WO2017206913A1 - 移动终端的指纹注册方法和指纹识别方法 - Google Patents

移动终端的指纹注册方法和指纹识别方法 Download PDF

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Publication number
WO2017206913A1
WO2017206913A1 PCT/CN2017/086649 CN2017086649W WO2017206913A1 WO 2017206913 A1 WO2017206913 A1 WO 2017206913A1 CN 2017086649 W CN2017086649 W CN 2017086649W WO 2017206913 A1 WO2017206913 A1 WO 2017206913A1
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Prior art keywords
fingerprint
sub
image
fingerprint data
finger
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PCT/CN2017/086649
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English (en)
French (fr)
Inventor
杜俊涛
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深圳信炜科技有限公司
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Publication of WO2017206913A1 publication Critical patent/WO2017206913A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/12—Fingerprints or palmprints
    • G06V40/13—Sensors therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/12—Fingerprints or palmprints
    • G06V40/1365—Matching; Classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2221/00—Indexing scheme relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F2221/21—Indexing scheme relating to G06F21/00 and subgroups addressing additional information or applications relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F2221/2117—User registration
    • Y—GENERAL 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
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Definitions

  • the present invention relates to the field of fingerprint image processing, and in particular, to a fingerprint registration method and a fingerprint identification method for a mobile terminal.
  • the mobile terminal In the process of the fingerprint sensor application (eg, screen unlocking), the mobile terminal first collects the current fingerprint data through the fingerprint sensor, and then retrieves the fingerprint data in the pre-stored fingerprint database and the collected fingerprint data for one-to-one comparison; Whether to unlock the screen for the result.
  • the fingerprint sensor application e.g, screen unlocking
  • the target fingerprint data is sorted backwards in the process of fingerprint matching, the fingerprint matching response time is too long.
  • the mobile terminal stores a plurality of fingerprint data, and the above situation is easily and frequently caused, resulting in a poor user experience.
  • the present invention provides a fingerprint registration method for a mobile terminal to acquire a better fingerprint image quality in a short time based on a self-adjustable fingerprint sensing chip.
  • the present invention provides a fingerprint registration method for a mobile terminal, the mobile terminal includes a fingerprint sensor, and the fingerprint registration method includes the following steps:
  • Step a determining whether the mobile terminal is currently in the fingerprint registration mode
  • Step b If it is determined that the mobile terminal is in the fingerprint registration mode, the user is prompted to press the fingerprint sensor to input the finger fingerprint data;
  • Step c determining whether the fingerprint data of the finger is completed, if step d is performed, otherwise step c is performed;
  • Step d prompting the user whether to set the current finger fingerprint data as common finger fingerprint data
  • Step e If the user sets the current fingerprint data as the common fingerprint data, the finger input fingerprint data currently saved is set as the common fingerprint data and the initial configuration parameter of the current fingerprint sensor is saved in response to the user selection operation.
  • the fingerprint registration method further includes the step f: if the user sets the current fingerprint data as the backup fingerprint data, the current fingerprint fingerprint data is saved as the backup finger fingerprint data in response to the user selection operation.
  • the finger fingerprint data includes fingerprint feature point information.
  • the fingerprint registration method further includes: setting a common fingerprint data corresponding to an application permission.
  • the fingerprint registration method further includes: setting the standby finger fingerprint data to the authority of the application.
  • the application includes any one of a screen unlock, a payment, and an application lock.
  • the step e includes the following sub-steps:
  • Sub-step e1 initializing the fingerprint sensor to configure the fingerprint image full scan parameter
  • Sub-step e2 collecting one frame of fingerprint image according to the full scan parameter
  • Sub-step e3 cutting the background image in the frame fingerprint image
  • Sub-step e4 performing histogram statistics on the cut fingerprint image
  • Sub-step e5 coarsely adjusting the fingerprint image according to the histogram statistical result
  • Sub-step e6 fine-tuning the fingerprint image according to the coarse-tuned fingerprint image
  • Sub-step e7 calculating a fingerprint image quality score according to the coarse adjustment result and the fine adjustment result
  • Sub-step e8 determining whether the fingerprint image quality score is greater than a preset score, if it is sub-step e9, otherwise performing sub-step e2;
  • Sub-step b9 collecting one frame of fingerprint image and saving finger fingerprint data corresponding to the fingerprint image.
  • the invention also provides a fingerprint identification method for a mobile terminal, the mobile terminal comprising a fingerprint sensor, and the fingerprint identification method comprises the following steps:
  • Step S1 determining whether the fingerprint sensor collects finger fingerprint data
  • Step S2 If it is determined that the fingerprint sensor collects the finger fingerprint data, it is determined whether the currently collected fingerprint data matches the preset common fingerprint data;
  • Step S3 If it is determined that the currently collected fingerprint data matches the preset common fingerprint data, performing an application operation based on the identity authentication is performed.
  • the method further includes the following steps:
  • Step S4 If it is determined that the currently collected fingerprint data does not match the preset common fingerprint data, it is determined whether the currently collected fingerprint data is preset to match the alternate finger fingerprint data;
  • Step S5 If it is determined that the currently collected fingerprint data matches the preset alternate finger fingerprint data, perform an application operation based on the identity authentication, otherwise the user fingerprint is not matched.
  • step S1 includes the following sub-steps:
  • Sub-step c1 initializing the fingerprint sensor to configure the fingerprint image scanning parameter
  • Sub-step c2 collecting a frame of partial fingerprint image according to the local tracing parameter
  • Sub-step c3 cutting the background image in the partial image of the frame fingerprint
  • Sub-step c4 performing histogram statistics on the cut partial image of the fingerprint
  • Sub-step c5 coarsely adjusting the fingerprint image according to the histogram statistical result
  • Sub-step c6 fine-tuning the fingerprint image according to the coarse-tuned fingerprint image
  • Sub-step c7 performing fingerprint image quality scoring according to the adjusted fingerprint image
  • Sub-step c8 determining whether the score result is greater than a preset score, if it is sub-step c9, otherwise performing sub-step c2;
  • Sub-step c9 Acquire fingerprint data of a partial image of a fingerprint.
  • One of the fingers is set as the common finger fingerprint data according to the user's needs. Therefore, in the fingerprint recognition mode, when the fingerprint sensor detects that the user's finger fingerprint is pressed, the fingerprint sensor Collect current finger fingerprint data. The user presses the fingerprint sensor of the mobile terminal with a common finger at most times. Therefore, the mobile terminal compares the current finger fingerprint data with the commonly used finger fingerprint data first, so that the fingerprint matching comparison process time in the fingerprint recognition mode can be shortened, so as to improve the user experience of fingerprint recognition.
  • FIG. 1 is a flowchart of a fingerprint registration method of a mobile terminal according to the present invention.
  • FIG. 2 is a schematic diagram of a process user interface of the mobile terminal fingerprint registration method shown in FIG. 1.
  • FIG. 3 is a flow chart of obtaining a high quality fingerprint image in the fingerprint registration mode shown in FIG. 1.
  • FIG. 4 is a schematic circuit diagram of a fingerprint sensor portion of the fingerprint image adjustment shown in FIG. 3.
  • FIG. 5 is a comparison diagram of a frame of a fingerprint image before and after background cutting.
  • FIG. 6 is a histogram of the fingerprint image before cutting according to FIG. 5.
  • FIG. 7 is a histogram of the fingerprint image after cutting according to FIG. 5.
  • FIG. 8 is a flowchart of a fingerprint identification method of a mobile terminal according to the present invention.
  • FIG. 9 is a flow chart of acquiring a fingerprint image in the fingerprint recognition mode shown in FIG. 8.
  • the present invention comprehensively determines the fingerprint image quality from various angles of the fingerprint image, thereby ensuring that a higher quality fingerprint image is acquired in the fingerprint registration mode to obtain accurate and comprehensive user finger fingerprint feature point information.
  • FIG. 1 is a flowchart of a method for registering a fingerprint of a mobile terminal according to the present invention.
  • 2 is a schematic diagram of a process user interface of the mobile terminal fingerprint registration method shown in FIG. 1.
  • a fingerprint registration method for a mobile terminal the mobile terminal includes a fingerprint sensor, and the method includes the following steps:
  • Step a Initiate the fingerprint registration mode in response to the user's selection.
  • the fingerprint registration driver and the corresponding user manipulation interface are generally configured.
  • the user selects a fingerprint registration option on the setting option interface of the mobile terminal, and the mobile terminal pops up the fingerprint registration interface according to the user's selection to activate the fingerprint registration mode.
  • the fingerprint image quality integrated factor collected in the fingerprint registration mode is much higher than the fingerprint image quality collected in the fingerprint recognition mode.
  • fingerprint image quality synthesis factors include the size, resolution, resolution, etc. of a finger fingerprint image.
  • Step b prompt the user to press the fingerprint sensor to input the finger fingerprint data.
  • the fingerprint registration interface guides the user to press the fingerprint sensor. Compared with the size of the fingerprint image collected by fingerprint recognition, the fingerprint is registered as much as possible to guide the user to input an image of a larger area of a finger fingerprint.
  • the fingerprint recognition mode when the user enters the fingerprint registration, any partial fingerprint image in the fingerprint image can be verified and passed, so as to improve the success rate of fingerprint authentication and enhance the user experience.
  • Step c Determine whether the fingerprint data of the finger is completed. If the step d is performed, otherwise step c is performed.
  • the user In order to improve the authentication success rate of fingerprint recognition, the user is required to enter fingerprint image data to preserve the integrity of the fingerprint data information. Therefore, in the fingerprint registration mode, the quality comprehensive index of each aspect of the fingerprint image collected by the fingerprint sensor presets a threshold value, and if the command integrated score of the fingerprint image is greater than the preset threshold value, the currently input finger fingerprint is saved. Data, you can judge the finger fingerprint data to complete the input, otherwise re-acquire a frame of fingerprint image and score the fingerprint image quality.
  • Step d Prompt the user whether to set the current finger fingerprint data as common finger fingerprint data.
  • the authorized user when collecting a registered fingerprint from an authorized user, the authorized user inputs one or more fingerprint information in the user interface, or a plurality of authorized users input multiple fingerprint information in the user interface. Those fingerprints are processed, if necessary, to provide fingerprint information and such fingerprint information is registered in a database associated with the authorized user. Therefore, the fingerprint data stored in the fingerprint database in the mobile terminal is more. In the fingerprint identification mode, since the fingerprint data in the fingerprint database is random, it sometimes takes time to compare the currently collected fingerprint data with the fingerprint data stored in the database in the mobile terminal. If the fingerprint matching process is too long, the user experience is poor.
  • the common finger fingerprint data can be set as the common finger fingerprint data according to the user's needs.
  • the current finger fingerprint data to be collected is first Common finger fingerprint data is used for matching comparison. In this way, the user can quickly implement the finger fingerprint data matching comparison process and shorten the time of fingerprint authentication when the fingerprint authentication application is applied most of the time.
  • Step e If the user sets the current fingerprint data as the common fingerprint data, the finger input fingerprint data currently saved is set as the common fingerprint data and the initial configuration parameter of the current fingerprint sensor is saved in response to the user selection operation.
  • the fingerprint registration mode In the fingerprint registration mode, one of the fingers is set as the common finger fingerprint data according to the user's needs. Therefore, in the fingerprint recognition mode, when the fingerprint sensor detects that the user's finger fingerprint is pressed, the fingerprint sensor collects the current finger fingerprint data. The mobile terminal compares the current finger fingerprint data with the commonly used finger fingerprint data first, so that the fingerprint matching comparison process time in the fingerprint recognition mode can be shortened, so as to improve the user experience of fingerprint recognition.
  • the currently entered finger fingerprint data is saved as the backup finger fingerprint data in response to the user selection operation.
  • the fingerprint sensor detects that the user's finger fingerprint is pressed, the fingerprint sensor collects the current finger fingerprint data.
  • the mobile terminal compares the current finger fingerprint data with the commonly used finger fingerprint data first, and if the current finger fingerprint data does not match the common finger fingerprint data, further matches the current finger fingerprint data with the alternate finger fingerprint data one by one. .
  • the common fingerprint data is set to correspond to the permissions of the application.
  • the main purpose of the fingerprint sensor in the prior art is the authority authentication.
  • the fingerprint sensor collects the fingerprint data of the user and compares it with the stored instruction data with the authentication authority. If they are consistent, confirm that the user has authority.
  • the fingerprint authority authentication process is a process of confirming identity by comparing one fingerprint data collected in the field with the fingerprint data in the fingerprint database already registered.
  • the fingerprint data of the user must be marked in the fingerprint database. Book, that is, the fingerprint data of the user is stored in the device for which the authority is to be authenticated.
  • the fingerprint images of the users A, B, and C are stored in advance in the mobile terminal, or the fingerprint features of the users A, B, and C are stored.
  • the standby finger fingerprint data is set to correspond to the permission of the application.
  • the user sets the same application permissions to the alternate finger fingerprint data one by one.
  • the alternate finger fingerprint data and the common finger fingerprint data can set access rights for the same application.
  • the user can open the common fingerprint data and the alternate finger fingerprint data into different applications.
  • the index finger is set as a common finger, and the index finger is correspondingly set to a common application of the mobile terminal, such as an authentication-based unlock screen, a privacy file usage authority, and the like.
  • the middle finger is an alternate finger, and the middle finger corresponds to an authentication right that is set on the mobile terminal to perform a payment function.
  • determining the initial configuration parameter of the current fingerprint sensor in the step e includes the following substeps:
  • Sub-step e1 Initialize the fingerprint sensor to configure the fingerprint image full scan parameters.
  • the fingerprint sensor determines whether the mobile terminal is in the fingerprint registration mode or the fingerprint recognition mode. If it is determined that the mobile terminal is in the fingerprint registration mode, the fingerprint sensor is initialized to configure the fingerprint image full scan parameter.
  • Sub-step e2 Acquire a frame of fingerprint image according to the full scan parameter.
  • the fingerprint sensor scans one frame of the fingerprint image according to the full scan parameter and calculates the fingerprint data by extracting the fingerprint image.
  • Sub-step e3 Cutting the background image in the frame fingerprint image.
  • FIG. 5 is a comparison diagram before and after background cutting of a frame of fingerprint image.
  • FIG. 6 is a histogram of the fingerprint image before cutting according to FIG. 5.
  • FIG. 7 is a histogram of the fingerprint image after cutting according to FIG. 5.
  • the non-touch portion is cut off, that is, the background portion is not involved in fingerprint image analysis for scoring.
  • the background cutting principle is as follows: the image t is the segmentation threshold of the foreground and the background, that is, the grayscale is greater than t for the foreground, otherwise it is the background; the front view number accounts for the image ratio w 0 , the average gray scale is u 0 ; the background dots account for the image ratio w 1 , the average gray level is u 1 , then the total average gray level of the image is:
  • the maximum time t is the optimal threshold for the segmentation.
  • the formula is actually to find the variance between classes.
  • the foreground and background divided by the threshold t constitute the whole image, and the foreground value u 0 , the probability is w 0 , the background value u 1 , the probability is w 1 , the total mean is u, according to the definition of variance That is the formula. Since variance is a measure of the uniformity of gray distribution, the larger the variance value, the greater the difference between the two parts that make up the fingerprint image. When part of the target is divided into the background or part of the background is divided into the target, the difference between the two parts will be reduced. Therefore, the largest division between the variances of the classes means that the probability of misclassification is the smallest.
  • Sub-step e4 Performing histogram statistics on the cut fingerprint image.
  • the degree histogram describes the number of pixels of the gray level in the image and the frequency at which the gray level pixels appear. That is, the abscissa represents the gray level, and the ordinate represents the number or frequency of occurrence of the gray level in the image, that is, the statistical result of the gray histogram is calculated.
  • Sub-step e5 coarsely adjust the fingerprint image based on the histogram statistics.
  • the circuit parameter is such that the dynamic gain value of the current fingerprint image is close to the target fingerprint image dynamic gain value Gtarget .
  • FIG. 4 is a schematic diagram of a module of an automatic gain control circuit in a fingerprint sensor.
  • the automatic gain control circuit includes four stages of operational amplifier circuits A, B, C, and D.
  • the fingerprint sensing array 113 collects each frame of the fingerprint image and performs coarse adjustment of the fingerprint image through the four-stage operational amplifier circuits A, B, C, and D, so that the adjusted fingerprint image gain is roughly close to the target fingerprint image dynamic gain value G target .
  • Sub-step e6 Fine-tune the fingerprint image based on the coarse-tuned fingerprint image. Since the adjustment of the fingerprint image by the automatic gain control circuit according to the sub-step e5 can only be adjusted according to a specific multiple, the dynamic gain value of the adjusted fingerprint image cannot completely reach the target fingerprint image dynamic gain value G target . Referring to FIG. 4 further, it is necessary to further adjust the coarsely adjusted fingerprint image through the ADC circuit. At this time, the adjustment amplitude is relatively small, and the fingerprint image is dynamically closer to the target dynamic G target for the link gain.
  • Sub-step e7 Calculate the fingerprint image quality score based on the coarse adjustment result and the fine adjustment result.
  • Image quality scoring High-quality fingerprint images have a clear estimate of the alternating structure, and the block image gray scale has a large variance value.
  • the standard deviation method officially uses the standard variance of the local region gray value to measure the fingerprint image quality.
  • the image is divided into blocks of w x w, and the standard deviation of each partial block is first calculated.
  • G(x, y) is the gray value of the pixel point (x, y)
  • G k is the average gray value of the k blocks.
  • the quality score of the entire image is obtained by weighting the local variance and normalized.
  • l c is the center of the singular point region of the fingerprint image
  • q is a standardized constant
  • the contribution of the block is reflected by the distance from the block to the center of the singular point region of the image.
  • areas near the singularity of the fingerprint image provide more information than the surrounding area function and are therefore given a higher weight.
  • Sub-step e8 determining whether the fingerprint image quality score is greater than a preset score, if sub-step e9 is performed, otherwise sub-step e2 is performed. Judging the number of cycles according to the score, in the fingerprint image
  • the quality of the target score is set to Num2, assuming that the currently collected fingerprint image quality score is Score. If Score>Num2, exit the automatic gain adjustment of the current fingerprint image; otherwise, re-acquire a frame of fingerprint image and adjust its fingerprint image to achieve the best image.
  • Sub-step e9 collecting one frame of fingerprint image and saving finger fingerprint data corresponding to the fingerprint image. Save the common finger parameter configuration.
  • Score>Num2 the current frame of the fingerprint image is collected and the initial configuration parameters of the current fingerprint sensor are saved.
  • the fingerprint image acquired by the above fingerprint image evaluation has a higher overall quality.
  • the user can relatively lower the threshold of the collected fingerprint quality when performing fingerprint recognition, and it is easy to shorten the fingerprint comparison time in the fingerprint recognition process and improve the user experience.
  • FIG. 8 is a flowchart of a fingerprint identification method of a mobile terminal according to the present invention.
  • the mobile terminal includes a fingerprint sensor, and the fingerprint identification method of the mobile terminal includes the following steps:
  • Step S1 Determine whether the fingerprint sensor collects finger fingerprint data.
  • the process of fingerprint acquisition is essentially the process of fingerprint imaging.
  • the principle is to obtain different feedback signals according to the geometrical characteristics, physical characteristics and biological characteristics of ⁇ and ⁇ , and to form a fingerprint image according to the magnitude of the feedback signal.
  • the geometrical characteristics of the fingerprint mean that the space is raised in the space and the defect is concave. ⁇ and ⁇ intersect, connect, and separate will appear as some geometric patterns.
  • the biological characteristics of fingerprints refer to the difference in conductivity between yttrium and ytterbium, the difference in dielectric constant formed between air and air, and the difference in temperature.
  • the physical characteristics of the fingerprint refer to the difference in the pressure formed on the contact surface and the impedance to the wave when the ⁇ and ⁇ are on the horizontal plane.
  • fingerprint sensor actively sends a detection signal to the finger, and then analyzes the feedback signal to form a pattern of fingerprints and defects.
  • optical acquisition and RF acquisition are active acquisitions.
  • the other is the way the fingerprint sensor is passively sensed.
  • different sensing signals are formed because of the physical characteristics or biological characteristics of the fingerprints and sputum, and then the magnitude of the sensing signal is analyzed to form a fingerprint pattern.
  • Thermal absorption Set, semiconductor capacitor acquisition and semiconductor pressure sensing are passive acquisitions.
  • the fingerprint sensor For the fingerprint sensor, it generally passes through three main processes: “perceive finger”, “image taking”, “quality judgment and automatic adjustment”. Considering the power consumption of the device, the fingerprint sensor is generally in a sleep state when there is no finger contact. When the finger touches the fingerprint sensor, the fingerprint sensor quickly senses the contact of the finger and switches to the working state, and most of the semiconductor-type fingerprint sensors have such a sharp fingerprint sensing technology. In general, when a non-real finger touches the fingerprint sensor, fingerprint data cannot be collected.
  • the fingerprint data may be a fingerprint image, or may be a fingerprint feature extracted according to the fingerprint image. Or other data related to the fingerprint, which is not specifically limited herein.
  • Step S2 If it is determined that the fingerprint sensor is the finger fingerprint data, it is determined whether the currently collected fingerprint data matches the preset common fingerprint data. If a finger touches the fingerprint sensor or slides over the fingerprint sensor, fingerprint data is collected. At this time, the fingerprint sensor may report the collected fingerprint data to the processor, and specifically may send an interrupt message to the processor, or send A high/low level, etc.
  • the processor determines whether the currently collected fingerprint data matches the preset common finger fingerprint data.
  • Step S3 If it is determined that the currently collected fingerprint data matches the preset common finger fingerprint data, the identity authentication based application operation is performed.
  • the identity authentication based application operation includes illuminating the screen of the mobile terminal. Further, after the processor executes the instruction to illuminate the screen, an instruction to unlock the mobile terminal may also be performed to unlock the mobile terminal. For example, in a mobile terminal installed with an Android operating system, the following instruction can be executed to unlock the mobile terminal.
  • the fingerprint identification method further includes the following steps:
  • Step S4 If it is determined that the currently collected fingerprint data does not match the preset common finger fingerprint data, it is determined whether the currently collected fingerprint data is preset to match the alternate finger fingerprint data.
  • Step S5 If it is determined that the currently collected fingerprint data matches the preset alternate finger fingerprint data, Then, the application operation is performed based on the identity authentication, otherwise the user's fingerprint is not matched.
  • performing the identity authentication based application operation includes illuminating the screen of the mobile terminal. Further, after the processor executes the instruction to illuminate the screen, an instruction to unlock the mobile terminal may also be performed to unlock the mobile terminal. For example, in a mobile terminal installed with an Android operating system, the following instruction can be executed to unlock the mobile terminal.
  • the identity authentication based payment operation is performed.
  • step S1 includes the following sub-steps:
  • Sub-step c1 Initialize the fingerprint sensor to configure the fingerprint image scan parameters.
  • the fingerprint sensor is initialized to configure the fingerprint image partial scan parameter.
  • Sub-step c2 Acquire a frame of partial fingerprint image according to the local tracing parameter.
  • the fingerprint sensor scans one frame of the fingerprint partial image according to the partial scan parameter and calculates the fingerprint data by extracting the fingerprint partial image.
  • Sub-step c3 cutting the background image in the partial image of the frame fingerprint.
  • FIG. 5 is a schematic diagram of a frame of fingerprint image cutting.
  • the non-touch portion is cut off, that is, the background portion is not involved in fingerprint image analysis for scoring.
  • the method for cutting the background image in the partial image of the frame fingerprint is the same as the principle of the foregoing sub-step e3, and details are not described herein again.
  • Sub-step c4 Performing histogram statistics on the cut partial image of the fingerprint.
  • Sub-step c5 coarsely adjust the fingerprint partial image according to the histogram statistical result.
  • Sub-step c6 Fine-tune the fingerprint partial image according to the coarse-tuned fingerprint image.
  • Sub-step c7 Performing a fingerprint partial image quality score according to the adjusted fingerprint image.
  • Sub-step c8 determining whether the score result is greater than a preset score, and if performing sub-step c9, Otherwise, sub-step c2 is performed;
  • Sub-step c9 Acquire fingerprint data of a partial image of a fingerprint.
  • the fingerprint image acquired by the above fingerprint image evaluation has a higher overall quality. In this way, the user can relatively lower the threshold of the collected fingerprint quality when performing fingerprint recognition, and it is easy to shorten the fingerprint comparison time in the fingerprint recognition process and improve the user experience.

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Abstract

一种移动终端的指纹注册方法，移动终端包括一指纹传感器。指纹注册方法包括：步骤a：判断移动终端当前是否处于指纹注册模式；步骤b：若判断移动终端处于指纹注册模式，则提示用户按压指纹传感器录入手指指纹数据；步骤c：判断手指指纹数据是否完成录入，若是执行步骤d，否则执行步骤c；步骤d：提示用户是否将当前手指指纹数据设置为常用手指指纹数据；步骤e：若用户将当前采指纹数据设置为常用指纹数据，则响应用户选择操作将当前录入的手指指纹数据保存设置为常用手指指纹数据并保存当前指纹传感器的初始化配置参数。用户在绝大多数时间使用常用指纹作为登录移动终端凭证，可缩短指纹匹配比对过程时间，以提高用户体验感。

Description

移动终端的指纹注册方法和指纹识别方法 技术领域
本发明涉及指纹图像处理领域，尤其涉及一种移动终端的指纹注册方法和指纹识别方法。
背景技术
移动终端基于指纹传感器应用(如，屏幕解锁)过程中，首先通过指纹传感器采集当前的指纹数据，然后调取预存指纹数据库中的指纹数据与采集到的指纹数据进行一一比对；最后根据比对结果是否进行解锁屏幕。
然，若在一次指纹比对过程中，若目标指纹数据被调取的排序靠后而导致指纹匹配响应时间过长。移动终端存储多个指纹数据而容易经常性的出现上述情况，导致用户体验感不佳。
发明内容
鉴于此，本发明提供一种移动终端基于可自调节指纹传感芯片在短时间内获取较好指纹图像质量的指纹注册方法。
本发明提供了一种移动终端的指纹注册方法，所述移动终端包括一指纹传感器，所述指纹注册方法包括以下步骤：
步骤a：判断移动终端当前是否处于指纹注册模式；
步骤b：若判断移动终端处于指纹注册模式，则提示用户按压指纹传感器录入手指指纹数据；
步骤c：判断手指指纹数据是否完成录入，若是执行步骤d，否则执行步骤c；
步骤d：提示用户是否将当前手指指纹数据设置为常用手指指纹数据；
步骤e：若用户将当前采指纹数据设置为常用指纹数据，则响应用户选择操作将当前录入的手指指纹数据保存设置为常用指纹数据并保存当前指纹传感器的初始化配置参数。
在某些实施方式中，所述指纹注册方法还包括步骤f：若用户将当前采指纹数据设置为备用手指指纹数据，响应用户选择操作将当前录入的手指指纹数据保存设置为备用手指指纹数据。
在某些实施方式中，所述手指指纹数据包括指纹特征点信息。
在某些实施方式中，所述指纹注册方法还包括：设置常用指纹数据对应应用程序的权限。
在某些实施方式中，所述指纹注册方法还包括：设置备用手指指纹数据对应应用程序的权限。
在某些实施方式中，所述应用程序包括屏幕解锁、支付、应用锁中任意一种。
在某些实施方式中，所述步骤e包括如下子步骤：
子步骤e1：初始化指纹传感器以配置指纹图像全扫描参数；
子步骤e2：根据全扫描参数采集一帧指纹图像；
子步骤e3：切割该帧指纹图像中的背景图像；
子步骤e4：将切割后的指纹图像进行直方图统计；
子步骤e5：根据直方图统计结果粗调指纹图像；
子步骤e6：根据粗调指纹图像进行微调指纹图像；
子步骤e7：根据粗调结果和微调结果计算指纹图像质量得分；
子步骤e8：判断指纹图像质量得分是否大于预设分值，若是执行子步骤e9，否则执行子步骤e2；
子步骤b9：采集一帧指纹图像并保存对应指纹图像的手指指纹数据。
本发明还提供了一种移动终端的指纹识别方法，所述移动终端包括一指纹传感器，所述指纹识别方法包括以下步骤：
步骤S1：判断指纹传感器是否采集到手指指纹数据；
步骤S2：若判断指纹传感器采集到手指指纹数据，则判断当前采集的指纹数据是否与预设常用指纹数据匹配；
步骤S3：若判断当前采集的指纹数据与预设常用指纹数据匹配，则执行基于身份鉴权执行应用操作。
进一步地，所述方法还包括以下步骤：
步骤S4：若判断当前采集的指纹数据与预设常用指纹数据不匹配，则判断当前采集的指纹数据是否预设备用手指指纹数据匹配；
步骤S5：若判断当前采集的指纹数据与预设备用手指指纹数据匹配，则执行基于身份鉴权执行应用操作，否则提示用户指纹不匹配。
进一步地，所述步骤S1包括如下子步骤：
子步骤c1：初始化指纹传感器以配置指纹图像扫描参数；
子步骤c2：根据局部描参数采集一帧局部指纹图像；
子步骤c3：切割该帧指纹局部图像中的背景图像；
子步骤c4：将切割后的指纹局部图像进行直方图统计；
子步骤c5：根据直方图统计结果粗调指纹图像；
子步骤c6：根据粗调指纹图像进行微调指纹图像；
子步骤c7：根据调整后的指纹图像进行指纹图像质量评分；
子步骤c8：判断评分结果是否大于预设分值，若是执行子步骤c9，否则执行子步骤c2；
子步骤c9：获取一帧指纹局部图像的指纹数据。
根据用户需求将其中之一手指设定为常用手指指纹数据。因此，在指纹识别模式下，当指纹传感器检测到有用户手指指纹按压时，指纹传感器 采集当前的手指指纹数据。而用户在绝大多数时间采用常用手指按压操作移动终端的指纹传感器。因此移动终端将当前的手指指纹数据首先与常用手指指纹数据进行比对，这样可以缩短在指纹识别模式下的指纹匹配比对过程时间，以提高用户指纹识别的体验感。
尽管公开了多个实施例，包括其变化，但是通过示出并描述了本发明公开的说明实施例的下列详细描述，本发明公开的其他实施例将对所属领域的技术人员显而易见。将认识到，本发明公开能够在各种显而易见的方面修改，所有修改都不会偏离本发明的精神和范围。相应地，附图和详细描述本质上应被视为说明性的，而不是限制性的。
附图说明
通过参照附图详细描述其示例实施方式，本发明的其它特征及优点将变得更加明显。
图1为本发明移动终端的指纹注册方法的流程图。
图2为图1所示移动终端指纹注册方法的过程用户界面示意图。
图3为图1所示指纹注册模式中获取高质量指纹图像的流程图。
图4是图3所示指纹图像调整的指纹传感器部分电路示意图。
图5为一帧指纹图像背景切割前后的对比图。
图6为图5所示指纹图像切割前直方统计图。
图7为图5所示指纹图像切割后直方统计图。
图8为本发明移动终端的指纹识别方法流程图。
图9为图8所示指纹识别模式中获取指纹图像的流程图。
具体实施方式
现在将参考附图更全面地描述示例实施方式。然而，示例实施方式能 够以多种形式实施，且不应被理解为限于在此阐述的实施方式；相反，提供这些实施方式使得本发明将全面和完整，并将示例实施方式的构思全面地传达给本领域的技术人员。在图中相同的附图标记表示相同或类似的结构。
所描述的特征或结构可以以任何合适的方式结合在一个或更多实施方式中。在下面的描述中，提供许多具体细节从而给出对本发明的实施方式的充分理解。然而，本领域技术人员应意识到，没有所述特定细节中的一个或更多，或者采用其它的结构、组件等，也可以实践本发明的技术方案。在其它情况下，不详细示出或描述公知结构或者操作以避免模糊本发明。
由于指纹图像质量的好坏取决多个角度考察，而不仅仅某一维度可以判定指纹图像质量。因此本发明综合指纹图像各个角度来确定指纹图像质量的评判，从而确保在指纹注册模式下，采集较高质量的指纹图像而获取准确全面的用户手指指纹特征点信息。
请一并参考图1和图2，图1为本发明移动终端的指纹注册方法流程图。图2为图1所示移动终端指纹注册方法的过程用户界面示意图。一种移动终端的指纹注册方法，所述移动终端包括一指纹传感器，所述方法包括以下步骤：
步骤a：响应用户的选择启动指纹注册模式。
指纹传感器安装于移动终端之中时一般配置有指纹注册驱动程序及对应的用户操控界面。用户在移动终端的设置选项界面选择指纹注册选项，移动终端根据用户的选择弹出指纹注册界面以启动指纹注册模式。指纹注册模式下采集的指纹图像质量综合因素要求远远高于指纹识别模式下采集的指纹图像质量。如指纹图像质量综合因素包括采集一枚手指指纹图像的面积大小、清晰度、分辨率等。
步骤b：提示用户按压指纹传感器录入手指指纹数据。
指纹注册界面引导用户按压指纹传感器。相比较指纹识别采集的指纹图像的大小而言，指纹注册时尽可能引导用户录入一手指指纹较大面积的图像。使得移动终端在指纹识别模式下，用户录入指纹注册时指纹图像中的任何一局部指纹图像即可验证通过，以提高指纹鉴权的成功率和提升用户的体验感。
步骤c：判断手指指纹数据是否完成录入，若是执行步骤d，否则执行步骤c。
为了提升指纹识别的鉴权成功率，要求用户录入指纹图像数据保存指纹数据信息的完整性。因此，在指纹注册模式下，指纹传感器采集的指纹图像各方面的质量综合指标预设一门槛值，若采集指纹图像的指令综合分值大于所述预设门槛值，则保存当前录入的手指指纹数据，即可判断手指指纹数据完成录入，否则重新采集一帧指纹图像并进行指纹图像质量进行评分。
步骤d：提示用户是否将当前手指指纹数据设置为常用手指指纹数据。
一般地，从授权用户收集注册指纹时，授权用户在该用户界面中输入一个或多个指纹信息，或者多个授权用户在在该用户界面中输入多个指纹信息。如果必要的话对那些指纹进行处理以提供指纹信息并且将这种指纹信息注册在与该授权用户相关联的数据库中。因此，导致移动终端中的指纹数据库存储的指纹数据信息较多。在指纹识别模式中，由于调取指纹数据库中指纹数据是随机的，因此有时会发生将当前采集的指纹数据与移动终端中数据库存储的指纹数据信息进行一一比对过程是耗时的。若经常性地指纹比对过程时间过长导致用户体验感较差。
当在指纹注册时，根据用户的需求可将常用手指指纹数据设置为常用手指指纹数据。当在指纹识别模式下，将采集的当前手指指纹数据首先与 常用手指指纹数据进行匹配比对。这样可使得用户在大部分时间指纹鉴权应用时，能够快速实现手指指纹数据匹配比对过程，缩短指纹鉴权的时间。
步骤e：若用户将当前采指纹数据设置为常用指纹数据，则响应用户选择操作将当前录入的手指指纹数据保存设置为常用指纹数据并保存当前指纹传感器的初始化配置参数。
在指纹注册模式中，根据用户需求将其中之一手指设定为常用手指指纹数据。因此，在指纹识别模式下，当指纹传感器检测到有用户手指指纹按压时，指纹传感器采集当前的手指指纹数据。移动终端将当前的手指指纹数据首先与常用手指指纹数据进行比对，这样可以缩短在指纹识别模式下的指纹匹配比对过程时间，以提高用户指纹识别的体验感。
若用户将当前采指纹数据设置为备用手指指纹数据，响应用户选择操作将当前录入的手指指纹数据保存设置为备用手指指纹数据。
当然，当用户选择当前录入的手指指纹数据为备用手指指纹数据。因此，在指纹识别模式下，当指纹传感器检测到有用户手指指纹按压时，指纹传感器采集当前的手指指纹数据。移动终端将当前的手指指纹数据首先与常用手指指纹数据进行比对，若当前手指指纹数据与常用手指指纹数据不匹配时，再进一步地将当前的手指指纹数据与备用手指指纹数据进行一一匹配。
进一步地，设置常用指纹数据对应应用程序的权限。
现有技术中指纹传感器的主要用途是权限认证，当用户将手指接触指纹传感器或者滑过指纹传感器时，指纹传感器采集用户的指纹数据，并与已存储的具有认证权限的指令数据进行比对，若一致则确认所述用户具有权限。指纹权限认证过程就是通过把一个现场采集到的指纹数据与已经登记的指纹库中的指纹数据进行一对一的比对，来确认身份的过程。一般来说，作为权限认证成功的前提条件，该用户的指纹数据须在指纹库中已注 册，即将该用户的指纹数据存储在欲进行权限认证的设备中。
例如若用户A、用户B、用户C具有使用该移动终端的权限，则在该移动终端中预先存储用户A、B、C的指纹图像，或者存储有用户A、B、C的指纹特征。
进一步地，设置备用手指指纹数据对应应用程序的权限。
同理，用户将备用手指指纹数据一一对应设置相同的应用程序权限。备用手指指纹数据和常用手指指纹数据可设置相同应用程序的访问权限。
当然，用户可以将常用指纹数据与备用手指指纹数据开启不同的应用程序。例如，食指设置为常用手指，食指对应设置为移动终端的常用的应用程序，如基于身份验证的解锁屏、隐私文件使用权限等。而中指为备用手指，中指对应设置在移动终端上执行支付功能的身份验证权限。
进一步地，所述步骤e中的确定当前指纹传感器的初始化配置参数包括如下子步骤：
子步骤e1：初始化指纹传感器以配置指纹图像全扫描参数。在本步骤中，指纹传感器判断移动终端处于指纹注册模式还是指纹识别模式？若判断移动终端处于指纹注册模式中，则初始化指纹传感器以配置指纹图像全扫描参数。
子步骤e2：根据全扫描参数采集一帧指纹图像。在本步骤中，指纹传感器根据全扫描参数扫描一帧指纹图像并将指纹图像计算提取指纹数据。
子步骤e3：切割该帧指纹图像中的背景图像。在本步骤中，请一并参考图5、图6及图7，其中图5为一帧指纹图像背景切割前后的对比图。图6为图5所示指纹图像切割前直方统计图。图7为图5所示指纹图像切割后直方统计图。在将非触摸部分切除，即背景部分不参与指纹图像分析进行评分。
背景切割原理如下：图像记t为前景与背景的分割阈值，即灰度大于t为前景，否则为背景；前景点数占图像比例为w0，平均灰度为u0；背景点数占图像比例为w1，平均灰度为u1，则图像的总平均灰度为：
u＝w0*u0+w1*u1
从最小灰度值到最大灰度值遍历t，当t使得值：
g＝w0*(u0-u)2+w1*(u1-u)2
最大时的t即为分割的最佳阈值。
该公式实际上就是求类间方差值。其中，阈值t分割出的前景和背景两部分构成了整幅图像，而前景取值u0，概率为w0，背景取值u1，概率为w1，总均值为u，根据方差的定义即得该公式。因方差是灰度分布均匀性的一种度量，方差值越大，说明构成指纹图像的两部分差别越大。当部分目标错分为背景或部分背景错分为目标都会导致两部分差别变小，因此使类间方差最大的分割意味着错分概率最小。
子步骤e4：将切割后的指纹图像进行直方图统计。在本步骤中，度直方图描述的是图像中该灰度级的像素个数和该灰度级像素出现的频率。即：横坐标表示灰度级，纵坐标表示图像中该灰度级出现的个数或频率，即计算得出灰度直方图统计结果。
子步骤e5：根据直方图统计结果粗调指纹图像。在本步骤中，根据灰度直方图统计结果确定当前指纹图像的动态增益值Gcruuent和目标指纹图像动态增益值Gtarget，根据上述两者比值G＝Gtarget/Gcruuent调整自动增益控制电路的电路参数，使得当前指纹图像的动态增益值接近目标指纹图像动态增益值Gtarget。
请参阅图4，为指纹传感器中自动增益控制电路的模块示意图。所述自动增益控制电路包括四级运放电路A，B，C，D。指纹传感阵列113采集每一帧指纹图像经过四级运放电路A，B，C，D进行指纹图像的粗调，使得调整后的指纹图像增益粗略的接近目标指纹图像动态增益值Gtarget。
子步骤e6：根据粗调指纹图像进行微调指纹图像。由于根据子步骤e5通过自动增益控制电路对指纹图像进行调节只能按照特定倍数进行调整，导致调整后的指纹图像的动态增益值不能完全到达目标指纹图像动态增益值Gtarget。进一步参阅图4，因此需要对粗调后的指纹图像通过ADC电路进一步进行调整，此时调整幅度相对较小，为了链路增益，指纹图像动态更接近目标动态Gtarget。
子步骤e7：根据粗调结果和微调结果计算指纹图像质量得分。图像质量打分：高质量的指纹图像具有清晰的估计交替的结构，其分块图像灰度有较大的方差值。标准差方法正式利用局部区域灰度值的标准方差来衡量指纹图像质量。将图像分成w x w的块，首先计算每一局部块的标准方差。
Figure PCTCN2017086649-appb-000001
其中G(x,y)为像素点(x,y)的灰度值，Gk是地k个块的平均灰度值。
整个图像的质量得分是通过加权方式求局部方差的和，并标准化，
Figure PCTCN2017086649-appb-000002
其中，C2是一个常数用来标准化最终的质量得分，使其值位于[0,1]内，N为整幅指纹图像被划分的总块数。对于中心在li＝(xi,yi)的地i块图像，其相对权重wi的计算如下：
wi＝exp{-||li-lc||2/(2q)}
其中，lc为指纹图像奇异点区的中心，q是一个标准化的常量，用块到图像奇异点区中心的距离来反映块的贡献。通常来说，靠近指纹图像奇异点的区域比周围区域功能提供更多的信息，因此被赋予了较高的权重。
子步骤e8：判断指纹图像质量得分是否大于预设分值，若是执行子步骤e9，否则执行子步骤e2。根据打分情况判断循环次数，在指纹图像 质量的为目标得分设置为Num2，假设当前采集的指纹图像质量的评分为Score。若当Score>Num2时，退出当前指纹图像的自动增益调整；否则重新采集一帧指纹图像并对其指纹图像进行调整以达到最佳图像。
子步骤e9：采集一帧指纹图像并保存对应指纹图像的手指指纹数据。保存常用手指参数配置。当Score>Num2时，采集当前一帧指纹图像并保存当前指纹传感器的初始化配置参数。
在指纹注册模式下，通过上述指纹图像评价而采集的指纹图像综合质量较高的。这样可以使得用户在做指纹识别时，对采集的指纹质量门槛相对要求较低，容易缩短指纹识别过程中指纹比对时间，提升用户的体验感。
请参阅图8，为本发明移动终端的指纹识别方法流程图。所述移动终端包括一指纹传感器，所述移动终端的指纹识别方法包括以下步骤：
步骤S1：判断指纹传感器是否采集到手指指纹数据。
指纹采集的过程本质上是指纹成像的过程。其原理是根据嵴与峪的几何特性、物理特征和生物特性的不同，以得到不同的反馈信号，根据反馈信号的量值来绘成指纹图像。
指纹的几何特性是指在空间上嵴是突起的，峪是凹下的。嵴与嵴相交、相连、分开会表现为一些几何图案。指纹的生物特性是指嵴和峪的导电性不同，与空气之间形成的介电常数不同、温度不同等。指纹的物理特性是指嵴和峪着力在水平面上时，对接触面形成的压力不同、对波的阻抗不同等。
指纹采集的方法有两种，一种是由指纹传感器主动向手指发出探测信号，然后分析反馈信号，以形成指纹嵴与峪的图案。如光学采集和射频采集属于主动式采集。另一种是指纹传感器是被动感应的方式。当手指放置到指纹传感器上时，因为指纹嵴和峪的物理特性或生物特性的不同，会形成不同的感应信号，然后分析感应信号的量值来形成指纹图案。如热敏采 集、半导体电容采集和半导体压感采集属于被动式采集。
对指纹传感器来讲，一般经过“感知手指”、“图像拍照”、“质量判断与自动调整”三个主要过程。考虑到设备功耗，在无手指接触时，指纹传感器一般处于休眠状态。当手指接触到指纹传感器时，指纹传感器会迅速感知到手指的接触并切换到工作状态，对于半导体类指纹传感器大多具有这种敏锐的指纹察觉技术。一般来说，非真实的手指接触指纹传感器时，是无法采集得到指纹数据的。其中，所述指纹数据可以为指纹图像，或者也可以为根据指纹图像提取的指纹特征。或者是其他的与指纹相关的数据信息，在此不做具体限定。
步骤S2：若判断指纹传感器是集到手指指纹数据，则判断当前采集的指纹数据是否与预设常用指纹数据匹配。若有手指接触所述指纹传感器或者滑过所述指纹传感器，会采集到指纹数据，此时指纹传感器可以向处理器上报已采集到指纹数据，具体的可以向处理器发送一个中断消息、或者发送一个高/低电平等。
当处理器得知指纹传感器已采集到指纹数据，则判断当前采集的指纹数据是否与预设常用手指指纹数据匹配。
步骤S3：若判断当前采集的指纹数据与预设常用手指指纹数据匹配，则执行基于身份鉴权的应用操作。基于身份鉴权的应用操作包括点亮移动终端的屏幕。进一步的，当处理器执行点亮屏幕的指令之后，还可以执行解锁移动终端的指令，解锁移动终端。例如，在安装有安卓操作系统的移动终端中，可以执行下述指令解锁移动终端。
所述指纹识别方法还包括以下步骤：
步骤S4：若判断当前采集的指纹数据与预设常用手指指纹数据不匹配，则判断当前采集的指纹数据是否预设备用手指指纹数据匹配。
步骤S5：若判断当前采集的指纹数据与预设备用手指指纹数据匹配， 则执行基于身份鉴权执行应用操作，否则提示用户指纹不匹配。
若判断当前采集的指纹数据与预设备用手指指纹数据匹配，执行基于身份鉴权的应用操作包括点亮移动终端的屏幕。进一步的，当处理器执行点亮屏幕的指令之后，还可以执行解锁移动终端的指令，解锁移动终端。例如，在安装有安卓操作系统的移动终端中，可以执行下述指令解锁移动终端。
另外，若用户预先设定备用手指指纹数据为支付应用操作，若判断当前采集的指纹数据与预设备用手指指纹数据匹配，执行基于身份鉴权的支付操作。
进一步地，所述步骤S1包括如下子步骤：
子步骤c1：初始化指纹传感器以配置指纹图像扫描参数。在本步骤中，移动终端处于指纹注册模式中，则初始化指纹传感器以配置指纹图像局部扫描参数。
子步骤c2：根据局部描参数采集一帧局部指纹图像。在本步骤中，指纹传感器根据局部扫描参数扫描一帧指纹局部图像并将指纹局部图像计算提取指纹数据。
子步骤c3：切割该帧指纹局部图像中的背景图像。在本步骤中，请参考图5所示，为一帧指纹图像切割的示意图。在将非触摸部分切除，即背景部分不参与指纹图像分析进行评分。由于切割该帧指纹局部图像中的背景图像的方法与前述子步骤e3原理相同，在此不再赘述。
子步骤c4：将切割后的指纹局部图像进行直方图统计。
子步骤c5：根据直方图统计结果粗调指纹局部图像。
子步骤c6：根据粗调指纹图像进行微调指纹局部图像。
子步骤c7：根据调整后的指纹图像进行指纹局部图像质量评分。
子步骤c8：判断评分结果是否大于预设分值，若是执行子步骤c9， 否则执行子步骤c2；
子步骤c9：获取一帧指纹局部图像的指纹数据。
通过上述指纹图像评价而采集的指纹图像综合质量较高的。这样可以使得用户在做指纹识别时，对采集的指纹质量门槛相对要求较低，容易缩短指纹识别过程中指纹比对时间，提升用户的体验感。
尽管是参考各实施例来描述本公开，但是可以理解，这些实施例是说明性的，并且本发明的范围不仅限于它们。许多变化、修改、添加、以及改进都是可能的。更一般而言，根据本发明公开的各实施例是在特定实施例的上下文中描述的。功能可以在本发明公开的各实施例中在过程中以不同的方式分离或组合，或利用不同的术语来描述。这些及其他变化、修改、添加、以及改进可以在如随后的权利要求书所定义的本发明公开的范围内。

Claims (10)

  1. 一种移动终端的指纹注册方法，其特征在于，所述移动终端包括一指纹传感器，所述方法包括以下步骤：
    步骤a：判断移动终端当前是否处于指纹注册模式；
    步骤b：若判断移动终端处于指纹注册模式，则提示用户按压指纹传感器录入手指指纹数据；
    步骤c：判断手指指纹数据是否完成录入，若是执行步骤d，否则执行步骤c；
    步骤d：提示用户是否将当前手指指纹数据设置为常用手指指纹数据；
    步骤e：若用户将当前采指纹数据设置为常用指纹数据，则响应用户选择操作将当前录入的手指指纹数据保存设置为常用手指指纹数据并保存当前指纹传感器的初始化配置参数。
  2. 根据权利要求1所述的指纹注册方法，其特征在于，所述指纹注册方法还包括步骤f：若用户将当前采指纹数据设置为备用手指指纹数据，响应用户选择操作将当前录入的手指指纹数据保存设置为备用手指指纹数据。
  3. 根据权利要求1所述的指纹注册方法，其特征在于，所述手指指纹数据包括指纹特征点信息。
  4. 根据权利要求1所述的指纹注册方法，其特征在于，所述指纹注册方法还包括：设置常用指纹数据对应应用程序的权限。
  5. 根据权利要求2所述的指纹注册方法，其特征在于，所述指纹注册方法还包括：设置备用手指指纹数据对应应用程序的权限。
  6. 根据权利要求4或5所述的指纹注册方法，其特征在于，所述应用程序包括屏幕解锁、支付、应用锁中任意一种。
  7. 根据权利要求1所述的指纹注册方法，其特征在于，所述步骤e包 括如下子步骤：
    子步骤e1：初始化指纹传感器以配置指纹图像全扫描参数；
    子步骤e2：根据全扫描参数采集一帧指纹图像；
    子步骤e3：切割该帧指纹图像中的背景图像；
    子步骤e4：将切割后的指纹图像进行直方图统计；
    子步骤e5：根据直方图统计结果粗调指纹图像；
    子步骤e6：根据粗调指纹图像进行微调指纹图像；
    子步骤e7：根据粗调结果和微调结果计算指纹图像质量得分；
    子步骤e8：判断指纹图像质量得分是否大于预设分值，若是执行子步骤e9，否则执行子步骤e2；
    子步骤b9：采集一帧指纹图像并保存所述指纹传感器的初始化配置参数。
  8. 一种移动终端的指纹识别方法，其特征在于，所述移动终端包括一指纹传感器，所述方法包括以下步骤：
    步骤S1：判断指纹传感器是否采集到手指指纹数据；
    步骤S2：若判断指纹传感器采集到手指指纹数据，判断当前采集的指纹数据是否与预设常用指纹数据匹配；
    步骤S3：若判断当前采集的指纹数据与预设常用指纹数据匹配，则执行基于身份鉴权执行应用操作。
  9. 根据权利要求8所述的指纹识别方法，其特征在于，所述方法还包括以下步骤：
    步骤S4：若判断当前采集的指纹数据与预设常用指纹数据不匹配，则判断当前采集的指纹数据是否预设备用手指指纹数据匹配；
    步骤S5：若判断当前采集的指纹数据与预设备用手指指纹数据匹配，则执行基于身份鉴权执行应用操作，否则提示用户指纹不匹配。
  10. 根据权利要求8所述的指纹识别方法，其特征在于，所述步骤S1包括如下子步骤：
    子步骤c1：初始化指纹传感器以配置指纹图像扫描参数；
    子步骤c2：根据局部描参数采集一帧局部指纹图像；
    子步骤c3：切割该帧指纹局部图像中的背景图像；
    子步骤c4：将切割后的指纹局部图像进行直方图统计；
    子步骤c5：根据直方图统计结果粗调指纹图像；
    子步骤c6：根据粗调指纹图像进行微调指纹图像；
    子步骤c7：根据调整后的指纹图像进行指纹图像质量评分；
    子步骤c8：判断评分结果是否大于预设分值，若是执行子步骤c9，否则执行子步骤c2；
    子步骤c9：获取一帧指纹局部图像的指纹数据。
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