, acquire a third face image through the front-facing camera when the front-facing light source is at a second power, where the second power is greater than the first power; determine whether the absolute value of the difference between the proportion of the eye region in the first face image and the proportion of the eye region in the third face image is greater than the preset threshold; if yes, determine that the acquired face image is a live face image and take the first face image as a valid face image; This is used to verify whether the valid face image matches a pre-stored face image template; if they match, the unit that passed face recognition is determined. 8. A mobile terminal, characterized in that it includes a front-facing light source, a front-facing camera, an application processor (AP), and a memory, the memory being used to store one or more programs configured to be executed by the AP, the programs including methods for performing the method as described in any one of claims 1-3. 9. A computer-readable storage medium, characterized in that the computer-readable storage medium is used to store a computer program for electronic data interchange, wherein the computer program causes a computer to perform the method as described in any one of claims 1-3.