CN107480496A - Solve lock control method and Related product - Google Patents

Abstract

The embodiment of the present invention discloses an unlocking control method and related products, wherein the method includes: detecting the target distance between the target object and the mobile terminal; acquiring the current environment parameter set; determining the distance from the target and the current environment parameter Set the corresponding target biometric mode, and activate the target biometric mode. In the embodiment of the present invention, the corresponding biometric identification mode can be activated according to the distance and the environment, and then, a reasonable biometric identification mode can be automatically activated in different environments, which greatly facilitates the user and improves the efficiency of multi-biological identification.

Description

Unlock control method and related products

technical field

The invention relates to the technical field of mobile terminals, in particular to an unlocking control method and related products.

Background technique

With the popularization and application of mobile terminals (mobile phones, tablet computers, etc.), mobile terminals can support more and more applications, and their functions are becoming more and more powerful. Missing electronics.

At present, multi-biometric identification is more and more favored by mobile terminal manufacturers, and multi-biometric identification will also be affected by the environment, thus reducing the identification efficiency. Therefore, how to improve the identification efficiency of multi-biometric identification needs to be solved urgently.

Contents of the invention

Embodiments of the present invention provide an unlocking control method and related products, which can improve the efficiency of multi-biometric identification.

In a first aspect, an embodiment of the present invention provides a mobile terminal, including an application processor (Application Processor, AP), and an environment sensor and a ranging sensor connected to the AP, wherein,

The ranging sensor is used to detect the target distance between the target object and the mobile terminal;

The environmental sensor is used to obtain the current environmental parameter set;

The AP is configured to determine a target biometric identification mode corresponding to the target distance and the current environment parameter set, and activate the target biometric identification mode.

In a second aspect, an embodiment of the present invention provides an unlocking control method, which is applied to a mobile terminal including an application processor AP, and an environment sensor and a ranging sensor connected to the AP, and the method includes:

The ranging sensor is used to detect the target distance between the target object and the mobile terminal;

The environmental sensor is used to obtain the current environmental parameter set;

The AP is configured to determine a target biometric identification mode corresponding to the target distance and the current environment parameter set, and activate the target biometric identification mode.

In a third aspect, an embodiment of the present invention provides an unlocking control method, including:

Detect the target distance between the target object and the mobile terminal;

Get the current environment parameter set;

A target biometric identification mode corresponding to the target distance and the current environment parameter set is determined, and the target biometric identification mode is activated.

In a fourth aspect, an embodiment of the present invention provides an unlocking control device, including:

a detection unit for detecting the target distance between the target object and the mobile terminal;

A determination unit is used to obtain the current environment parameter set;

A processing unit, configured to determine a target biometric identification mode corresponding to the target distance and the current environment parameter set, and activate the target biometric identification mode.

In the fifth aspect, the embodiment of the present invention provides a mobile terminal, an application processor AP and a memory; and one or more programs, the one or more programs are stored in the memory, And configured to be executed by the AP, the program includes instructions for executing some or all of the steps described in the third aspect.

In a sixth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store a computer program, wherein the computer program enables the computer to execute the third aspect of the present invention. Some or all of the steps described in .

In a seventh aspect, an embodiment of the present invention provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable the computer to execute the Part or all of the steps described in the third aspect of the invention embodiment. The computer program product may be a software installation package.

Implementing the embodiment of the present invention has the following beneficial effects:

It can be seen that in the embodiment of the present invention, the mobile terminal can detect the target distance between the target object and the mobile terminal, obtain the current environment parameter set, determine the target biometric pattern corresponding to the target distance and the current environment parameter set, and activate the target Biometrics mode, it can be seen that the corresponding biometrics mode can be activated through distance and environment, and then, a reasonable biometrics mode can be automatically activated in different environments, which greatly facilitates users and improves the efficiency of multiple biometrics.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present invention. Those skilled in the art can also obtain other drawings based on these drawings without creative work.

FIG. 1A is a schematic structural diagram of an example mobile terminal provided by an embodiment of the present invention;

FIG. 1B is another schematic structural diagram of a mobile terminal provided by an embodiment of the present invention;

Fig. 1C is a schematic flowchart of an unlocking control method disclosed in an embodiment of the present invention;

Fig. 2 is a schematic flowchart of another unlocking control method disclosed in an embodiment of the present invention;

FIG. 3 is another schematic structural diagram of a mobile terminal provided by an embodiment of the present invention;

Fig. 4A is a schematic structural diagram of an unlocking control device provided by an embodiment of the present invention;

Fig. 4B is another structural schematic diagram of an unlocking control device provided by an embodiment of the present invention;

Fig. 5 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 following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

The terms "first", "second" and the like in the description and claims of the present invention and the above drawings are used to distinguish different objects, rather than to describe a specific order. Furthermore, the terms "include" and "have", as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but optionally also includes unlisted steps or units, or optionally further includes For other steps or units inherent in these processes, methods, products or devices.

Reference herein to an "embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present invention. The occurrences of this phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is understood explicitly and implicitly by those skilled in the art that the embodiments described herein can be combined with other embodiments.

The mobile terminals involved in the embodiments of the present invention may include various handheld devices, vehicle-mounted devices, wearable devices, computing devices or other processing devices connected to wireless modems, as well as various forms of user equipment (User Equipment, UE), mobile station (Mobile Station, MS), terminal device (terminal device) and so on. For convenience of description, the devices mentioned above are collectively referred to as mobile terminals. The following describes the embodiments of the present invention in detail.

It should be noted that the mobile terminal in the embodiment of the present invention can be equipped with multiple biometric identification devices, that is, multiple biometric identification devices, which may include but not limited to: fingerprint identification devices, face recognition devices, iris Recognition device, vein recognition device, brainwave recognition device, electrocardiogram recognition device, etc., each biometric device has a corresponding recognition algorithm and recognition threshold, in addition, each biometric device has a corresponding The entered template, for example, the fingerprint recognition device has a corresponding preset fingerprint template, further, the fingerprint recognition device can collect a fingerprint image, when the matching value between the fingerprint image and the preset fingerprint template is greater than its corresponding recognition threshold , the identification is passed. The iris image in the embodiment of the present invention may refer to an image of an iris area alone, or an image including an iris area (for example, an image of a human eye). For example, when a user uses a mobile terminal, an iris image may be obtained through an iris recognition device.

Optionally, in the embodiment of the present invention, the mobile terminal in the embodiment of the present invention can store a variety of biometric identification patterns, and the biometric identification patterns can be one or more combinations of the following: fingerprint recognition pattern, face recognition pattern, iris pattern recognition mode, vein recognition mode, brain wave recognition mode, electrocardiogram recognition mode, etc. Perform fingerprint recognition first, and then perform iris recognition), and for another example, the biometric recognition mode can be iris recognition + fingerprint recognition (that is, in the unlocking process, it is necessary to perform iris recognition first, and then perform fingerprint recognition).

The following describes the embodiments of the present invention in detail. An example mobile terminal 1000 as shown in Figure 1A, the iris recognition device of the mobile terminal 1000 may include an infrared supplementary light 21 and an infrared camera 22, and during the working process of the iris recognition device, the light of the infrared supplementary light 21 hits After the iris is on, it is reflected back to the infrared camera 22 through the iris, and the iris recognition device collects the iris image. The front camera 23 can be used as a face recognition device, and the front camera 23 can be a camera module.

Please refer to FIG. 1B. FIG. 1B is a schematic structural diagram of a mobile terminal 100 shown, the mobile terminal 100 includes: an application processor AP110, a multi-biometric identification device 120, a ranging sensor 130, a memory 140 and an environment sensor 160, Wherein, the AP 110 is connected to the multi-biometric identification device 120 , the range sensor 130 , the memory 140 and the environment sensor 160 through the bus 150 . Wherein, the environment sensor 160 may be at least one of the following: a temperature sensor, a humidity sensor, a magnetic field detection sensor, an ambient light sensor and the like.

Optionally, the ranging sensor 130 is configured to detect the target distance between the target object and the mobile terminal;

The environment sensor 160 is used to acquire the current environment parameter set;

The AP110 is configured to determine a target biometric identification mode corresponding to the target distance and the current environment parameter set, and activate the target biometric identification mode.

Optionally, in terms of starting the target biometric identification mode, the AP110 is specifically used for:

Determine the control parameters of the supplementary light and the biological information collection parameters corresponding to the target biological identification mode according to the current environment parameter set;

Controlling the supplementary light to perform supplementary light according to the control parameters, and starting the target biometric identification mode according to the biometric information collection parameters.

Optionally, in terms of activating the target biometric identification mode, the AP110 is specifically used for:

Determine the identification parameter corresponding to the target biometric identification mode according to the current environment parameter set, and activate the target biometric identification mode according to the identification parameter, and the identification parameter is at least one of the following: identification threshold, identification algorithm, identification Region and Recognition Area.

Optionally, the memory 140 is used to pre-store P types of biometric identification patterns, where P is an integer greater than 1;

In terms of determining the target biometric pattern corresponding to the target distance and the current environment parameter set, the AP110 is specifically used for:

Selecting Q biometric patterns corresponding to the target distance from the P biometric patterns according to the correspondence between distances and biometric patterns, where Q is a positive integer smaller than P;

Evaluate the recognition success rate of the Q kinds of biometric recognition modes according to the current environment parameter set, and obtain Q evaluation values;

Selecting the biometric identification pattern corresponding to the largest evaluation value from the Q evaluation values as the target biometric identification pattern.

Optionally, the current environment parameter set includes k environment parameters, and k is a positive integer;

In terms of evaluating the recognition success rate of the Q kinds of biometric recognition patterns according to the current environment parameter set, and obtaining Q evaluation values, the AP110 is specifically used for:

Determine the weight and average recognition success rate corresponding to the first biometric identification pattern according to the K environmental parameters, and perform a weighted operation according to the weight and average recognition success rate corresponding to the first biometric identification pattern to obtain an evaluation value, the second biometric identification pattern A biometric identification mode is any one of the Q biometric identification modes.

Optionally, the face recognition device in the multiple biometrics recognition device 120 is configured to acquire a face image;

The AP110 is also specifically configured to determine the location information of the target object according to the face image, and the location information corresponds to a plurality of pixel points;

In terms of the target distance between the detection target object and the mobile terminal, the AP110 is used for:

Determine a distance value between each pixel point in the plurality of pixel points and the mobile terminal to obtain a plurality of distance values, and use an average value of the plurality of distance values as the target distance.

Based on the mobile terminal described above in FIG. 1A-FIG. 1B, the mobile terminal is used to perform the following unlocking control method, the method comprising:

The ranging sensor 130 is used to detect the target distance between the target object and the mobile terminal;

The environment sensor 160 is used to acquire the current environment parameter set;

The AP110 is configured to determine a target biometric identification mode corresponding to the target distance and the current environment parameter set, and activate the target biometric identification mode.

It can be seen that in the embodiment of the present invention, the mobile terminal can detect the target distance between the target object and the mobile terminal, obtain the current environment parameter set, determine the target biometric pattern corresponding to the target distance and the current environment parameter set, and activate the target Biometrics mode, it can be seen that the corresponding biometrics mode can be activated through distance and environment, and then, a reasonable biometrics mode can be automatically activated in different environments, which greatly facilitates users and improves the efficiency of multiple biometrics.

Please refer to FIG. 1C , which is a schematic flowchart of an embodiment of an unlocking control method provided by an embodiment of the present invention. The unlocking control method described in this embodiment is applied to a mobile terminal, and its physical diagram and structure diagram can be referred to in Fig. 1A-Fig. 1B, which includes the following steps:

101. Detect a target distance between a target object and a mobile terminal.

Wherein, the mobile terminal may detect the target distance between the target object and the mobile terminal through a ranging sensor, wherein the ranging sensor may be a laser range finder, an infrared range finder, a distance sensor, or the like. The target object can be a person or an object.

Optionally, the mobile terminal can also acquire a face image, and determine the position information of the target object according to the face image, and the position information corresponds to a plurality of pixel points; furthermore, in the above step 101, the detection target object and The target distance between mobile terminals can be implemented in the following manner:

Determine a distance value between each pixel point in the plurality of pixel points and the mobile terminal to obtain a plurality of distance values, and use an average value of the plurality of distance values as the target distance.

Wherein, the mobile terminal can use the face recognition device to obtain a face image, and determine the position information of the target object from the face image, and the position information can be understood as a plurality of pixel points. The distance between each pixel point and the mobile terminal in the multiple pixel points can be determined to obtain multiple distance values, and the mean value of the multiple distance values can be used as the target distance. Since multiple positions are used to determine the distance between the mobile terminal and the target object The obtained distance is more reliable.

Further optionally, the mobile terminal may also acquire a face image, and determine the location information of the target object according to the face image, which may include the following steps:

Acquiring a face image, performing image enhancement processing on the face image, and determining position information of the target object according to the face image after image enhancement processing.

Among them, image enhancement processing may include but not limited to: image denoising (for example, wavelet transform for image denoising), image restoration (for example, Wiener filtering), dark vision enhancement algorithms (for example, histogram equalization, gray scale stretching, etc.), after image enhancement processing is performed on the face image, the quality of the face image can be improved to a certain extent.

Optionally, the aforementioned acquisition of the face image and performing image enhancement processing on the face image may include the following steps A1-A2, specifically as follows:

A1, performing image quality evaluation on the face image to obtain an image quality evaluation value;

A2. When the image quality evaluation value is lower than a preset quality threshold, perform image enhancement processing on the face image.

Wherein, the above-mentioned preset quality threshold can be set by the user or defaulted by the system. First, the image quality evaluation of the face image can be performed to obtain an image quality evaluation value, and the quality of the face image can be judged by the image quality evaluation value. Whether the quality of the face image is good or bad , when the image quality evaluation value is greater than or equal to the preset quality threshold, it can be considered that the quality of the face image is good, and when the image quality evaluation value is less than the preset quality threshold, it can be considered that the quality of the face image is poor. Perform image enhancement processing.

Wherein, in the above step A1, at least one image quality evaluation index may be used to perform image quality evaluation on the face image, thereby obtaining an image quality evaluation value.

Of course, multiple image quality evaluation indexes can be used to evaluate the image quality of the face image, and each image quality evaluation index also corresponds to a weight. In this way, when each image quality evaluation index evaluates the image quality of the image, a weight can be obtained. The evaluation results are finally weighted to obtain the final image quality evaluation value. Image quality evaluation indicators may include, but are not limited to: mean value, standard deviation, entropy, sharpness, signal-to-noise ratio, and the like.

It should be noted that there are certain limitations when using a single evaluation index to evaluate image quality. Therefore, multiple image quality evaluation indexes can be used to evaluate image quality. Of course, when evaluating image quality, it is not the The more quality evaluation indicators, the better, because the more image quality evaluation indicators, the higher the computational complexity of the image quality evaluation process, and the better the image quality evaluation effect. Therefore, in the case of higher requirements for image quality evaluation , 2 to 10 image quality evaluation indicators can be used to evaluate the image quality. Specifically, the number of image quality evaluation indicators and which indicator to select depends on specific implementation conditions. Of course, the image quality evaluation index must be selected in combination with the specific scene, and the image quality evaluation index selected for image quality evaluation in a dark environment and image quality evaluation in a bright environment may be different.

Optionally, when the accuracy of image quality evaluation is not high, an image quality evaluation index can be used for evaluation. For example, the image quality evaluation value of the image to be processed is calculated by entropy. It can be considered that the greater the entropy, the better the image quality. Well, conversely, the smaller the entropy, the worse the image quality.

Optionally, in the case where the accuracy of the image quality evaluation is high, multiple image quality evaluation indicators can be used to evaluate the image, and when multiple image quality evaluation indicators are used to evaluate the image quality of the image, the multiple The weight of each image quality evaluation index in the image quality evaluation index can obtain multiple image quality evaluation values, and the final image quality evaluation value can be obtained according to the multiple image quality evaluation values and their corresponding weights, for example, three image quality evaluation values The quality evaluation indicators are: A index, B index and C index, the weight of A is a1, the weight of B is a2, and the weight of C is a3. When A, B and C are used to evaluate the image quality of an image, A The corresponding image quality evaluation value is b1, the image quality evaluation value corresponding to B is b2, and the image quality evaluation value corresponding to C is b3. Then, the final image quality evaluation value=a1b1+a2b2+a3b3. Generally, the larger the image quality evaluation value, the better the image quality.

102. Obtain the current environment parameter set.

Wherein, the current environment parameter set may include at least one environment parameter, and the environment parameters may include but not limited to: environment brightness, weather, humidity, temperature, magnetic field interference intensity, environment color and so on. When triggering the unlock operation, get the environment parameters. The mobile terminal can acquire the current environment parameter set through the environment sensor, and the environment sensor can be at least one of the following: temperature sensor, humidity sensor, magnetic field detection sensor, ambient light sensor and so on. Among them, the ambient brightness can be detected by the ambient light sensor, the weather can be obtained by the weather application APP, the magnetic field interference intensity can be detected by the magnetic field detection sensor, and the ambient color can be obtained by the camera.

103. Determine a target biometric identification mode corresponding to the target distance and the current environment parameter set, and activate the target biometric identification mode.

Wherein, the mapping relationship between the biometric pattern and the distance and the environmental parameter set can be pre-stored in the mobile terminal. After the target distance and the current environmental parameter set are determined, the target distance and the current environmental parameter set can be obtained according to the mapping relationship. The target biometric mode, and then, to activate the target biometric mode, the above description can be expressed by a formula, f(a, b)=c, where a represents the distance, b represents the environmental parameter set, c represents the biometric mode, and f It represents the mapping relationship between the biometric pattern and the distance and the environment parameter set. After the target biometric identification mode is activated, the unlocking operation can be performed in the target biometric identification mode.

Optionally, in step 103 above, activating the target biometric identification mode may include steps A11-A12, specifically as follows:

A11. Determine the control parameters of the supplementary light and the biological information collection parameters corresponding to the target biological recognition mode according to the current environmental parameter set;

A12. Control the supplementary light to perform supplementary light according to the control parameters, and activate the target biometric identification mode according to the biometric information collection parameters.

Wherein, the control parameters of the supplementary light may include but not limited to: control current, control voltage, control power, brightness of supplementary light, duration of supplementary light and so on. The biological information collection parameters mentioned above can be at least one of the following: collection voltage, collection current, collection power, fill light intensity, focusing time, whether to zoom, aperture size, exposure time, etc. The mapping relationship between the environmental parameter set and the supplementary light control parameters can be stored in advance in the mobile terminal. After the current environmental parameter set is determined, the current environment can be determined according to the mapping relationship between the environmental parameter set and the supplementary light control parameters. The control parameters of the fill light corresponding to the parameter set. Similarly, the mobile terminal can pre-store the mapping relationship between the environmental parameter set and the biological information collection parameters of the target biometric identification mode. After the current environmental parameter set is determined, it can The mapping relationship determines the biological information collection parameters corresponding to the current environment parameter set. Undoubtedly, in this way, the best control parameters of the supplementary light and the parameters of biological information collection can be obtained, thereby improving the quality of biological information collection and helping to improve the effect of subsequent multi-biological identification.

Optionally, in step 103 above, starting the target biometric identification mode can be implemented in the following manner:

Determine the identification parameter corresponding to the target biometric identification mode according to the current environment parameter set, and activate the target biometric identification mode according to the identification parameter, and the identification parameter is at least one of the following: identification threshold, identification algorithm, identification Region and Recognition Area.

Wherein, the mapping relationship between the environmental parameter set and the identification parameter corresponding to the target biometric pattern can be stored in the mobile terminal in advance, and then, after the current environmental parameter set is determined, the corresponding identification parameter corresponding to the current environmental parameter can be determined directly according to the mapping relationship. Identify parameters. The recognition parameter can be at least one of the following: recognition threshold, recognition algorithm, recognition area and recognition area, etc., wherein, the recognition threshold refers to that in the recognition process, if it is greater than the recognition threshold, the recognition can be considered successful, and the recognition algorithm refers to which method is used. The algorithm implements the recognition process. The recognition area can be understood as which part of an image is used for recognition. The recognition area can be understood as that not all areas in an image are used for recognition, as long as it reaches a certain area. Determine the identification parameters that are suitable for the environment, and set them more specifically for the environment, which can improve the efficiency of multi-biological identification.

Optionally, the mobile terminal further includes a memory connected to the AP, the memory is used to pre-store P types of biometric patterns, and the P is an integer greater than 1; in the above step 103, determine the The distance and the target biometric pattern corresponding to the current environment parameter set include the following steps B1-B3, specifically as follows:

B1. Selecting Q biometric patterns corresponding to the target distance from the P biometric patterns according to the correspondence between distances and biometric patterns, where Q is a positive integer smaller than P;

B2. Evaluate the recognition success rate of the Q kinds of biometric recognition patterns according to the current environment parameter set, and obtain Q evaluation values;

B3. Selecting the biometric identification pattern corresponding to the largest evaluation value from the Q evaluation values as the target biometric identification pattern.

Wherein, P types of biometric identification modes are pre-stored in the mobile terminal, P is an integer greater than 1, and the corresponding relationship between the storage distance and the biometric identification mode, of course, the distance in the above corresponding relationship can be a specific value, or it can be One range value and one distance can correspond to multiple biometric identification modes. Therefore, it is possible to select Q biological identification modes corresponding to the target distance from P biological identification modes according to the correspondence between distances and biological identification modes, and Q is a positive integer less than P. The above corresponding relationship can refer to the following table:

In addition, the mobile terminal can evaluate the recognition success rate of Q kinds of biometric identification modes according to the current environment parameter set, and can obtain Q evaluation values, and select the biometric identification mode corresponding to the largest evaluation value from the Q evaluation values as the target biometric identification mode . In this way, the most suitable biometric mode for the environment can be selected from a variety of biometric modes, which is beneficial to improve the efficiency of multi-biological identification.

Further optionally, the current environmental parameter set includes k environmental parameters. In the above step B2, the recognition success rate of the Q biometric identification modes is evaluated according to the current environmental parameter set to obtain Q evaluation values, This can be achieved as follows:

Determine the weight and average recognition success rate corresponding to the first biometric identification pattern according to the K environmental parameters, and perform a weighted operation according to the weight and average recognition success rate corresponding to the first biometric identification pattern to obtain an evaluation value, the second biometric identification pattern A biometric identification mode is any one of the Q biometric identification modes.

Among them, the mobile terminal can analyze the historical unlock records in advance, and analyze the average recognition success rate corresponding to each environmental parameter in each specific environment. In addition, the weight can be set by the user, or the system defaults, or is determined by the system. The analysis is obtained (for example, analyze the historical unlocking records, count the number of times the user uses each biometric mode, and determine the weight according to the number of times of use. The more times of use, the greater the weight). Each of the Q biometric modes is analyzed to obtain its corresponding evaluation value. Taking the first biometric mode as an example, it is any of the above Q biometric modes. The first biometric The weight corresponding to the recognition mode and the average recognition success rate are weighted. The weight corresponding to the first biometric recognition mode and the average recognition success rate are shown in the table below. After weighted calculation, the evaluation value = A1*B1+A2*B2 +A3*B3+…+Ak*Bk.

Environment parameter set Weights Recognition success rate Environmental parameter 1 A1 B1 Environmental parameters 2 A2 B2 Environmental parameters 3 A3 B3 … … … Environmental parameter k Ak Bk

It can be seen that in the embodiment of the present invention, the mobile terminal can detect the target distance between the target object and the mobile terminal, obtain the current environment parameter set, determine the target biometric pattern corresponding to the target distance and the current environment parameter set, and activate the target Biometrics mode, it can be seen that the corresponding biometrics mode can be activated through distance and environment, and then, a reasonable biometrics mode can be automatically activated in different environments, which greatly facilitates users and improves the efficiency of multiple biometrics.

Please refer to FIG. 2 , which is a schematic flowchart of an embodiment of an unlocking control method provided by an embodiment of the present invention. The unlocking control method described in this embodiment is applied to a mobile terminal, and its physical diagram and structure diagram can be referred to in Fig. 1A-Fig. 1B, which includes the following steps:

201. Acquire a face image, and determine position information of a target object according to the face image, where the position information corresponds to a plurality of pixel points.

Wherein, the mobile terminal can use the face recognition device to obtain a face image, and determine the position information of the target object from the face image, and the position information can be understood as a plurality of pixel points. The distance between each pixel point and the mobile terminal in the multiple pixel points can be determined to obtain multiple distance values, and the mean value of the multiple distance values can be used as the target distance. Since multiple positions are used to determine the distance between the mobile terminal and the target object The obtained distance is more reliable.

202. Determine a distance value between each pixel point in the plurality of pixel points and the mobile terminal to obtain a plurality of distance values, and use an average value of the plurality of distance values as a target distance.

203. Obtain the current environment parameter set.

204. Determine a target biometric identification mode corresponding to the target distance and the current environment parameter set, and activate the target biometric identification mode.

Wherein, for the specific description of the above steps 201-204, reference may be made to the corresponding steps of the unlocking control method described in FIG. 1 .

It can be seen that, in the embodiment of the present invention, the mobile terminal can obtain the face image, and determine the position information of the target object according to the face image, the position information corresponds to a plurality of pixel points, and each pixel point in the plurality of pixel points is determined and the distance value between the mobile terminal, obtain multiple distance values, and use the mean value of the multiple distance values as the target distance, obtain the current environment parameter set, determine the target biometric pattern corresponding to the target distance and the current environment parameter set, and Starting the target biometric mode, it can be seen that the corresponding biometric mode can be activated according to the distance and the environment, and then a reasonable biometric mode can be automatically activated in different environments, which greatly facilitates the user and improves the efficiency of multi-biometric identification.

Please refer to FIG. 3. FIG. 3 is a mobile terminal provided by an embodiment of the present invention, including: an application processor AP and a memory; and one or more programs, the one or more programs are stored in the memory, And configured to be executed by the AP, the program includes instructions for performing the following steps:

Detect the target distance between the target object and the mobile terminal;

Get the current environment parameter set;

A target biometric identification mode corresponding to the target distance and the current environment parameter set is determined, and the target biometric identification mode is activated.

In one possible example, with respect to said activating said target biometric mode, said program includes instructions for performing the following steps:

Determine the control parameters of the supplementary light and the biological information collection parameters corresponding to the target biological identification mode according to the current environment parameter set;

Controlling the supplementary light to perform supplementary light according to the control parameters, and starting the target biometric identification mode according to the biometric information collection parameters.

In one possible example, with respect to said activating said target biometric mode, said program includes instructions for performing the following steps:

Determine the identification parameter corresponding to the target biometric identification mode according to the current environment parameter set, and activate the target biometric identification mode according to the identification parameter, and the identification parameter is at least one of the following: identification threshold, identification algorithm, identification Region and Recognition Area.

In a possible example, P types of biometric identification patterns are pre-stored in the memory, where P is an integer greater than 1. In terms of determining the target biometric identification pattern corresponding to the target distance and the current environment parameter set, The program includes instructions for performing the following steps:

Selecting Q biometric patterns corresponding to the target distance from the P biometric patterns according to the correspondence between distances and biometric patterns, where Q is a positive integer smaller than P;

Evaluate the recognition success rate of the Q kinds of biometric recognition modes according to the current environment parameter set, and obtain Q evaluation values;

Selecting the biometric identification pattern corresponding to the largest evaluation value from the Q evaluation values as the target biometric identification pattern.

In a possible example, the current environment parameter set includes k environment parameters, and k is a positive integer; in the evaluation of the recognition success rate of the Q biometric patterns according to the current environment parameter set , in terms of obtaining Q evaluation values, the program includes instructions for performing the following steps:

Determine the weight and average recognition success rate corresponding to the first biometric identification pattern according to the K environmental parameters, and perform a weighted operation according to the weight and average recognition success rate corresponding to the first biometric identification pattern to obtain an evaluation value, the second biometric identification pattern A biometric identification mode is any one of the Q biometric identification modes.

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

Acquiring a face image, and determining position information of the target object according to the face image, where the position information corresponds to a plurality of pixel points;

In terms of the target distance between the detection target object and the mobile terminal, the program includes instructions for performing the following steps:

Determine a distance value between each pixel point in the plurality of pixel points and the mobile terminal to obtain a plurality of distance values, and use an average value of the plurality of distance values as the target distance.

Please refer to FIG. 4A . FIG. 4A is a schematic structural diagram of an unlocking control device provided in this embodiment. The unlocking control device is applied to a mobile terminal, and the unlocking control device includes a detection unit 401, a first acquisition unit 402, and a processing unit 403, wherein,

A detection unit 401, configured to detect the target distance between the target object and the mobile terminal;

The first acquiring unit 402 is configured to acquire the current environment parameter set;

The processing unit 403 is configured to determine a target biometric identification mode corresponding to the target distance and the current environment parameter set, and activate the target biometric identification mode.

Optionally, in terms of starting the target biometric identification mode, the processing unit 403 is specifically configured to:

Determine the control parameters of the supplementary light and the biological information collection parameters corresponding to the target biological identification mode according to the current environment parameter set;

Controlling the supplementary light to perform supplementary light according to the control parameters, and starting the target biometric identification mode according to the biometric information collection parameters.

Optionally, in terms of activating the target biometric identification mode, the processing unit 403 is specifically configured to:

Determine the identification parameter corresponding to the target biometric identification mode according to the current environment parameter set, and activate the target biometric identification mode according to the identification parameter, and the identification parameter is at least one of the following: identification threshold, identification algorithm, identification Region and Recognition Area.

Optionally, P types of biometric identification patterns are pre-stored in the mobile terminal, where P is an integer greater than 1;

When determining the target biometric pattern corresponding to the target distance and the current environment parameter set, the processing unit 403 is specifically configured to:

Selecting Q biometric patterns corresponding to the target distance from the P biometric patterns according to the correspondence between distances and biometric patterns, where Q is a positive integer smaller than P;

Evaluate the recognition success rate of the Q kinds of biometric recognition modes according to the current environment parameter set, and obtain Q evaluation values;

Selecting the biometric identification pattern corresponding to the largest evaluation value from the Q evaluation values as the target biometric identification pattern.

Optionally, the current environment parameter set includes k environment parameters, and k is a positive integer;

In terms of evaluating the recognition success rate of the Q kinds of biometric recognition patterns according to the current environment parameter set, and obtaining Q evaluation values, the processing unit 403 is specifically used for:

Determine the weight and average recognition success rate corresponding to the first biometric identification pattern according to the K environmental parameters, and perform a weighted operation according to the weight and average recognition success rate corresponding to the first biometric identification pattern to obtain an evaluation value, the second biometric identification pattern A biometric identification mode is any one of the Q biometric identification modes.

Optionally, as shown in FIG. 4B, FIG. 4B is another modified structure of the unlocking control device described in FIG. 4A. Compared with the mobile terminal described in FIG. 4A, it may further include: a second acquiring unit 404 and a determining unit 405 ,details as follows:

A second acquiring unit 404, configured to acquire a face image;

The determination unit 405 is configured to determine the position information of the target object according to the face image, the position information corresponds to a plurality of pixels; For the distance value between the mobile terminals, a plurality of distance values are obtained, and an average value of the plurality of distance values is used as the target distance.

It can be seen that the unlocking control device described in the embodiment of the present invention can detect the target distance between the target object and the mobile terminal, obtain the current environment parameter set, and determine the target biometric pattern corresponding to the target distance and the current environment parameter set , and start the target biometric mode, it can be seen that the corresponding biometric mode can be activated through the distance and the environment, and then a reasonable biometric mode can be automatically activated in different environments, which greatly facilitates the user and improves the efficiency of multi-biometric identification.

It can be understood that the functions of the program modules of the unlocking control device in this embodiment can be specifically implemented according to the method in the above method embodiment, and the specific implementation process can refer to the relevant description of the above method embodiment, and will not be repeated here.

The embodiment of the present invention also provides another mobile terminal, as shown in Fig. 5, for the convenience of description, only the parts related to the embodiment of the present invention are shown, and the specific technical details are not disclosed, please refer to the method of the embodiment of the present invention part. The mobile terminal can be any terminal device including a mobile phone, tablet computer, PDA (Personal Digital Assistant, personal digital assistant), POS (Point of Sales, sales terminal), vehicle-mounted computer, etc. Taking the mobile terminal as a mobile phone as an example:

FIG. 5 shows a block diagram of a partial structure of a mobile phone related to the mobile terminal provided by the embodiment of the present invention. Referring to FIG. 5 , the mobile phone includes: a radio frequency (Radio Frequency, RF) circuit 910, a memory 920, an input unit 930, a sensor 950, an audio circuit 960, a wireless fidelity (Wireless Fidelity, WiFi) module 970, an application processor AP980, and a power supply 990 and other components. Those skilled in the art can understand that the structure of the mobile phone shown in FIG. 5 is not limited to the mobile phone, and may include more or less components than shown in the figure, or combine some components, or arrange different components.

The following is a specific introduction to each component of the mobile phone in conjunction with Figure 5:

The input unit 930 can be used to receive input numbers or character information, and generate key signal input related to user settings and function control of the mobile phone. Specifically, the input unit 930 may include a touch screen 933 , multiple biometric identification devices 931 and other input devices 932 . The input unit 930 may also include other input devices 932 . Specifically, other input devices 932 may include but not limited to one or more of physical keys, function keys (such as volume control keys, switch keys, etc.), trackball, mouse, joystick, and the like.

The AP980 is used to perform the following steps:

Detect the target distance between the target object and the mobile terminal;

Get the current environment parameter set;

A target biometric identification mode corresponding to the target distance and the current environment parameter set is determined, and the target biometric identification mode is activated.

AP980 is the control center of the mobile phone. It uses various interfaces and lines to connect various parts of the entire mobile phone. By running or executing software programs and/or modules stored in the memory 920, and calling data stored in the memory 920, the mobile phone is executed. Various functions and processing data, so as to monitor the mobile phone as a whole. Optionally, the AP980 may include one or more processing units; preferably, the AP980 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface and application programs, etc., and the modem The processor mainly handles wireless communication. It can be understood that the above-mentioned modem processor may not be integrated into the AP980.

In addition, the memory 920 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage devices.

RF circuitry 910 may be used for the reception and transmission of information. Generally, the RF circuit 910 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier (Low Noise Amplifier, LNA), a duplexer, and the like. In addition, RF circuitry 910 may also communicate with networks and other devices via wireless communications. The above wireless communication can use any communication standard or protocol, including but not limited to Global System of Mobile Communication (Global System of Mobilecommunication, GSM), General Packet Radio Service (General Packet Radio Service, GPRS), Code Division Multiple Access (Code Division Multiple Access, CDMA), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), email, Short Messaging Service (Short Messaging Service, SMS), etc.

The handset may also include at least one sensor 950, such as a light sensor, motion sensor, and other sensors. Specifically, the light sensor can 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 screen when the mobile phone is moved to the ear. and/or backlighting. As a kind of motion sensor, the accelerometer sensor can detect the magnitude of acceleration in various directions (generally three axes), and can detect the magnitude and direction of gravity when it is stationary, and can be used to identify the application of mobile phone posture (such as horizontal and vertical screen switching, related Games, magnetometer attitude calibration), vibration recognition related functions (such as pedometer, tap), etc.; as for other sensors such as gyroscope, barometer, hygrometer, thermometer, infrared sensor, etc. repeat.

The audio circuit 960, the speaker 961, and the microphone 962 can provide an audio interface between the user and the mobile phone. The audio circuit 960 can transmit the electrical signal converted from the received audio data to the loudspeaker 961, and the loudspeaker 961 converts it into a sound signal for playback; After being received, it is converted into audio data, and then the audio data is processed by the playback AP980, and then sent to another mobile phone through the RF circuit 910, or the audio data is played to the memory 920 for further processing.

WiFi is a short-distance wireless transmission technology. The mobile phone can help users send and receive emails, browse web pages, and access streaming media through the WiFi module 970. It provides users with wireless broadband Internet access. Although Fig. 5 shows the WiFi module 970, it can be understood that it is not an essential component of the mobile phone, and can be completely omitted according to needs without changing the essence of the invention.

The mobile phone also includes a power supply 990 (such as a battery) for supplying power to each component. Preferably, the power supply can be logically connected to the AP980 through the power management system, so that functions such as charging, discharging, and power consumption management can be realized through the power management system.

Although not shown, the mobile phone may also include a camera, a Bluetooth module, etc., which will not be repeated here.

In the aforementioned embodiments shown in FIG. 1C and FIG. 2 , the method flow of each step can be realized based on the structure of the mobile phone.

In the aforementioned embodiments shown in FIG. 3 , FIG. 4A , and FIG. 4B , the functions of each unit can be realized based on the structure of the mobile phone.

An embodiment of the present invention also provides a computer storage medium, wherein the computer storage medium is used to store a computer program, and the computer program enables the computer to execute some or all steps of any unlocking control method described in the above method embodiments.

An embodiment of the present invention also provides a computer program product, the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the method described in the above method embodiments. Part or all of the steps of any unlocking control method.

It should be noted that for the foregoing method embodiments, for the sake of simple description, they are expressed as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence. Because of the present invention, certain steps may be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification belong to preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

In the foregoing embodiments, the descriptions of each embodiment have their own emphases, and for parts not described in detail in a certain embodiment, reference may be made to relevant descriptions of other embodiments.

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

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

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit. The above-mentioned integrated units can be implemented not only in the form of hardware, but also in the form of software program modules.

The integrated units may be stored in a computer-readable memory if implemented in the form of a software program module and sold or used as an independent product. Based on this understanding, the essence of 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, and the computer software product is stored in a memory. Several instructions are included to make a computer device (which may be a personal computer, server or network device, etc.) execute all or part of the steps of the methods described in the various embodiments 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 codes.

Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above-mentioned embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, and the memory can include: a flash disk , Read-only memory (English: Read-Only Memory, abbreviated: ROM), random access device (English: Random Access Memory, abbreviated: RAM), magnetic disk or optical disk, etc.

The embodiments of the present invention have been described in detail above, and specific examples have been used in this paper to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only used to help understand the method and core idea of the present invention; at the same time, for Those skilled in the art will have changes in the specific implementation and scope of application according to the idea of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims (16)

1. A kind of 1. mobile terminal, it is characterised in that including application processor AP, and with the AP environmental sensors being connected and Distance measuring sensor, wherein,

   The distance measuring sensor, for the target range between detected target object and mobile terminal；

   The environmental sensor, for obtaining current environment parameter set；

   The AP, for determining target organism identification mould corresponding with the target range and the current environment parameter set Formula, and start the target organism recognition mode.
2. 2. mobile terminal according to claim 1, it is characterised in that start the target organism recognition mode side described Face, the AP are specifically used for:

   According to corresponding to the current environment parameter set determines control parameter and the target organism recognition mode of light compensating lamp Biomedical information acquisition parameter；

   Control light compensating lamp to carry out light filling according to the control parameter, and the target is started according to the biomedical information acquisition parameter Bio-identification pattern.
3. 3. mobile terminal according to claim 1, it is characterised in that start the target organism recognition mode side described Face, the AP are specifically used for：

   Identification parameter corresponding with the target organism recognition mode is determined according to the current environment parameter set, and according to the knowledge Other parameter starts the target organism recognition mode, and the identification parameter is following at least one：Recognition threshold, recognizer, Identification region and identification area.
4. 4. according to the mobile terminal described in claim any one of 1-3, it is characterised in that the mobile terminal also include with it is described The memory of AP connections, the memory are used to prestore P kind bio-identification patterns, and the P is the integer more than 1；

   In terms of determination target organism recognition mode corresponding with the target range and the current environment parameter set, The AP is specifically used for：

   Chosen and the target from the P kinds bio-identification pattern according to the corresponding relation between distance and bio-identification pattern Q kind bio-identification patterns corresponding to distance, the Q are the positive integer less than the P；

   The recognition success rate of the Q kinds bio-identification pattern is evaluated according to the current environment parameter set, Q is obtained and comments Value；

   Bio-identification pattern corresponding to maximum evaluation of estimate is chosen from the Q evaluation of estimate and identifies mould as the target organism Formula.
5. 5. mobile terminal according to claim 4, it is characterised in that the current environment parameter set, which includes k environment, joins Number, the k is positive integer；

   The recognition success rate of the Q kinds bio-identification pattern is evaluated according to the current environment parameter set described, obtained In terms of Q evaluation of estimate, the AP is specifically used for：

   Weight and average recognition success rate according to corresponding to the K ambient parameter determines the first bio-identification pattern, and root It is weighted according to weight corresponding to the first bio-identification pattern and average recognition success rate, obtains evaluation of estimate, institute The first bio-identification pattern is stated as any bio-identification pattern in the Q kinds bio-identification pattern.
6. 6. according to the mobile terminal described in claim any one of 1-3, it is characterised in that the mobile terminal also include with it is described The face identification device of AP connections, the face identification device, for obtaining facial image；

   The AP is also particularly useful for the positional information that the destination object is determined according to the facial image, the positional information pair Answer multiple pixels；

   In terms of target range between the detected target object and mobile terminal, the AP is specifically used for：

   The distance between each pixel and the mobile terminal value in the multiple pixel are determined, obtains multiple distance values, And using the average of the multiple distance value as the target range.
7. 7. one kind solution lock control method, it is characterised in that applied to including application processor AP, and the ring being connected with the AP The mobile terminal of border sensor and distance measuring sensor, methods described include：

   The distance measuring sensor, for the target range between detected target object and mobile terminal；

   The environmental sensor, for obtaining current environment parameter set；

   The AP, for determining target organism identification mould corresponding with the target range and the current environment parameter set Formula, and start the target organism recognition mode.
8. 8. one kind solution lock control method, it is characterised in that including：

   Target range between detected target object and mobile terminal；

   Obtain current environment parameter set；

   It is determined that target organism recognition mode corresponding with the target range and the current environment parameter set, and described in startup Target organism recognition mode.
9. 9. according to the method for claim 8, it is characterised in that the startup target organism recognition mode, including:

   According to corresponding to the current environment parameter set determines control parameter and the target organism recognition mode of light compensating lamp Biomedical information acquisition parameter；

   Control light compensating lamp to carry out light filling according to the control parameter, and the target is started according to the biomedical information acquisition parameter Bio-identification pattern.
10. 10. according to the method for claim 8, it is characterised in that the startup target organism recognition mode, including：

    Identification parameter corresponding with the target organism recognition mode is determined according to the current environment parameter set, and according to the knowledge Other parameter starts the target organism recognition mode, and the identification parameter is following at least one：Recognition threshold, recognizer, Identification region and identification area.
11. 11. according to the method described in claim any one of 8-10, it is characterised in that prestore P kinds in the mobile terminal Bio-identification pattern, the P are the integer more than 1；

    It is described to determine corresponding with the target range and current environment parameter set target organism recognition mode, including：

    Chosen and the target from the P kinds bio-identification pattern according to the corresponding relation between distance and bio-identification pattern Q kind bio-identification patterns corresponding to distance, the Q are the positive integer less than the P；

    The recognition success rate of the Q kinds bio-identification pattern is evaluated according to the current environment parameter set, Q is obtained and comments Value；

    Bio-identification pattern corresponding to maximum evaluation of estimate is chosen from the Q evaluation of estimate and identifies mould as the target organism Formula.
12. 12. according to the method for claim 11, it is characterised in that the current environment parameter set includes k ambient parameter, The k is positive integer；

    It is described that the recognition success rate of the Q kinds bio-identification pattern is evaluated according to the current environment parameter set, obtain Q Individual evaluation of estimate, including：

    Weight and average recognition success rate according to corresponding to the K ambient parameter determines the first bio-identification pattern, and root It is weighted according to weight corresponding to the first bio-identification pattern and average recognition success rate, obtains evaluation of estimate, institute The first bio-identification pattern is stated as any bio-identification pattern in the Q kinds bio-identification pattern.
13. 13. according to the method described in claim any one of 8-10, it is characterised in that methods described also includes：

    Facial image is obtained, and the positional information of the destination object, the positional information pair are determined according to the facial image Answer multiple pixels；

    Target range between the detected target object and mobile terminal, including：

    The distance between each pixel and the mobile terminal value in the multiple pixel are determined, obtains multiple distance values, And using the average of the multiple distance value as the target range.
14. 14. one kind solution lock control device, it is characterised in that including：

    Detection unit, for the target range between detected target object and mobile terminal；

    Determining unit, for obtaining current environment parameter set；

    Processing unit, for determining target organism identification mould corresponding with the target range and the current environment parameter set Formula, and start the target organism recognition mode.
15. A kind of 15. mobile terminal, it is characterised in that including：Application processor AP and memory；And one or more programs, One or more of programs are stored in the memory, and are configured to be performed by the AP, and described program includes Instruction for such as any one of claim 8-13 methods.
16. A kind of 16. computer-readable recording medium, it is characterised in that it is used to store computer program, wherein, the computer Program causes computer to perform the method as described in claim any one of 8-13.