WO2019015575A1 - 解锁控制方法及相关产品 - Google Patents

解锁控制方法及相关产品 Download PDF

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Publication number
WO2019015575A1
WO2019015575A1 PCT/CN2018/095942 CN2018095942W WO2019015575A1 WO 2019015575 A1 WO2019015575 A1 WO 2019015575A1 CN 2018095942 W CN2018095942 W CN 2018095942W WO 2019015575 A1 WO2019015575 A1 WO 2019015575A1
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WO
WIPO (PCT)
Prior art keywords
biometric
information
electronic device
identification
identification threshold
Prior art date
Application number
PCT/CN2018/095942
Other languages
English (en)
French (fr)
Inventor
周意保
张海平
Original Assignee
Oppo广东移动通信有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Application filed by Oppo广东移动通信有限公司 filed Critical Oppo广东移动通信有限公司
Priority to US16/624,229 priority Critical patent/US11055547B2/en
Priority to EP18835435.1A priority patent/EP3637290B1/en
Publication of WO2019015575A1 publication Critical patent/WO2019015575A1/zh

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31User authentication
    • G06F21/32User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/12Fingerprints or palmprints
    • G06V40/1365Matching; Classification
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/60Static or dynamic means for assisting the user to position a body part for biometric acquisition
    • G06V40/63Static or dynamic means for assisting the user to position a body part for biometric acquisition by static guides
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/70Multimodal biometrics, e.g. combining information from different biometric modalities
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W12/00Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/06Authentication
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L2463/00Additional details relating to network architectures or network communication protocols for network security covered by H04L63/00
    • H04L2463/082Additional details relating to network architectures or network communication protocols for network security covered by H04L63/00 applying multi-factor authentication
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02DCLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00Reducing energy consumption in communication networks
    • Y02D30/70Reducing energy consumption in communication networks in wireless communication networks

Definitions

  • the present application relates to the field of electronic device technologies, and in particular, to an unlock control method and related products.
  • multi-biometric identification is increasingly favored by electronic equipment manufacturers, but in the state of motion, because the electronic equipment is also in motion, it will cause the collected biological information (for example, fingerprint image) to be blurred, thereby Reduce the efficiency of multiple biometrics.
  • the embodiment of the present application provides an unlocking control method and related products, so as to improve the efficiency of multiple biometrics.
  • an embodiment of the present application provides an electronic device, including: a motion sensor, an application processor AP, a memory, a first biometric device, and a second biometric device, the motion sensor, the memory, and the a biometric identification device and the second biometric identification device are both connected to the AP, wherein
  • the motion sensor is configured to detect whether the electronic device is in a motion state
  • the first biometric identification device is configured to acquire first biometric information
  • the memory is configured to store first preset biometric template information
  • the AP is configured to lower the first identification threshold when the electronic device is in a motion state, to obtain a second identification threshold
  • the second biometric identification device is configured to acquire second biometric information when a matching value between the first biometric identification information and the first preset biometric template information is greater than the second identification threshold;
  • the AP performs an identification operation on the second biometric identification information.
  • an unlocking control method including:
  • an unlocking control apparatus including:
  • a detecting unit configured to detect whether the electronic device is in a motion state
  • a lowering unit configured to lower the first identification threshold when the electronic device is in a motion state, to obtain a second identification threshold
  • An obtaining unit configured to acquire first biometric information
  • a processing unit configured to acquire second biometric information and compare the second biometric information when a matching value between the first biometric identification information and the first preset biometric template information is greater than the second identification threshold The information is identified.
  • an embodiment of the present application provides an electronic device, an application processor AP and a memory, and one or more programs, where the one or more programs are stored in the memory, and configured to be The AP is executed, and the program includes instructions for performing some or all of the steps described in the second aspect.
  • the embodiment of the present application provides a computer readable storage medium, wherein the computer readable storage medium is used for storing a computer program, wherein the computer program causes the computer to perform a second embodiment as in the present application.
  • an embodiment of the present application provides a computer program product, where the computer program product includes a non-transitory computer readable storage medium storing a computer program, the computer program being operative to cause a computer to execute Apply some or all of the steps described in the second aspect of the embodiments.
  • the computer program product can be a software installation package.
  • detecting whether the electronic device is in a motion state when the electronic device is in a motion state, lowering the first recognition threshold, obtaining a second identification threshold, and acquiring the first biometric information, in the first biometric identification
  • the matching value between the information and the first preset biometric template information is greater than the second identification threshold
  • acquiring the second biometric identification information and performing the identification operation on the second threshold biometric identification information so that the electronic device is in the motion state
  • the recognition threshold is lowered, thereby improving the efficiency of multi-biometric recognition.
  • FIG. 1A is a schematic structural diagram of a smart phone disclosed in an embodiment of the present application.
  • 1B is a schematic structural diagram of an electronic device disclosed in an embodiment of the present application.
  • 1C is a schematic flowchart of an unlocking control method disclosed in an embodiment of the present application.
  • FIG. 2 is a schematic flow chart of another unlocking control method disclosed in an embodiment of the present application.
  • FIG. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
  • 4A is a schematic structural diagram of an unlocking control apparatus according to an embodiment of the present application.
  • FIG. 4B is a schematic structural diagram of a detecting unit of the unlocking control device described in FIG. 4A according to an embodiment of the present application;
  • FIG. 4C is a schematic structural diagram of a lowering unit of the unlocking control device described in FIG. 4A according to an embodiment of the present application;
  • 4D is a schematic structural diagram of an acquiring unit of the unlocking control device described in FIG. 4A according to an embodiment of the present application;
  • FIG. 4E is another schematic structural diagram of the unlocking control device described in FIG. 4A according to an embodiment of the present application.
  • FIG. 5 is a schematic structural diagram of another electronic device disclosed in the embodiment of the present application.
  • references to "an embodiment” herein mean that a particular feature, structure, or characteristic described in connection with the embodiments can be included in at least one embodiment of the present application.
  • the appearances of the phrases in various places in the specification are not necessarily referring to the same embodiments, and are not exclusive or alternative embodiments that are mutually exclusive. Those skilled in the art will understand and implicitly understand that the embodiments described herein can be combined with other embodiments.
  • the electronic device involved in the embodiments of the present application may include various handheld devices having wireless communication functions, in-vehicle devices, wearable devices, computing devices, or other processing devices connected to the wireless modem, and various forms of user devices (user Equipment, UE), mobile station (MS), terminal device, etc.
  • user Equipment user Equipment
  • MS mobile station
  • terminal device etc.
  • the devices mentioned above are collectively referred to as electronic devices.
  • the embodiments of the present application are described in detail below.
  • the electronic device in the embodiment of the present application may be installed with multiple biometric devices, and the multiple biometric device includes a plurality of biometric devices, and the plurality of biometric devices may include at least two biometric devices: fingerprint Identification device, iris recognition device, face recognition device, vein recognition device, brain wave recognition device, electrocardiogram recognition device, etc., each biometric device has a corresponding recognition algorithm and an identification threshold, and each biometric device There is a template corresponding to the user and pre-recorded by the user.
  • the fingerprint identification device has a preset fingerprint template corresponding thereto.
  • the fingerprint recognition device can collect the fingerprint image between the fingerprint image and the preset fingerprint template. When the matching value is greater than its corresponding recognition threshold, the recognition is passed.
  • the multiple biometric mode in the embodiment of the present application may include two or more recognition steps, for example, fingerprint recognition, face recognition after fingerprint recognition, or fingerprint recognition and face recognition. Synchronization. Multi-biometric recognition mode is more secure than single biometric recognition mode (for example, unlocking only by fingerprint recognition), and thus, multiple biometric recognition modes are becoming more and more popular.
  • the first biometric information may include, but is not limited to, fingerprint information, iris information, face information, vein information, brain wave information, electrocardiogram information, and the like.
  • the second biometric information may include, but is not limited to, fingerprint information, iris information, face information, vein information, brain wave information, electrocardiogram information, and the like.
  • the first biometric identification device is configured to collect the first biometric identification information
  • the first biometric identification device may be one of the following: a fingerprint identification device, an iris recognition device, a face recognition device, a vein recognition device, and an electroencephalogram recognition device. , ECG recognition device, etc.
  • the second biometric device is configured to collect the second biometric identification information
  • the second biometric identification device may be one of the following: a fingerprint identification device, an iris recognition device, a face recognition device, a vein recognition device, and a brain wave recognition device. , ECG recognition device, etc.
  • the first biometric information may be different from the second biometric information category, for example, the first biometric information is fingerprint information, the second biometric information is iris information, and, for example, the first biometric information is iris information.
  • the second biometric information is face information.
  • the first biometric information is face information
  • the second biometric information is iris information.
  • the iris recognition device of the smart phone 1000 may include an infrared fill light 21 and an infrared camera 22. During the operation of the iris recognition device, the light of the infrared fill light 21 is hit. After the iris is reflected back to the infrared camera 22 through the iris, the iris recognition device collects the iris image, and the front camera 23 can be used as a face recognition device.
  • FIG. 1B is a schematic structural diagram of an electronic device 100.
  • the electronic device 100 includes an application processor AP110, a first biometric device 120, and a second biometric device 130.
  • the bus 150 connects the first biometric device 120, the second biometric device 130, the motion sensor 160, and the memory 140.
  • the motion sensor 160 is configured to detect whether the electronic device is in a motion state
  • the first biometric device 120 is configured to acquire first biometric information
  • the memory 140 is configured to store first preset biometric template information
  • the AP 110 is configured to: when the electronic device is in a motion state, lower the first identification threshold to obtain a second identification threshold;
  • the second biometric identification device 130 is configured to acquire second biometric information when a matching value between the first biometric identification information and the first preset biometric template information is greater than the second identification threshold;
  • the AP 110 performs an identification operation on the second biometric information.
  • the motion sensor 160 in the detecting whether the electronic device is in a motion state, is specifically configured to:
  • the AP 110 is specifically configured to:
  • the first biometric device 120 is specifically configured to:
  • the AP 110 is also specifically configured to:
  • the AP 110 is specifically configured to:
  • the AP 110 is also specifically configured to:
  • the matching value between the first biometric information and the first preset biometric template information is less than or equal to the second identification threshold, prompting the user to re-enter the first biometric information.
  • FIG. 1C is a schematic flowchart of an embodiment of an unlocking control method according to an embodiment of the present application, which is applied to an electronic device, and a physical map or a structural diagram of the electronic device may be referred to FIG. 1A or FIG. 1B.
  • the described unlock control method includes the following steps:
  • the electronic device can detect whether it is in motion by the following sensors, such as an acceleration sensor, a displacement sensor, a vibration sensor, a pedometer sensor, a gyroscope, and the like.
  • the following step 102 can be performed if the electronic device is in motion.
  • detecting whether the electronic device is in a motion state may include the following steps:
  • A3. Detect whether the electronic device is in a motion state according to the feature parameter.
  • the gyroscope in the lens also moves along, so that it can record the motion state in a period of time
  • the motion state is the motion curve
  • the horizontal axis is the time axis
  • longitudinal is the displacement from the equilibrium position.
  • characteristic parameters can be derived from the motion profile, which can include, but are not limited to, speed, acceleration, amplitude, and the like. These characteristic parameters can be used to detect whether the electronic device is in motion.
  • detecting whether the electronic device is in a motion state according to the feature parameter may be implemented as follows:
  • the first threshold and the second threshold may be set by the user or the system defaults.
  • detecting whether the electronic device is in a motion state may include the following steps:
  • the obtained image is likely to be blurred. Therefore, if multiple images are taken, it can be judged whether each image is blurred, and if so, the electronic device is in motion. For example, if three images are taken and all three images are blurred, the electronic device is in motion.
  • the following method may be employed: determining a blurred area of any image, and if the area of the blurred area is larger than a preset blurred area, it is confirmed that the image is blurred.
  • the image may be blurred. Therefore, the first recognition threshold may be appropriately reduced to obtain a second recognition threshold, thereby improving the recognition efficiency.
  • the first identification threshold is decreased, and the second identification threshold is obtained, which may include the following steps:
  • the first identification threshold is decreased according to the first proportional coefficient, and the second identification threshold is obtained.
  • the acceleration in the specified time period can be determined by the gyroscope in the lens, and then the acceleration in the specified time period is averaged to obtain the average acceleration.
  • the first proportional coefficient corresponding to the average acceleration may be determined according to the correspondence between the preset acceleration and the proportional coefficient, and further, the first recognition threshold is decreased according to the first proportional coefficient, and the second identification threshold is obtained, wherein the proportional coefficient is obtained. It is 0 to 1. In this way, the recognition threshold can be reduced by the acceleration.
  • the larger the acceleration the smaller the proportional coefficient, for example, the acceleration is 5 m/s, the first proportional coefficient is 0.8, and the acceleration is 8 m/s.
  • the scale factor is 0.6.
  • the first biometric information is image information or feature texture information (information obtained after feature extraction of the image information).
  • acquiring the first biometric information may include the following steps:
  • the moving speed of the electronic device can be detected, and the moving speed can be an average speed, which can be implemented by a step counter sensor.
  • the correspondence between the speed and the anti-shake coefficient can be set in advance, and the anti-shake coefficient corresponding to the motion speed can be determined according to the correspondence relationship, and further, the anti-shake can be determined according to the anti-shake coefficient.
  • the coefficient acquires the first biometric information.
  • the above anti-shake coefficient is an anti-shake coefficient for the camera, so that the camera can acquire the first biometric information more stably, thereby reducing the blur area.
  • step 103 the following steps may be further included:
  • the first biometric information may be an image, for example, an iris image.
  • Image enhancement processing may include, but is not limited to, image denoising (eg, wavelet transform for image denoising), image restoration (eg, Wiener filtering), dark visual enhancement algorithms (eg, histogram equalization, grayscale stretching, etc.) Wait).
  • image denoising eg, wavelet transform for image denoising
  • image restoration eg, Wiener filtering
  • dark visual enhancement algorithms eg, histogram equalization, grayscale stretching, etc.
  • the first biometric information after the image enhancement processing may be matched with the first preset biometric template.
  • step 103 the following steps may be further included:
  • A31 performing image quality evaluation on the first biometric identification information, and obtaining an image quality evaluation value
  • A32 Perform image enhancement processing on the first biometric information when the image quality evaluation value is lower than a preset quality threshold.
  • the preset quality threshold may be set by the user or the system defaults, and the image quality evaluation may be performed on the first biometric information to obtain an image quality evaluation value, and whether the quality of the iris image is good or not is determined by the image quality evaluation value.
  • Bad taking the iris image as an example, when the image quality evaluation value is greater than or equal to the preset quality threshold, the iris image quality is considered to be good, and when the image quality evaluation value is less than the preset quality threshold, the iris image quality may be considered to be poor.
  • the first biometric information may be subjected to image enhancement processing.
  • At least one image quality evaluation index may be used to perform image quality evaluation on the first biometric information, thereby obtaining an image quality evaluation value.
  • Image quality evaluation indicators may be included, and each image quality evaluation index also corresponds to a weight. Thus, each image quality evaluation index can obtain an evaluation result when performing image quality evaluation on the image, and finally, weighting operation is performed. The final image quality evaluation value is obtained.
  • Image quality evaluation indicators may include, but are not limited to, mean, standard deviation, entropy, sharpness, signal to noise ratio, and the like.
  • Image quality can be evaluated by using 2 to 10 image quality evaluation indicators. Specifically, the number of image quality evaluation indicators and which indicator are selected are determined according to specific implementation conditions. Of course, it is also necessary to select image quality evaluation indicators in combination with specific scenes, and the image quality indicators in the dark environment and the image quality evaluation in the bright environment may be different.
  • an image quality evaluation index may be used for evaluation.
  • the image quality evaluation value is processed by entropy processing, and the entropy is larger, indicating that the image quality is higher.
  • the smaller the entropy the worse the image quality.
  • the image may be evaluated by using multiple image quality evaluation indicators, and the plurality of image quality evaluation indicators may be set when the image quality is evaluated.
  • the weight of each image quality evaluation index in the image quality evaluation index may obtain a plurality of image quality evaluation values, and the final image quality evaluation value may be obtained according to the plurality of image quality evaluation values and corresponding weights, for example, three images
  • the quality evaluation indicators are: A index, B index and C index.
  • the weight of A is a1
  • the weight of B is a2
  • the weight of C is a3.
  • 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
  • the image quality evaluation value corresponding to C is b3
  • the final image quality evaluation value a1b1+a2b2+a3b3.
  • the larger the image quality evaluation value the better the image quality.
  • the first preset biometric template information may be pre-stored, and is implemented by a user registration before the step 101 is performed.
  • the first preset biometric template information is collected by the first biometric identification device. Matching the first biometric information with the first preset biometric template information, and obtaining a matching value between the first biometric identification information and the first preset biometric template information, where the second biometric template information is greater than the second identification threshold.
  • the second biometric identification information and the identification operation of the second biometric identification information may be pre-stored, and is implemented by a user registration before the step 101 is performed.
  • the first preset biometric template information is collected by the first biometric identification device. Matching the first biometric information with the first preset biometric template information, and obtaining a matching value between the first biometric identification information and the first preset biometric template information, where the second biometric template information is greater than the second identification threshold.
  • the matching value between the first biometric information and the first preset biometric template information is less than or equal to the second identification threshold, prompting the user to re-enter the first biometric information.
  • the user is prompted to re-enter the first biometric information.
  • detecting whether the electronic device is in a motion state when the electronic device is in a motion state, lowering the first recognition threshold, obtaining a second identification threshold, and acquiring the first biometric information, in the first biometric identification
  • the matching value between the information and the first preset biometric template information is greater than the second identification threshold
  • acquiring the second biometric identification information and performing the identification operation on the second threshold biometric identification information so that the electronic device is in the motion state
  • the recognition threshold is lowered, thereby increasing the efficiency of biometric recognition.
  • FIG. 2 is a schematic flowchart of an embodiment of an unlocking control method according to an embodiment of the present application, which is applied to an electronic device.
  • the physical map or structure diagram of the electronic device may refer to FIG. 1A or FIG. 1B.
  • the described unlock control method includes the following steps:
  • the user is prompted to re-enter the first biometric information.
  • the third identification threshold is decreased to obtain a fourth identification threshold, which may include the following steps:
  • the instantaneous acceleration can be determined by the gyroscope in the lens, and the instantaneous acceleration can be understood as the acceleration acquired at the latest time.
  • the second proportional coefficient corresponding to the average acceleration may be determined, and further, the third recognition threshold is decreased according to the second proportional coefficient, and the fourth identification threshold is obtained, wherein the proportional coefficient is obtained. It is 0 to 1. In this way, the recognition threshold can be reduced by the acceleration.
  • the larger the acceleration the smaller the proportional coefficient, for example, the acceleration is 5 m/s
  • the second proportional coefficient is 0.8
  • the acceleration is 8 m/s.
  • the scale factor is 0.6.
  • the second preset biometric template information may be pre-stored, and is implemented by a user registration before the step 201 is performed, and the second preset biometric template information is collected by the second biometric identification device.
  • the second biometric information can be matched with the second preset biometric template information.
  • acquiring the first biometric information may include the following steps:
  • the moving speed of the electronic device can be detected, and the moving speed can be an average speed, which can be implemented by a step counter sensor.
  • the correspondence between the speed and the anti-shake coefficient can be set in advance, and the anti-shake coefficient corresponding to the motion speed can be determined according to the correspondence relationship, and further, the anti-shake can be determined according to the anti-shake coefficient.
  • the coefficient acquires the second biometric information.
  • the above-mentioned anti-shake coefficient is an anti-shake coefficient for the camera, so that the camera can acquire the second biometric information more stably, thereby reducing the blur area.
  • the unlocking operation may be performed when the matching value between the second biometric identification information and the second preset biometric template information is greater than the fourth identification threshold, and the unlocking operation may be understood as: lighting the screen of the electronic device and entering The main page, or, when the electronic device is in a bright state, enters the main page of the electronic device, or, for an unlock operation of an application, enters a specified page of the application after being unlocked, and the specified page can be set by the user or the system defaults.
  • detecting whether the electronic device is in a motion state when the electronic device is in a motion state, lowering the first recognition threshold, obtaining a second identification threshold, and acquiring the first biometric information, in the first biometric identification
  • the matching value between the information and the first preset biometric template information is greater than the second identification threshold
  • acquiring the second biometric identification information and performing the identification operation on the second threshold biometric identification information so that the electronic device is in the motion state
  • the recognition threshold is lowered, thereby improving the efficiency of multi-biometric recognition.
  • FIG. 3 is an electronic device according to an embodiment of the present application, including: an application processor AP and a memory; and one or more programs, where the one or more programs are stored in the memory, And configured to be executed by the AP, the program comprising instructions for performing the following steps:
  • the program includes instructions for performing the following steps in terms of whether the electronic device is in motion:
  • the program includes instructions for performing the following steps:
  • the program includes instructions for performing the following steps:
  • the program further includes instructions for performing the following steps:
  • the program includes instructions for performing the following steps in the identifying operation of the second biometric information:
  • the program further includes instructions for performing the following steps:
  • the matching value between the first biometric information and the first preset biometric template information is less than or equal to the second identification threshold, prompting the user to re-enter the first biometric information.
  • FIG. 4A is a schematic structural diagram of an unlocking control apparatus according to this embodiment.
  • the unlocking control device is applied to an electronic device, and the unlocking control device includes a detecting unit 401, a reducing unit 402, an obtaining unit 403, and a processing unit 404, where
  • the detecting unit 401 is configured to detect whether the electronic device is in a motion state
  • the lowering unit 402 is configured to lower the first identification threshold when the electronic device is in a motion state, to obtain a second identification threshold;
  • the processing unit 404 is configured to acquire, when the matching value between the first biometric information and the first preset biometric template information is greater than the second identification threshold, the second biometric information, and the second biometric Identify the information for identification.
  • FIG. 4B is a specific refinement structure of the detecting unit 401 of the unlocking control device described in FIG. 4A, and the detecting unit 401 may include: a first obtaining module 4011 and a first determining module 4012, specifically as follows:
  • the first obtaining module 4011 is configured to detect a motion curve by using a gyroscope in the lens
  • a first determining module 4012 configured to determine a characteristic parameter of the motion curve
  • the first determining module 4012 is further configured to:
  • FIG. 4C is a specific refinement structure of the lowering unit 402 of the unlocking control device described in FIG. 4A, and the reducing unit 402 may include: a second obtaining module 4021, a second determining module 4022, and a lowering Module 4023 is as follows:
  • the second obtaining module 4021 is configured to acquire an average acceleration of the electronic device.
  • the second determining module 4022 is configured to determine, according to a correspondence between the preset acceleration and the proportional coefficient, a first proportional coefficient corresponding to the average acceleration;
  • the lowering module 4023 is configured to reduce the first identification threshold according to the first proportional coefficient to obtain the second identification threshold.
  • FIG. 4D is a specific refinement structure of the acquiring unit 403 of the unlocking control device described in FIG. 4A, where the obtaining unit 403 may include: a third obtaining module 4031 and a third determining module 4032, specifically as follows:
  • a third obtaining module 4031 configured to acquire a motion speed of the electronic device
  • a third determining module 4032 configured to determine an anti-shake coefficient corresponding to the motion speed
  • the third obtaining module 4031 is further configured to acquire the first biometric information according to the anti-shake coefficient.
  • the reducing unit 402 is further configured to: reduce the third identification threshold to obtain a fourth identification threshold; and the specific implementation manner of the processing unit 404 performing the identifying operation on the second biometric information is:
  • FIG. 4E is another modified structure of the unlocking control device described in FIG. 4A.
  • the present invention may further include: a prompting unit 405, as follows:
  • the prompting unit is configured to prompt the user to re-enter the first biometric information if the matching value between the first biometric identification information and the first preset biometric template information is less than or equal to the second identification threshold.
  • the unlocking control device described in the embodiment of the present application detects whether the electronic device is in a motion state, and when the electronic device is in a motion state, lowers the first recognition threshold, obtains a second identification threshold, and acquires the first biometric information. And acquiring, when the matching value between the first biometric information and the first preset biometric template information is greater than the second identification threshold, acquiring the second biometric identification information, and performing the identification operation on the second threshold biometric identification information, thereby When the electronic device is in motion, the recognition threshold is lowered, thereby improving the efficiency of multi-biometric recognition.
  • the embodiment of the present application further provides another electronic device. As shown in FIG. 5, for the convenience of description, only the parts related to the embodiment of the present application are shown. If the specific technical details are not disclosed, refer to the method of the embodiment of the present application. section.
  • the electronic device may be any terminal device including a mobile phone, a tablet computer, a PDA (Personal Digital Assistant), a POS (Point of Sales), an in-vehicle computer, and the like, and the electronic device is used as a mobile phone as an example:
  • FIG. 5 is a block diagram showing a partial structure of a mobile phone related to an electronic device provided by an embodiment of the present application.
  • the mobile phone includes: a radio frequency (RF) circuit 910, a memory 920, an input unit 930, a sensor 950, an audio circuit 960, a Wireless Fidelity (WiFi) module 970, an application processor AP980, and a power supply. 990 and other components.
  • RF radio frequency
  • the input unit 930 can be configured to receive input numeric or character information and to generate key signal inputs related to user settings and function controls of the handset.
  • the input unit 930 may include a touch display screen 933, a multi-biometric device 931, and other input devices 932.
  • the multi-biometric device 931 includes at least two biometric devices (for example, a face recognition device + an iris recognition device).
  • the input unit 930 can also include other input devices 932.
  • other input devices 932 may include, but are not limited to, one or more of physical buttons, function keys (such as volume control buttons, switch buttons, etc.), trackballs, mice, joysticks, and the like.
  • the AP 980 is configured to perform the following steps:
  • the AP 980 is the control center of the handset, which utilizes various interfaces and lines to connect various portions of the entire handset, and executes the handset by running or executing software programs and/or modules stored in the memory 920, as well as invoking data stored in the memory 920. A variety of functions and processing data to monitor the phone as a whole.
  • the AP 980 may include one or more processing units; optionally, the AP 980 may integrate an application processor and a modem processor, where the application processor mainly processes an operating system, a user interface, an application, and the like, and the modulation solution The processor mainly handles wireless communication. It can be understood that the above modem processor may not be integrated into the AP 980.
  • memory 920 can include high speed random access memory, and can also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.
  • the RF circuit 910 can be used for receiving and transmitting information.
  • 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.
  • LNA low noise amplifier
  • RF circuitry 910 can also communicate with the network and other devices via wireless communication.
  • the above wireless communication may use any communication standard or protocol, including but not limited to global system of mobile communication (GSM), general packet radio service (GPRS), code division multiple access (code division) Multiple access (CDMA), wideband code division multiple access (WCDMA), long term evolution (LTE), e-mail, short messaging service (SMS), and the like.
  • GSM global system of mobile communication
  • GPRS general packet radio service
  • CDMA code division multiple access
  • WCDMA wideband code division multiple access
  • LTE long term evolution
  • SMS short messaging service
  • the handset may also include at least one type of sensor 950, such as a light sensor, motion sensor, and other sensors.
  • the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor can adjust the brightness of the touch display screen according to the brightness of the ambient light, and the proximity sensor can turn off the touch display when the mobile phone moves to the ear. And / or backlight.
  • the accelerometer sensor can detect the magnitude of acceleration in all directions (usually three axes). When it is stationary, it can detect the magnitude and direction of gravity.
  • the mobile phone can be used to identify the gesture of the mobile phone (such as horizontal and vertical screen switching, related Game, magnetometer attitude calibration), vibration recognition related functions (such as pedometer, tapping), etc.; as for the mobile phone can also be configured with gyroscopes, barometers, hygrometers, thermometers, infrared sensors and other sensors, no longer Narration.
  • the gesture of the mobile phone such as horizontal and vertical screen switching, related Game, magnetometer attitude calibration
  • vibration recognition related functions such as pedometer, tapping
  • the mobile phone can also be configured with gyroscopes, barometers, hygrometers, thermometers, infrared sensors and other sensors, no longer Narration.
  • An audio circuit 960, a speaker 961, and a microphone 962 can provide an audio interface between the user and the handset.
  • the audio circuit 960 can transmit the converted electrical data of the received audio data to the speaker 961 for conversion to the sound signal by the speaker 961; on the other hand, the microphone 962 converts the collected sound signal into an electrical signal by the audio circuit 960. After receiving, it is converted into audio data, and then the audio data is played by the AP 980, sent to the other mobile phone via the RF circuit 910, or the audio data is played to the memory 920 for further processing.
  • WiFi is a short-range wireless transmission technology
  • the mobile phone can help users to send and receive emails, browse web pages, and access streaming media through the WiFi module 970, which provides users with wireless broadband Internet access.
  • FIG. 5 shows the WiFi module 970, it can be understood that it does not belong to the essential configuration of the mobile phone, and may be omitted as needed within the scope of not changing the essence of the invention.
  • the mobile phone also includes a power supply 990 (such as a battery) that supplies power to various components.
  • a power supply 990 (such as a battery) that supplies power to various components.
  • the power supply can be logically connected to the AP980 through a power management system to manage functions such as charging, discharging, and power management through the power management system.
  • the mobile phone may further include a camera, a Bluetooth module, and the like, and details are not described herein again.
  • each step method flow can be implemented based on the structure of the mobile phone.
  • each unit function can be implemented based on the structure of the mobile phone.
  • the embodiment of the present application further provides a computer storage medium, wherein the computer storage medium is used for storing a computer program, and the computer program causes the computer to perform some or all of the steps of any one of the unlocking control methods described in the foregoing method embodiments. .
  • the embodiment of the present application further provides a computer program product, comprising: a non-transitory computer readable storage medium storing a computer program, the computer program being operative to cause a computer to perform the operations as recited in the foregoing method embodiments Any or all of the steps to unlock the control method.
  • the disclosed apparatus may be implemented in other ways.
  • the device embodiments described above are merely illustrative.
  • the division of the unit is only a logical function division.
  • there may be another division manner for example, multiple units or components may be combined or may be Integrate into another system, or some features can be ignored or not executed.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be electrical or otherwise.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
  • the above integrated unit can be implemented in the form of hardware or in the form of a software program module.
  • the integrated unit if implemented in the form of a software program module and sold or used as a standalone product, may be stored in a computer readable memory.
  • a computer device which may be a personal computer, server or network device, etc.
  • the foregoing memory includes: a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk, or an optical disk, and the like, which can store program codes.

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Abstract

本申请实施例公开了一种解锁控制方法及相关产品,方法包括:在待解锁状态下,检测当前电量是否低于第一预设阈值;在所述当前电量低于所述第一预设阈值时,获取当前多生物识别模式,所述当前多生物识别模式包含至少两个识别步骤;减少所述当前多生物识别模式的识别步骤。本申请实施例在电量低于第一预设阈值时,可减少多生物识别模式的至少一个识别步骤,在进行多生物识别模式时,采用减少识别步骤后的多生物识别模式即可,可降低电子设备的功耗。

Description

解锁控制方法及相关产品
本申请要求2017年7月18日递交的发明名称为“解锁控制方法及相关产品”的申请号201710585207.3的在先申请优先权,上述在先申请的内容以引入的方式并入本文本中。
技术领域
本申请涉及电子设备技术领域,具体涉及一种解锁控制方法及相关产品。
背景技术
随着电子设备(手机、平板电脑等)的大量普及应用,电子设备能够支持的应用越来越多,功能越来越强大,电子设备向着多样化、个性化的方向发展,成为用户生活中不可缺少的电子用品。
目前来看,多生物识别越来越受到电子设备生产厂商的青睐,但是在运动状态下,由于电子设备也处于运动状态,因而,会导致采集的生物信息(例如,指纹图像)模糊,从而,降低了多生物识别的效率。
发明内容
本申请实施例提供了一种解锁控制方法及相关产品,以期提升多生物识别的效率。
第一方面,本申请实施例提供一种电子设备,包括:运动传感器、应用处理器AP、存储器、第一生物识别装置和第二生物识别装置,所述运动传感器、所述存储器、所述第一生物识别装置和所述第二生物识别装置均连接于所述AP,其中,
所述运动传感器,用于检测所述电子设备是否处于运动状态;
所述第一生物识别装置,用于获取第一生物识别信息;
所述存储器,用于存储第一预设生物模板信息;
所述AP,用于在所述电子设备处于运动状态时,降低第一识别阈值,得到第二识别阈值;
所述第二生物识别装置,用于在所述第一生物识别信息与第一预设生物模板信息之间的匹配值大于所述第二识别阈值时,获取第二生物识别信息;以及所述AP对所述第二生物识别信息进行识别操作。
第二方面,本申请实施例提供一种解锁控制方法,包括:
检测电子设备是否处于运动状态;
在所述电子设备处于运动状态时,降低第一识别阈值,得到第二识别阈值;
获取第一生物识别信息;
在所述第一生物识别信息与第一预设生物模板信息之间的匹配值大于所述第二识别阈值时,获取第二生物识别信息,并对所述第二生物识别信息进行识别操作。
第三方面,本申请实施例提供了一种解锁控制装置,包括:
检测单元,用于检测电子设备是否处于运动状态;
降低单元,用于在所述电子设备处于运动状态时,降低第一识别阈值,得到第二识别阈值;
获取单元,用于获取第一生物识别信息;
处理单元,用于在所述第一生物识别信息与第一预设生物模板信息之间的匹配值大于所述第二识别阈值时,获取第二生物识别信息,并对所述第二生物识别信息进行识别操作。
第四方面,本申请实施例提供了一种电子设备,应用处理器AP和存储器;以及一个或多个程序,所述一个或多个程序被存储在所述存储器中,并且被配置成由所述AP执行,所述程序包括用于执行第二方面中所描述的部分或全部步骤的指令。
第五方面,本申请实施例提供了一种计算机可读存储介质,其中,所述计算机可读存储介质用于存储的计算机程序,其中,所述计算机程序使得计算机执行如本申请实施例第二方面中所描述的部分或全部步骤。
第六方面,本申请实施例提供了一种计算机程序产品,其中,所述计算机程序产品包括存储了计算机程序的非瞬时性计算机可读存储介质,所述计算机程序可操作来使计算机执行如本申请实施例第二方面中所描述的部分或全部步骤。该计算机程序产品可以为一个软件安装包。
实施本申请实施例,具有如下有益效果:
可以看出,本申请实施例中,检测电子设备是否处于运动状态,在电子设备处于运动状态时,降低第一识别阈值,得到第二识别阈值,获取第一生物识别信息,在第一生物识别信息与第一预设生物模板信息之间的匹配值大于第二识别阈值时,获取第二生物识别信息,并对识别阈值第二生物识别信息进行识别操作,从而,可在电子设备处于运动状态下的时候,降低识别阈值,从而,可提升多生物识别的效率。
附图说明
为了更清楚地说明本申请实施例或现有技术中的技术方案,下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍,显而易见地,下面描述中的附图仅仅是本申请的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动的前提下,还可以根据这些附图获得其他的附图。
图1A是本申请实施例公开的一种智能手机的结构示意图;
图1B是本申请实施例公开的一种电子设备的结构示意图;
图1C是本申请实施例公开的一种解锁控制方法的流程示意图;
图2是本申请实施例公开的另一种解锁控制方法的流程示意图;
图3是本申请实施例提供的一种电子设备的结构示意图;
图4A是本申请实施例提供的一种解锁控制装置的结构示意图;
图4B是本申请实施例提供的图4A所描述的解锁控制装置的检测单元的结构示意图;
图4C是本申请实施例提供的图4A所描述的解锁控制装置的降低单元的结构示意图;
图4D是本申请实施例提供的图4A所描述的解锁控制装置的获取单元的结构示意图;
图4E是本申请实施例提供的图4A所描述的解锁控制装置的又一结构示意图;
图5是本申请实施例公开的另一种电子设备的结构示意图。
具体实施方式
为了使本技术领域的人员更好地理解本申请方案,下面将结合本申请实施例中的附图,对本申请实施例中的技术方案进行清楚、完整地描述,显然,所描述的实施例仅仅是本申请一部分实施例,而不是全部的实施例。基于本申请中的实施例,本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例,都属于本申请保护的范围。
本申请的说明书和权利要求书及上述附图中的术语“第一”、“第二”等是用于区别不同对象,而不是用于描述特定顺序。此外,术语“包括”和“具有”以及它们任何变形,意图在于覆盖不排他的包含。例如包含了一系列步骤或单元的过程、方法、***、产品或设备没有限定于已列出的步骤或单元,而是可选地还包括没有列出的步骤或单元,或可选地还包括对于这些过程、方法、产品或设备固有的其他步骤或单元。
在本文中提及“实施例”意味着,结合实施例描述的特定特征、结构或特性可以包含在本申请的至少一个实施例中。在说明书中的各个位置出现该短语并不一定均是指相同的实施例,也不是与其它实施例互斥的独立的或备选的实施例。本领域技术人员显式地和隐式地理解的是,本文所描述的实施例可以与其它实施例相结合。
本申请实施例所涉及到的电子设备可以包括各种具有无线通信功能的手持设备、车载设备、可穿戴设备、计算设备或连接到无线调制解调器的其他处理设备,以及各种形式的用户设备(user equipment,UE),移动台(mobile station,MS),终端设备(terminal device)等等。为方便描述,上面提到的设备统称为电子设备。下面对本申请实施例进行详细介绍。
需要说明的是,本申请实施例中的电子设备可安装多生物识别装置,该多生物识别装置包含有多个生物识别装置,该多个生物识别装置可包括以下至少两种生物识别装置:指纹识别装置、虹膜识别装置、人脸识别装置、静脉识别装置、脑电波识别装置、心电图识别装置等等,每一生物识别装置均有对应的识别算法以及识别阈值,另外,每一生物识别装置均有与之对应的并由用户预先录入的模板,例如,指纹识别装置有与之对应的预设指纹模板,进一步地,指纹识别装置可采集指纹图像,在指纹图像与预设指纹模板之间的匹配值大于其对应的识别阈值时,则识别通过。
进一步地,本申请实施例中的多生物识别模式可包含两种或者两种以上的识别步骤,例如,先指纹识别,在指纹识别通过后再人脸识别,又或者,指纹识别和人脸识别同步进行。多生物识别模式与单生物识别模式(例如,仅进行指纹识别则可实现解锁)相比较,其安全性更高,因而,多生物识别模式越来越受欢迎。
进一步地,本申请实施例中,第一生物识别信息可包括但不仅限于:指纹信息、虹膜信息、人脸信息、静脉信息、脑电波信息、心电图信息等等。第二生物识别信息可包括但不仅限于:指纹信息、虹膜信息、人脸信息、静脉信息、脑电波信息、心电图信息等等。
可选地,第一生物识别装置用于采集第一生物识别信息,第一生物识别装置可为以下一种:指纹识别装置、虹膜识别装置、人脸识别装置、静脉识别装置、脑电波识别装置、心电图识别装置等等。
可选地,第二生物识别装置用于采集第二生物识别信息,第二生物识别装置可为以下一种:指纹识别装置、虹膜识别装置、人脸识别装置、静脉识别装置、脑电波识别装置、心电图识别装置等等。
可选地,第一生物识别信息可与第二生物识别信息类别不同,例如,第一生物识别信息为指纹信息,第二生物识别信息为虹膜信息,又例如,第一生物识别信息为虹膜信息,第二生物识别信息为人脸信息,又例如,第一生物识别信息为人脸信息,第二生物识别信息为虹膜信息。
下面对本申请实施例进行详细介绍。如图1A所示的一种示例智能手机1000,该智能手机1000的虹膜识别装置可以包括红外补光灯21和红外摄像头22,在虹膜识别装置工作过程中,红外补光灯21的光线打到虹膜上之后,经过虹膜反射回红外摄像头22,虹膜识别装置采集虹膜图像,前置摄像头23可作为人脸识别装置。
请参阅图1B,图1B是所示的一种电子设备100的结构示意图,所述电子设备100包括:应用处理器AP110、第一生物识别装置120、第二生物识别装置130,所述AP110通过总线150连接第一生物识别装置120、第二生物识别装置130、运动传感器160和存储器140。
在一个可能的示例中,所述运动传感器160,用于检测所述电子设备是否处于运动状态;
所述第一生物识别装置120,用于获取第一生物识别信息;
所述存储器140,用于存储第一预设生物模板信息;
所述AP110,用于在所述电子设备处于运动状态时,降低第一识别阈值,得到第二识别阈值;
所述第二生物识别装置130,用于在所述第一生物识别信息与第一预设生物模板信息之间的匹配值大于所述第二识别阈值时,获取第二生物识别信息;以及所述AP110对所述第二生物识别信息进行识别操作。
在一个可能的示例中,在所述检测所述电子设备是否处于运动状态方面,所述运动传感器160具体用于:
利用镜头内的陀螺仪检测获取运动曲线;
确定所述运动曲线的特征参数;
根据所述特征参数检测所述电子设备是否处于运动状态。
在一个可能的示例中,在所述降低第一识别阈值,得到第二识别阈值方面,所述AP110具体用于:
获取所述电子设备的平均加速度;
按照预设的加速度与比例系数之间的对应关系,确定所述平均加速度对应的第一比例系数;
根据所述第一比例系数降低所述第一识别阈值,得到所述第二识别阈值。
在一个可能的示例中,在所述获取第一生物识别信息方面,所述第一生物识别装置120具体用于:
获取所述电子设备的运动速度;
确定与所述运动速度对应的防抖系数;
根据所述防抖系数获取所述第一生物识别信息。
在一个可能的示例中,所述AP110还具体用于:
降低第三识别阈值,得到第四识别阈值;
在所述对所述第二生物识别信息进行识别操作方面,所述AP110具体用于:
将所述第二生物识别信息与第二预设生物模板信息进行匹配;
在所述第二生物识别信息与第二预设生物模板信息之间的匹配值大于所述第四识别阈值时,进行解锁操作。
在一个可能的示例中,所述AP110还具体用于:
若所述第一生物识别信息与所述第一预设生物模板信息之间的匹配值小于或等于所述第二识别阈值时,则提示用户重新输入第一生物识别信息。
请参阅图1C,为本申请实施例提供的一种解锁控制方法的实施例流程示意图,应用于电子设备,该电子设备的实物图或者结构图可参考图1A或者图1B,本实施例中所描述的解锁控制方法,包括以下步骤:
101、检测电子设备是否处于运动状态。
其中,若电子设备处于运动状态,则其采集到的图像会出现模糊状态,因而,会影响生物识别效率。电子设备可通过以下传感器检测其是否处于运动状态,例如:加速度传感器、位移传感器、振动传感器、计步传感器、陀螺仪等等。若电子设备处于运动状态可执行下述步骤102。
可选地,上述步骤101中,检测电子设备是否处于运动状态,可包括如下步骤:
A1、利用镜头内的陀螺仪检测获取运动曲线;
A2、确定所述运动曲线的特征参数;
A3、根据所述特征参数检测所述电子设备是否处于运动状态。
其中,电子设备在运动的过程中,其镜头内的陀螺仪也会随着运动,因而,其可以记录一段时间内的运动状态,该运动状态即是运动曲线,其横轴为时间轴,纵轴为偏离平衡位置的位移。因而,可通过该运动曲线得到特征参数,该特征参数可包括但不仅限于:速度、加速度、振幅等等。可通过这些特征参数检测电子设备是否处于运动状态。
例如,上述步骤A3,根据所述特征参数检测所述电子设备是否处于运动状态,可按照如下方式实施:
在加速度大于第一阈值,且振幅大于第二阈值时,确认所述电子设备处于运动状态。
其中,上述第一阈值、第二阈值均可由用户自行设置或者***默认。
可选地,上述步骤101中,检测电子设备是否处于运动状态,可包括如下步骤:
B1、利用所述电子设备的摄像头拍摄多张图像;
B2、通过所述多张图像判断所述电子设备是否处于运动状态。
其中,电子设备处于运动状态的话,其得到的图像很可能会是模糊的,因而,拍摄多张图像的话,可以判断每一张图像是否都是模糊,若是,则电子设备处于运动状态。例如,拍摄3张图像,3张图像均模糊,则电子设备处于运动状态。在判断每一张图像是否模糊的时候,可采用下述方法:确定任一图像的模糊区域,若该模糊区域的面积大于预设模糊面积,则确认该图像是模糊。
102、在所述电子设备处于运动状态时,降低第一识别阈值,得到第二识别阈值。
其中,若电子设备处于运动状态,则说明图像可能会出现模糊,因而,可适当降低第一识别阈值,得到第二识别阈值,可提高识别效率。
可选地,上述步骤102中,降低第一识别阈值,得到第二识别阈值,可包括如下步骤:
21、获取所述电子设备的平均加速度;
22、按照预设的加速度与比例系数之间的对应关系,确定所述平均加速度对应的第一比例系数;
23、根据所述第一比例系数降低所述第一识别阈值,得到所述第二识别阈值。
其中,可通过镜头内的陀螺仪确定指定时间段内的加速度,进而,对该指定时间段内的加速度取均值运算,得到平均加速度。按照预设的加速度与比例系数之间的对应关系,可确定平均加速度对应的第一比例系数,进而,根据该第一比例系数降低第一识别阈值,得到第二识别阈值,其中,上述比例系数为0~1。如此,可通过加速度实现降低识别阈值,具体实现中,可以设置为加速度越大,则比例系数越小,例如,加速度为5m/s,第一比例系数为0.8,加速度为8m/s,第一比例系数为0.6。
103、获取第一生物识别信息。
其中,第一生物识别信息为可图像信息或者特征纹路信息(对图像信息进行特征提取之后得到的信息)。
可选地,上述步骤103中,获取第一生物识别信息,可包括如下步骤:
31、获取所述电子设备的运动速度;
32、确定与所述运动速度对应的防抖系数;
33、根据所述防抖系数获取所述第一生物识别信息。
其中,可检测电子设备的运动速度,该运动速度可为平均速度,可由计步传感器实现。通常情况下,运动越剧烈,则抖动越大,因而,可预先设置速度与防抖系数之间的对应关系,根据该对应关系可确定运动速度对应的防抖系数,进而,可根据该防抖系数获取第一生物识别信息。其中,上述防抖系数为针对摄像头的防抖系数,如此,可使得摄像头更稳定地获取第一生物识别信息,从而,减少模糊面积。
可选的,在上述步骤103与步骤104之间,还可以包含如下步骤:
对所述第一生物识别信息进行图像增强处理。
其中,第一生物识别信息可为图像,例如,虹膜图像。图像增强处理可包括但不仅限于:图像去噪(例如,小波变换进行图像去噪)、图像复原(例如,维纳滤波)、暗视觉增强算法(例如,直方图均衡化、灰度拉伸等等)。以虹膜图像为例,在对虹膜图像进行图像增强处理之后,虹膜图像的质量可在一定程度上得到提升。进一步地,在执行步骤104的过程中,可将图像增强处理后的第一生物识别信息与第一预设生物模板进行匹配。
可选地,在上述步骤103与步骤104之间,还可以包含如下步骤:
A31、对所述第一生物识别信息进行图像质量评价,得到图像质量评价值;
A32、在所述图像质量评价值低于预设质量阈值时,对所述第一生物识别信息进行图像增强处理。
其中,上述预设质量阈值可由用户自行设置或者***默认,可先对第一生物识别信息进行图像质量评价,得到一个图像质量评价值,通过该图像质量评价值判断该虹膜图像的质量是好还是坏,以虹膜图像为例,在图像质量评价值大于或等于预设质量阈值时,可认为虹膜图像质量好,在图像质量评价值小于预设质量阈值时,可认为虹膜图像质量差,进而,可对第一生物识别信息进行图像增强处理。
其中,上述步骤A31中,可采用至少一个图像质量评价指标对第一生物识别信息进行图像质量评价,从而,得到图像质量评价值。
可包含多个图像质量评价指标,每一图像质量评价指标也对应一个权重,如此,每一图像质量评价指标对图像进行图像质量评价时,均可得到一个评价结果,最终,进行加权运算,也就得到最终的图像质量评价值。图像质量评价指标可包括但不仅限于:均值、标准差、熵、清晰度、信噪比等等。
需要说明的是,由于采用单一评价指标对图像质量进行评价时,具有一定的局限性,因此,可采用多个图像质量评价指标对图像质量进行评价,当然,对图像质量进行评价时,并非图像质量评价指标越多越好,因为图像质量评价指标越多,图像质量评价过程的计算复杂度越高,也不见得图像质量评价效果越好,因此,在对图像质量评价要求较高的情况下,可采用2~10个图像质量评价指标对图像质量进行评价。具体地,选取图像质量评价指标的个数及哪个指标,依据具体实现情况而定。当然,也得结合具体地场景选取图像质量评价指标,在暗环境下进行图像质量评价和亮环境下进行图像质量评价选取的图像质量指标可不一样。
可选地,在对图像质量评价精度要求不高的情况下,可用一个图像质量评价指标进行评价,例如,以熵对待处理图像进行图像质量评价值,可认为熵越大,则说明图像质量越好,相反地,熵越小,则说明图像质量越差。
可选地,在对图像质量评价精度要求较高的情况下,可以采用多个图像质量评价指标对图像进行评价,在多个图像质量评价指标对图像进行图像质量评价时,可设置该多个图像质量评价指标中每一图像质量评价指标的权重,可得到多个图像质量评价值,根据该多个图像质量评价值及其对应的权重可得到最终的图像质量评价值,例如,三个图像质量评价指标分别为:A指标、B指标和C指标,A的权重为a1,B的权重为a2,C的权重为a3,采用A、B和C对某一图像进行图像质量评价时,A对应的图像质量评价值为b1,B对应的图像质量评价值为b2,C对应的图像质量评价值为b3,那么,最后的图 像质量评价值=a1b1+a2b2+a3b3。通常情况下,图像质量评价值越大,说明图像质量越好。
104、在所述第一生物识别信息与第一预设生物模板信息之间的匹配值大于所述第二识别阈值时,获取第二生物识别信息,并对所述第二生物识别信息进行识别操作。
其中,第一预设生物模板信息可预先存储,在执行上述步骤101之前,由用户注册实现,该第一预设生物模板信息由第一生物识别装置采集。将第一生物识别信息与第一预设生物模板信息进行匹配,可得到第一生物识别信息与第一预设生物模板信息之间的匹配值,在其大于第二识别阈值时,可获取第二生物识别信息,并对该第二生物识别信息进行识别操作。
可选地,上述步骤103之后,还可以包括如下步骤:
若所述第一生物识别信息与所述第一预设生物模板信息之间的匹配值小于或等于所述第二识别阈值时,则提示用户重新输入第一生物识别信息。
其中,若第一生物识别信息与第一预设生物模板信息之间的匹配值小于或等于第二识别阈值时,则提示用户重新输入第一生物识别信息。
可以看出,本申请实施例中,检测电子设备是否处于运动状态,在电子设备处于运动状态时,降低第一识别阈值,得到第二识别阈值,获取第一生物识别信息,在第一生物识别信息与第一预设生物模板信息之间的匹配值大于第二识别阈值时,获取第二生物识别信息,并对识别阈值第二生物识别信息进行识别操作,从而,可在电子设备处于运动状态下的时候,降低识别阈值,从而,可提多生物识别的效率。
请参阅图2,为本申请实施例提供的一种解锁控制方法的实施例流程示意图,应用于电子设备,该电子设备的实物图或者结构图可参考图1A或者图1B,本实施例中所描述的解锁控制方法,包括以下步骤:
201、检测电子设备是否处于运动状态。
202、在所述电子设备处于运动状态时,降低第一识别阈值,得到第二识别阈值。
203、获取第一生物识别信息。
其中,上述步骤201-步骤203的具体描述可参照图1C所描述的解锁控制方法的对应步骤,在此不再赘述。
204、在所述第一生物识别信息与第一预设生物模板信息之间的匹配值大于所述第二识别阈值时,降低第三识别阈值,得到第四识别阈值。
其中,若第一生物识别信息与第一预设生物模板信息之间的匹配值小于或等于第二识别阈值时,则提示用户重新输入第一生物识别信息。
可选地,上述步骤204中,降低第三识别阈值,得到第四识别阈值,可包括如下步骤:
21、获取所述电子设备的瞬间加速度;
22、按照预设的加速度与比例系数之间的对应关系,确定所述瞬间加速度对应的第二比例系数;
23、根据所述第二比例系数降低所述第三识别阈值,得到所述第四识别阈值。
其中,可通过镜头内的陀螺仪确定瞬间加速度,该瞬间加速度可理解为最近时刻获取的加速度。按照预设的加速度与比例系数之间的对应关系,可确定平均加速度对应的第二比例系数,进而,根据该第二比例系数降低第三识别阈值,得到第四识别阈值,其中,上述比例系数为0~1。如此,可通过加速度实现降低识别阈值,具体实现中,可以设置为加速度越大,则比例系数越小,例如,加速度为5m/s,第二比例系数为0.8,加速度为8m/s,第二比例系数为0.6。
205、获取第二生物识别信息,将所述第二生物识别信息与第二预设生物模板信息进行匹配。
其中,第二预设生物模板信息可预先存储,在执行上述步骤201之前,由用户注册实现,该第二预设生物模板信息由第二生物识别装置采集。可将第二生物识别信息与第二预设生物模板信息进行匹配。
可选地,上述步骤205中,获取第一生物识别信息,可包括如下步骤:
51、获取所述电子设备的运动速度;
52、确定与所述运动速度对应的防抖系数;
53、根据所述防抖系数获取所述第二生物识别信息。
其中,可检测电子设备的运动速度,该运动速度可为平均速度,可由计步传感器实现。通常情况下,运动越剧烈,则抖动越大,因而,可预先设置速度与防抖系数之间的对应关系,根据该对应关系可确定运动速度对应的防抖系数,进而,可根据该防抖系数获取第二生物识别信息。其中,上述防抖系数为针对摄像头的防抖系数,如此,可使得摄像头更稳定地获取第二生物识别信息,从而,减少模糊面积。
206、在所述第二生物识别信息与第二预设生物模板信息之间的匹配值大于所述第四识别阈值时,进行解锁操作。
其中,在第二生物识别信息与第二预设生物模板信息之间的匹配值大于第四识别阈值时,可进行解锁操作,该解锁操作,可理解为:点亮电子设备的屏幕,并进入主页面,或者,在电子设备处于亮屏状态下,进入电子设备的主页面,或者,针对某个应用的解锁操作,解锁之后进入该应用的指定页面,指定页面可由用户自行设置或者***默认。
可以看出,本申请实施例中,检测电子设备是否处于运动状态,在电子设备处于运动状态时,降低第一识别阈值,得到第二识别阈值,获取第一生物识别信息,在第一生物识别信息与第一预设生物模板信息之间的匹配值大于第二识别阈值时,获取第二生物识别信息,并对识别阈值第二生物识别信息进行识别操作,从而,可在电子设备处于运动状态下的时候,降低识别阈值,从而,可提升多生物识别的效率。
请参阅图3,图3是本申请实施例提供的一种电子设备,包括:应用处理器AP和存储器;以及一个或多个程序,所述一个或多个程序被存储在所述存储器中,并且被配置成由所述AP执行,所述程序包括用于执行以下步骤的指令:
检测电子设备是否处于运动状态;
在所述电子设备处于运动状态时,降低第一识别阈值,得到第二识别阈值;
获取第一生物识别信息;
在所述第一生物识别信息与第一预设生物模板信息之间的匹配值大于所述第二识别阈值时,获取第二生物识别信息,并对所述第二生物识别信息进行识别操作。
在一个可能的示例中,在所述检测电子设备是否处于运动状态方面,所述程序包括用于执行以下步骤的指令:
利用镜头内的陀螺仪检测获取运动曲线;
确定所述运动曲线的特征参数;
根据所述特征参数检测所述电子设备是否处于运动状态。
在一个可能的示例中,在所述降低第一识别阈值,得到第二识别阈值方面,所述程序包括用于执行以下步骤的指令:
获取所述电子设备的平均加速度;
按照预设的加速度与比例系数之间的对应关系,确定所述平均加速度对应的第一比例系数;
根据所述第一比例系数降低所述第一识别阈值,得到所述第二识别阈值。
在一个可能的示例中,在所述获取第一生物识别信息方面,所述程序包括用于执行以下步骤的指令:
获取所述电子设备的运动速度;
确定与所述运动速度对应的防抖系数;
根据所述防抖系数获取所述第一生物识别信息。
在一个可能的示例中,所述程序还包括用于执行以下步骤的指令:
降低第三识别阈值,得到第四识别阈值;在所述对所述第二生物识别信息进行识别操作方面,所述程序包括用于执行以下步骤的指令:
将所述第二生物识别信息与第二预设生物模板信息进行匹配;
在所述第二生物识别信息与第二预设生物模板信息之间的匹配值大于所述第四识别阈值时,进行解锁操作。
在一个可能的示例中,所述程序还包括用于执行以下步骤的指令:
若所述第一生物识别信息与所述第一预设生物模板信息之间的匹配值小于或等于所述第二识别阈值时,则提示用户重新输入第一生物识别信息。
请参阅图4A,图4A是本实施例提供的一种解锁控制装置的结构示意图。该解锁控制装置应用于电子设备,解锁控制装置包括检测单元401、降低单元402、获取单元403和处理单元404,其中,
检测单元401,用于检测电子设备是否处于运动状态;
降低单元402,用于在所述电子设备处于运动状态时,降低第一识别阈值,得到第二识别阈值;
获取单元403,用于获取第一生物识别信息;
处理单元404,用于在所述第一生物识别信息与第一预设生物模板信息之间的匹配值大于所述第二识别阈值时,获取第二生物识别信息,并对所述第二生物识别信息进行识别操作。
可选地,如图4B,图4B为图4A所描述的解锁控制装置的检测单元401的具体细化结构,所述检测单元401可包括:第一获取模块4011和第一确定模块4012,具体如下:
第一获取模块4011,用于利用镜头内的陀螺仪检测获取运动曲线;
第一确定模块4012,用于确定所述运动曲线的特征参数;
所述第一确定模块4012,还用于:
根据所述特征参数检测所述电子设备是否处于运动状态。
可选地,如图4C,图4C为图4A所描述的解锁控制装置的降低单元402的具体细化结构,所述降低单元402可包括:第二获取模块4021、第二确定模块4022和降低模块4023,具体如下:
第二获取模块4021,用于获取所述电子设备的平均加速度;
第二确定模块4022,用于按照预设的加速度与比例系数之间的对应关系,确定所述平均加速度对应的第一比例系数;
降低模块4023,用于根据所述第一比例系数降低所述第一识别阈值,得到所述第二识别阈值。
可选地,如图4D,图4D为图4A所描述的解锁控制装置的获取单元403的具体细化结构,所述获取单元403可包括:第三获取模块4031和第三确定模块4032,具体如下:
第三获取模块4031,用于获取所述电子设备的运动速度;
第三确定模块4032,用于确定与所述运动速度对应的防抖系数;
所述第三获取模块4031,还具体用于根据所述防抖系数获取所述第一生物识别信息。
可选地,所述降低单元402还具体用于:降低第三识别阈值,得到第四识别阈值;所述处理单元404对所述第二生物识别信息进行识别操作的具体实现方式为:
将所述第二生物识别信息与第二预设生物模板信息进行匹配;在所述第二生物识别信息与第二预设生物模板信息之间的匹配值大于所述第四识别阈值时,进行解锁操作。
可选地,如图4E,图4E为图4A所描述的解锁控制装置又一变型结构,其与图4A相比较,还可以包括:提示单元405,具体如下:
提示单元,用于若所述第一生物识别信息与所述第一预设生物模板信息之间的匹配值小于或等于所述第二识别阈值时,则提示用户重新输入第一生物识别信息。
可以看出,本申请实施例中所描述的解锁控制装置,检测电子设备是否处于运动状态,在电子设备处于运动状态时,降低第一识别阈值,得到第二识别阈值,获取第一生物识别信息,在第一生物识别信息与第一预设生物模板信息之间的匹配值大于第二识别阈值时,获取第二生物识别信息,并对识别阈值第二生物识别信息进行识别操作,从而,可在电子设备处于运动状态下的时候,降低识别阈值,从而,可提升多生物识别的效率。
可以理解的是,本实施例的解锁控制装置的各程序模块的功能可根据上述方法实施例中的方法具 体实现,其具体实现过程可以参照上述方法实施例的相关描述,此处不再赘述。
本申请实施例还提供了另一种电子设备,如图5所示,为了便于说明,仅示出了与本申请实施例相关的部分,具体技术细节未揭示的,请参照本申请实施例方法部分。该电子设备可以为包括手机、平板电脑、PDA(Personal Digital Assistant,个人数字助理)、POS(Point of Sales,销售终端)、车载电脑等任意终端设备,以电子设备为手机为例:
图5示出的是与本申请实施例提供的电子设备相关的手机的部分结构的框图。参考图5,手机包括:射频(Radio Frequency,RF)电路910、存储器920、输入单元930、传感器950、音频电路960、无线保真(Wireless Fidelity,WiFi)模块970、应用处理器AP980、以及电源990等部件。本领域技术人员可以理解,图5中示出的手机结构并不构成对手机的限定,可以包括比图示更多或更少的部件,或者组合某些部件,或者不同的部件布置。
下面结合图5对手机的各个构成部件进行具体的介绍:
输入单元930可用于接收输入的数字或字符信息,以及产生与手机的用户设置以及功能控制有关的键信号输入。具体地,输入单元930可包括触控显示屏933、多生物识别装置931以及其他输入设备932。多生物识别装置931至少包括2个生物识别装置(例如,人脸识别装置+虹膜识别装置)。输入单元930还可以包括其他输入设备932。具体地,其他输入设备932可以包括但不限于物理按键、功能键(比如音量控制按键、开关按键等)、轨迹球、鼠标、操作杆等中的一种或多种。
其中,所述AP980,用于执行如下步骤:
检测电子设备是否处于运动状态;
在所述电子设备处于运动状态时,降低第一识别阈值,得到第二识别阈值;
获取第一生物识别信息;
在所述第一生物识别信息与第一预设生物模板信息之间的匹配值大于所述第二识别阈值时,获取第二生物识别信息,并对所述第二生物识别信息进行识别操作。
AP980是手机的控制中心,利用各种接口和线路连接整个手机的各个部分,通过运行或执行存储在存储器920内的软件程序和/或模块,以及调用存储在存储器920内的数据,执行手机的各种功能和处理数据,从而对手机进行整体监控。可选的,AP980可包括一个或多个处理单元;可选的,AP980可集成应用处理器和调制解调处理器,其中,应用处理器主要处理操作***、用户界面和应用程序等,调制解调处理器主要处理无线通信。可以理解的是,上述调制解调处理器也可以不集成到AP980中。
此外,存储器920可以包括高速随机存取存储器,还可以包括非易失性存储器,例如至少一个磁盘存储器件、闪存器件、或其他易失性固态存储器件。
RF电路910可用于信息的接收和发送。通常,RF电路910包括但不限于天线、至少一个放大器、收发信机、耦合器、低噪声放大器(low noise amplifier,LNA)、双工器等。此外,RF电路910还可以通过无线通信与网络和其他设备通信。上述无线通信可以使用任一通信标准或协议,包括但不限于全球 移动通讯***(global system of mobile communication,GSM)、通用分组无线服务(general packet radio service,GPRS)、码分多址(code division multiple access,CDMA)、宽带码分多址(wideband code division multiple access,WCDMA)、长期演进(long term evolution,LTE)、电子邮件、短消息服务(short messaging service,SMS)等。
手机还可包括至少一种传感器950,比如光传感器、运动传感器以及其他传感器。具体地,光传感器可包括环境光传感器及接近传感器,其中,环境光传感器可根据环境光线的明暗来调节触控显示屏的亮度,接近传感器可在手机移动到耳边时,关闭触控显示屏和/或背光。作为运动传感器的一种,加速计传感器可检测各个方向上(一般为三轴)加速度的大小,静止时可检测出重力的大小及方向,可用于识别手机姿态的应用(比如横竖屏切换、相关游戏、磁力计姿态校准)、振动识别相关功能(比如计步器、敲击)等;至于手机还可配置的陀螺仪、气压计、湿度计、温度计、红外线传感器等其他传感器,在此不再赘述。
音频电路960、扬声器961,传声器962可提供用户与手机之间的音频接口。音频电路960可将接收到的音频数据转换后的电信号,传输到扬声器961,由扬声器961转换为声音信号播放;另一方面,传声器962将收集的声音信号转换为电信号,由音频电路960接收后转换为音频数据,再将音频数据播放AP980处理后,经RF电路910以发送给比如另一手机,或者将音频数据播放至存储器920以便进一步处理。
WiFi属于短距离无线传输技术,手机通过WiFi模块970可以帮助用户收发电子邮件、浏览网页和访问流式媒体等,它为用户提供了无线的宽带互联网访问。虽然图5示出了WiFi模块970,但是可以理解的是,其并不属于手机的必须构成,完全可以根据需要在不改变发明的本质的范围内而省略。
手机还包括给各个部件供电的电源990(比如电池),可选的,电源可以通过电源管理***与AP980逻辑相连,从而通过电源管理***实现管理充电、放电、以及功耗管理等功能。
尽管未示出,手机还可以包括摄像头、蓝牙模块等,在此不再赘述。
前述图1C、图2所示的实施例中,各步骤方法流程可以基于该手机的结构实现。
前述图3、图4A~图4E所示的实施例中,各单元功能可以基于该手机的结构实现。
本申请实施例还提供一种计算机存储介质,其中,该计算机存储介质用于存储的计算机程序,该计算机程序使得计算机执行如上述方法实施例中记载的任何一种解锁控制方法的部分或全部步骤。
本申请实施例还提供一种计算机程序产品,所述计算机程序产品包括存储了计算机程序的非瞬时性计算机可读存储介质,所述计算机程序可操作来使计算机执行如上述方法实施例中记载的任何一种解锁控制方法的部分或全部步骤。
需要说明的是,对于前述的各方法实施例,为了简单描述,故将其都表述为一系列的动作组合,但是本领域技术人员应该知悉,本申请并不受所描述的动作顺序的限制,因为依据本申请,某些步骤可以采用其他顺序或者同时进行。其次,本领域技术人员也应该知悉,说明书中所描述的实施例均属于可选实施例,所涉及的动作和模块并不一定是本申请所必须的。
在上述实施例中,对各个实施例的描述都各有侧重,某个实施例中没有详述的部分,可以参见其他实施例的相关描述。
在本申请所提供的几个实施例中,应该理解到,所揭露的装置,可通过其它的方式实现。例如,以上所描述的装置实施例仅仅是示意性的,例如所述单元的划分,仅仅为一种逻辑功能划分,实际实现时可以有另外的划分方式,例如多个单元或组件可以结合或者可以集成到另一个***,或一些特征可以忽略,或不执行。另一点,所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口,装置或单元的间接耦合或通信连接,可以是电性或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的,作为单元显示的部件可以是或者也可以不是物理单元,即可以位于一个地方,或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外,在本申请各个实施例中的各功能单元可以集成在一个处理单元中,也可以是各个单元单独物理存在,也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现,也可以采用软件程序模块的形式实现。
所述集成的单元如果以软件程序模块的形式实现并作为独立的产品销售或使用时,可以存储在一个计算机可读取存储器中。基于这样的理解,本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来,该计算机软件产品存储在一个存储器中,包括若干指令用以使得一台计算机设备(可为个人计算机、服务器或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储器包括:U盘、只读存储器(read-only memory,ROM)、随机存取存储器(random access memory,RAM)、移动硬盘、磁碟或者光盘等各种可以存储程序代码的介质。
本领域普通技术人员可以理解上述实施例的各种方法中的全部或部分步骤是可以通过程序来指令相关的硬件来完成,该程序可以存储于一计算机可读存储器中,存储器可以包括:闪存盘、ROM、RAM、磁盘或光盘等。
以上对本申请实施例进行了详细介绍,本文中应用了具体个例对本申请的原理及实施方式进行了阐述,以上实施例的说明只是用于帮助理解本申请的方法及其核心思想;同时,对于本领域的一般技术人员,依据本申请的思想,在具体实施方式及应用范围上均会有改变之处,综上所述,本说明书内容不应理解为对本申请的限制。

Claims (20)

  1. 一种电子设备,其特征在于,包括:运动传感器、应用处理器AP、存储器、第一生物识别装置和第二生物识别装置,所述运动传感器、所述存储器、所述第一生物识别装置和所述第二生物识别装置均连接于所述AP,其中,
    所述运动传感器,用于检测所述电子设备是否处于运动状态;
    所述第一生物识别装置,用于获取第一生物识别信息;
    所述存储器,用于存储第一预设生物模板信息;
    所述AP,用于在所述电子设备处于运动状态时,降低第一识别阈值,得到第二识别阈值;
    所述第二生物识别装置,用于在所述第一生物识别信息与第一预设生物模板信息之间的匹配值大于所述第二识别阈值时,获取第二生物识别信息;以及所述AP对所述第二生物识别信息进行识别操作。
  2. 根据权利要求1所述的电子设备,其特征在于,在所述检测所述电子设备是否处于运动状态方面,所述运动传感器具体用于:
    利用镜头内的陀螺仪检测获取运动曲线;
    确定所述运动曲线的特征参数;
    根据所述特征参数检测所述电子设备是否处于运动状态。
  3. 根据权利要求1或2所述的电子设备,其特征在于,在所述降低第一识别阈值,得到第二识别阈值方面,所述AP具体用于:
    获取所述电子设备的平均加速度;
    按照预设的加速度与比例系数之间的对应关系,确定所述平均加速度对应的第一比例系数;
    根据所述第一比例系数降低所述第一识别阈值,得到所述第二识别阈值。
  4. 根据权利要求1或2所述的电子设备,其特征在于,在所述获取第一生物识别信息方面,所述第一生物识别装置具体用于:
    获取所述电子设备的运动速度;
    确定与所述运动速度对应的防抖系数;
    根据所述防抖系数获取所述第一生物识别信息。
  5. 根据权利要求1至4任一项所述的电子设备,其特征在于,所述AP还具体用于:
    降低第三识别阈值,得到第四识别阈值;
    在所述对所述第二生物识别信息进行识别操作方面,所述AP具体用于:
    将所述第二生物识别信息与第二预设生物模板信息进行匹配;
    在所述第二生物识别信息与第二预设生物模板信息之间的匹配值大于所述第四识别阈值时,进行解锁操作。
  6. 根据权利要求1至5任一项所述的电子设备,其特征在于,所述AP还具体用于:
    若所述第一生物识别信息与所述第一预设生物模板信息之间的匹配值小于或等于所述第二识别阈值时,则提示用户重新输入第一生物识别信息。
  7. 一种解锁控制方法,其特征在于,包括:
    检测电子设备是否处于运动状态;
    在所述电子设备处于运动状态时,降低第一识别阈值,得到第二识别阈值;
    获取第一生物识别信息;
    在所述第一生物识别信息与第一预设生物模板信息之间的匹配值大于所述第二识别阈值时,获取第二生物识别信息,并对所述第二生物识别信息进行识别操作。
  8. 根据权利要求7所述的方法,其特征在于,所述检测电子设备是否处于运动状态,包括:
    利用镜头内的陀螺仪检测获取运动曲线;
    确定所述运动曲线的特征参数;
    根据所述特征参数检测所述电子设备是否处于运动状态。
  9. 根据权利要求7或8所述的方法,其特征在于,所述降低第一识别阈值,得到第二识别阈值,包括:
    获取所述电子设备的平均加速度;
    按照预设的加速度与比例系数之间的对应关系,确定所述平均加速度对应的第一比例系数;
    根据所述第一比例系数降低所述第一识别阈值,得到所述第二识别阈值。
  10. 根据权利要求7-9任一项所述的方法,其特征在于,所述获取第一生物识别信息,包括:
    获取所述电子设备的运动速度;
    确定与所述运动速度对应的防抖系数;
    根据所述防抖系数获取所述第一生物识别信息。
  11. 根据权利要求7至10任一项所述的方法,其特征在于,所述方法还包括:
    降低第三识别阈值,得到第四识别阈值;
    所述对所述第二生物识别信息进行识别操作,包括:
    将所述第二生物识别信息与第二预设生物模板信息进行匹配;
    在所述第二生物识别信息与第二预设生物模板信息之间的匹配值大于所述第四识别阈值时,进行解锁操作。
  12. 根据权利要求7至11任一项所述的方法,其特征在于,所述方法还包括:
    若所述第一生物识别信息与所述第一预设生物模板信息之间的匹配值小于或等于所述第二识别阈值时,则提示用户重新输入第一生物识别信息。
  13. 一种解锁控制装置,其特征在于,所述解锁控制装置包括:检测单元、降低单元、获取单元和处理单元,其中,
    所述检测单元,用于检测电子设备是否处于运动状态;
    所述降低单元,用于在所述电子设备处于运动状态时,降低第一识别阈值,得到第二识别阈值;
    所述获取单元,用于获取第一生物识别信息;
    所述处理单元,用于在所述第一生物识别信息与第一预设生物模板信息之间的匹配值大于所述第二识别阈值时,获取第二生物识别信息,并对所述第二生物识别信息进行识别操作。
  14. 根据权利要求13所述的装置,其特征在于,所述检测单元包括:
    第一获取模块,用于利用镜头内的陀螺仪检测获取运动曲线;
    第一确定模块,用于确定所述运动曲线的特征参数;以及根据所述特征参数检测所述电子设备是否处于运动状态。
  15. 根据权利要求13或14所述装置,其特征在于,所述降低单元包括:
    第二获取模块,用于获取所述电子设备的平均加速度;
    第二确定模块,用于按照预设的加速度与比例系数之间的对应关系,确定所述平均加速度对应的第一比例系数;
    降低模块,用于根据所述第一比例系数降低所述第一识别阈值,得到所述第二识别阈值。
  16. 根据权利要求13-15任一项所述的装置,其特征在于,所述获取单元包括:
    第三获取模块,用于获取所述电子设备的运动速度;
    第三确定模块,用于确定与所述运动速度对应的防抖系数;
    所述第三获取模块,还用于根据所述防抖系数获取所述第一生物识别信息。
  17. 根据权利要求13至16任一项所述的装置,其特征在于,
    所述降低单元,用于降低第三识别阈值,得到第四识别阈值;
    在所述对所述第二生物识别信息进行识别操作方面,所述处理单元具体用于:
    将所述第二生物识别信息与第二预设生物模板信息进行匹配;
    在所述第二生物识别信息与第二预设生物模板信息之间的匹配值大于所述第四识别阈值时,进行解锁操作。
  18. 一种电子设备,其特征在于,包括:应用处理器AP和存储器;以及一个或多个程序,所述一个或多个程序被存储在所述存储器中,并且被配置成由所述AP执行,所述程序包括用于如权利要求7-12任一项方法的指令。
  19. 一种计算机可读存储介质,其特征在于,其用于存储的计算机程序,其中,所述计算机程序使得计算机执行如权利要求7-12任一项所述的方法
  20. 一种计算机程序产品,其特征在于,所述计算机程序产品包括存储了计算机程序的非瞬时性计算机可读存储介质,所述计算机程序可操作来使计算机执行如权利要求7-12任一项所述的方法。
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Families Citing this family (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107451446B (zh) * 2017-07-18 2020-05-26 Oppo广东移动通信有限公司 解锁控制方法及相关产品
CN108418682A (zh) * 2018-02-11 2018-08-17 广东欧珀移动通信有限公司 密码生成方法及相关产品
CN108519810B (zh) * 2018-03-07 2021-04-09 Oppo广东移动通信有限公司 电子装置、脑电波解锁方法及相关产品
CN110020619A (zh) * 2019-03-28 2019-07-16 维沃移动通信有限公司 一种指纹识别方法及移动终端
CN113312950A (zh) * 2020-09-24 2021-08-27 一令通(上海)科技有限公司 一种基于人脸和虹膜特征的身份认证方法
CN112532885B (zh) * 2020-11-27 2022-05-03 维沃移动通信有限公司 防抖方法、装置及电子设备
CN112802240B (zh) * 2020-12-31 2022-04-15 西南交通大学 一种基于脑电波的保险解锁方法
CN114385012B (zh) * 2022-01-17 2023-06-30 维沃移动通信有限公司 运动的识别方法、装置、电子设备和可读存储介质
CN114626038A (zh) * 2022-01-26 2022-06-14 安徽点亮网络技术有限公司 一种身份验证方法、***及装置
CN114858200B (zh) * 2022-04-19 2023-06-27 合众新能源汽车股份有限公司 车辆传感器检测到的对象的质量评价方法及装置

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160063235A1 (en) * 2014-08-28 2016-03-03 Kevin Alan Tussy Facial Recognition Authentication System Including Path Parameters
CN106407776A (zh) * 2016-08-30 2017-02-15 深圳市金立通信设备有限公司 一种终端控制方法及终端
WO2017040867A1 (en) * 2015-09-01 2017-03-09 Quantum Interface, Llc. Apparatuses, systems and methods for constructing unique identifiers
CN106599651A (zh) * 2016-11-17 2017-04-26 努比亚技术有限公司 一种终端解锁装置和方法
CN107451446A (zh) * 2017-07-18 2017-12-08 广东欧珀移动通信有限公司 解锁控制方法及相关产品

Family Cites Families (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6947609B2 (en) * 2002-03-04 2005-09-20 Xerox Corporation System with motion triggered processing
JP5230501B2 (ja) * 2009-03-26 2013-07-10 富士フイルム株式会社 認証装置及び認証方法
CN201638241U (zh) * 2010-02-11 2010-11-17 苏州市职业大学 一种指纹识别装置
US9372979B2 (en) * 2011-01-07 2016-06-21 Geoff Klein Methods, devices, and systems for unobtrusive mobile device user recognition
US8441548B1 (en) 2012-06-15 2013-05-14 Google Inc. Facial image quality assessment
WO2014200485A1 (en) 2013-06-13 2014-12-18 Intel Corporation Techniques for user authentication on a computing device via pattern recognition
CN103618832B (zh) * 2013-11-29 2016-06-22 广东欧珀移动通信有限公司 一种用于移动终端的信息提示方法及终端
CN110489952A (zh) 2014-09-30 2019-11-22 华为技术有限公司 身份认证的方法、装置及用户设备
CN106156688A (zh) * 2015-03-10 2016-11-23 上海骏聿数码科技有限公司 一种动态人脸识别方法及***
CN106250751B (zh) 2016-07-18 2019-09-17 青岛海信移动通信技术股份有限公司 一种移动设备及调整体征信息检测阈值的方法
CN106250825A (zh) * 2016-07-22 2016-12-21 厚普(北京)生物信息技术有限公司 一种在医保应用中场景自适应的人脸识别***
CN106599660A (zh) * 2016-12-02 2017-04-26 宇龙计算机通信科技(深圳)有限公司 终端安全验证方法及装置
US10586031B2 (en) * 2016-12-21 2020-03-10 Fingerprint Cards Ab Biometric authentication of a user
CN106599875A (zh) * 2016-12-23 2017-04-26 努比亚技术有限公司 指纹识别装置及方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160063235A1 (en) * 2014-08-28 2016-03-03 Kevin Alan Tussy Facial Recognition Authentication System Including Path Parameters
WO2017040867A1 (en) * 2015-09-01 2017-03-09 Quantum Interface, Llc. Apparatuses, systems and methods for constructing unique identifiers
CN106407776A (zh) * 2016-08-30 2017-02-15 深圳市金立通信设备有限公司 一种终端控制方法及终端
CN106599651A (zh) * 2016-11-17 2017-04-26 努比亚技术有限公司 一种终端解锁装置和方法
CN107451446A (zh) * 2017-07-18 2017-12-08 广东欧珀移动通信有限公司 解锁控制方法及相关产品

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP3637290A4

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