WO2016176989A1 - 移动终端基于眼纹识别的图像曝光方法及图像曝光系统 - Google Patents

移动终端基于眼纹识别的图像曝光方法及图像曝光系统 Download PDF

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Publication number
WO2016176989A1
WO2016176989A1 PCT/CN2015/096654 CN2015096654W WO2016176989A1 WO 2016176989 A1 WO2016176989 A1 WO 2016176989A1 CN 2015096654 W CN2015096654 W CN 2015096654W WO 2016176989 A1 WO2016176989 A1 WO 2016176989A1
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Prior art keywords
exposure
parameter
image
mobile terminal
recognition
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PCT/CN2015/096654
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English (en)
French (fr)
Inventor
唐向东
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捷开通讯(深圳)有限公司
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Priority to US15/110,066 priority Critical patent/US10437972B2/en
Publication of WO2016176989A1 publication Critical patent/WO2016176989A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/08—Network architectures or network communication protocols for network security for authentication of entities
    • H04L63/0861—Network architectures or network communication protocols for network security for authentication of entities using biometrical features, e.g. fingerprint, retina-scan
    • 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
    • G06V40/18—Eye characteristics, e.g. of the iris
    • 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
    • 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
    • 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
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • G06V40/174—Facial expression recognition
    • 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
    • G06V40/18—Eye characteristics, e.g. of the iris
    • G06V40/19—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
    • G06V40/18—Eye characteristics, e.g. of the iris
    • G06V40/193—Preprocessing; Feature extraction
    • 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
    • G06V40/18—Eye characteristics, e.g. of the iris
    • G06V40/197—Matching; Classification
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/61—Control of cameras or camera modules based on recognised objects
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/61—Control of cameras or camera modules based on recognised objects
    • H04N23/611—Control of cameras or camera modules based on recognised objects where the recognised objects include parts of the human body
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/63—Control of cameras or camera modules by using electronic viewfinders
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/70—Circuitry for compensating brightness variation in the scene
    • H04N23/71—Circuitry for evaluating the brightness variation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/70—Circuitry for compensating brightness variation in the scene
    • H04N23/73—Circuitry for compensating brightness variation in the scene by influencing the exposure time
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/70—Circuitry for compensating brightness variation in the scene
    • H04N23/76—Circuitry for compensating brightness variation in the scene by influencing the image signals
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/06—Authentication
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/08—Access security

Definitions

  • the present invention relates to the field of mobile terminal technologies, and in particular, to an image exposure method and an image exposure system based on eye mark recognition of a mobile terminal.
  • the eye pattern recognition lock screen software is a lock screen software that protects the privacy of the user's mobile phone. Since each person's eye texture is different, and the general situation will not change much, the eye pattern recognition lock screen software uses this principle to determine whether it is the owner of the phone by analyzing the eye pattern.
  • Eye pattern recognition lock screen software use process For the first time, the user must enter his own eye texture information, just like the face recognition lock screen software. At the same time, you need to enter an alternative unlock method. Because the image recognition lock screen software can unlock the screen with a certain probability, set an alternative unlocking method, such as a password or a nine-square pattern, so that the alternate unlocking method can be enabled when the eye pattern recognition fails.
  • an alternative unlocking method such as a password or a nine-square pattern
  • the principle of eye pattern recognition lock screen software use the front camera to obtain several eye images of the user, and then perform data processing on these pictures to obtain the user's eye pattern information and save it to the mobile phone local.
  • the eye pattern recognition software opens the front camera (ie, camera), acquires the user's eye pattern information again, and compares the information with the pre-stored eye information to determine whether it is the owner of the mobile phone.
  • the eye pattern recognition lock screen software uses the front camera to obtain the user's eye picture information. Then process and analyze these image data. Therefore, the image quality of the front camera is relatively high.
  • the technical problem to be solved by the present invention is to provide an image exposure method and an exposure system based on eye mark recognition for a mobile terminal, aiming at solving the problem that the mobile terminal adopts an eye pattern on the user's mobile terminal in the prior art. Identification is the defect that the eye pattern recognition fails or is slow due to insufficient or excessive exposure.
  • An image exposure method based on eye mark recognition of a mobile terminal wherein the image exposure method comprises:
  • the camera is opened to obtain a facial image of the user, and the obtained facial image preview is displayed on the display screen;
  • step E specific methods for adjusting the queried exposure parameters include: If the brightness parameter is less than 128 gray scale, the signal amplification factor and the exposure time are increased; if the brightness parameter is greater than 128 gray scale, the signal amplification factor and the exposure time are reduced.
  • the invention also provides an image exposure method based on eye mark recognition of a mobile terminal, wherein the image exposure method comprises:
  • the image data is acquired by the camera
  • the mobile terminal is based on an image recognition method for eye mark recognition, wherein the step A further includes:
  • the mobile terminal is based on an image-receiving method for eye-pattern recognition, wherein the step C further includes:
  • the mobile terminal is based on an image-receiving method for eye-pattern recognition, wherein the step C specifically includes:
  • the eyeball used for eye pattern recognition may be the left eye or/and the right eye.
  • the invention further provides an image exposure system based on eye mark recognition of a mobile terminal, wherein the image exposure system comprises:
  • a detecting and acquiring module configured to acquire image data by the camera when detecting that the mobile terminal opens the eye pattern recognition
  • a positioning module configured to locate an eyeball position by image processing, and obtain a brightness parameter of a position where the eyeball is located;
  • the adjusting and exposing module is configured to query the pre-stored exposure parameter corresponding to the brightness parameter according to the acquired brightness parameter, adjust the exposure parameter, and expose the eyeball position according to the adjusted exposure parameter.
  • the mobile terminal is based on an image recognition system for eye mark recognition, wherein the system further comprises:
  • the pre-storage module is configured to pre-acquire and store the corresponding relationship between the user's eye pattern data, the brightness parameter and the exposure parameter.
  • the mobile terminal is based on an image recognition system for eye mark recognition, wherein the system further comprises:
  • the verification and unlocking module is configured to verify the image obtained after the exposure and the pre-stored eyeprint data to unlock the mobile terminal.
  • the mobile terminal is based on an image recognition system for eye mark recognition, wherein the adjustment and exposure module comprises:
  • a query unit configured to query, according to the acquired brightness parameter, a pre-stored exposure parameter corresponding to the brightness parameter
  • the adjusting unit is configured to reduce the exposure time and the signal amplification factor according to the correspondence or increase the exposure time and the signal amplification factor;
  • An exposure module for exposing the position of the eyeball according to the adjusted exposure parameter.
  • the eyeball employed in the eyeprint recognition may be a left eye or/and a right eye.
  • the invention provides an image exposure method and an image exposure system based on eye mark recognition of a mobile terminal, wherein the image exposure method comprises: when detecting that the mobile terminal opens eye mark recognition, acquiring image data through a camera; and positioning by image processing The eyeball position is obtained, and the brightness parameter of the position of the eyeball is obtained; according to the obtained brightness parameter, the pre-stored exposure parameter corresponding to the brightness parameter is queried, the exposure parameter is adjusted, and the eyeball position is exposed according to the adjusted exposure parameter.
  • the exposure of the eyeball of the user is controlled by an area, and the exposure thereof is controlled, thereby speeding up the recognition of the eye pattern, and unlocking more safely and conveniently, thereby providing convenience for the user.
  • FIG. 1 is a flow chart of a preferred embodiment of an image exposure method based on eye mark recognition of a mobile terminal according to the present invention
  • FIG. 2 is a flow chart of a specific application embodiment of an image exposure method based on eye mark recognition of a mobile terminal according to the present invention
  • FIG. 3 is a functional block diagram of a preferred embodiment of an image exposure system based on eye mark recognition of a mobile terminal of the present invention.
  • An image exposure method based on eye pattern recognition of a mobile terminal according to the first embodiment of the present invention, as shown in FIG. 1 includes:
  • Step S100 When detecting that the mobile terminal turns on the eye pattern recognition, the image data is acquired by the camera.
  • the mobile terminal when the user activates the eye pattern recognition unlocking, the mobile terminal turns on the camera and turns on the camera to acquire an image.
  • the front camera is opened to acquire facial data of the person, and the data preview is displayed on the display screen of the mobile terminal.
  • the method further includes:
  • the user sets the unlocking mode of the mobile terminal to eye pattern recognition and unlock.
  • the eye lines can show many physiological information of the human body, such as blood vessels and veins. These seemingly irrelevant data are just an important indicator of identifying users.
  • Smart mobile terminals can capture human eye tracking information.
  • the mobile terminal collects the eye pattern data of the user, and stores the collected eye pattern data for later eye pattern recognition.
  • the user's eye pattern data can be directly obtained by the mobile terminal camera, or can be acquired by the camera and stored in the mobile terminal.
  • the user's eye pattern data is directly obtained by using the mobile terminal camera.
  • the Y value (ie, the luminance value) in the YUV space is 128 as a threshold.
  • the exposure parameter is adjusted by adjusting the exposure time, Gain (ie, signal amplification).
  • the multiple is equal to 128 so that the Y value is equal to 128.
  • a target brightness value of about 18 degrees gray (gray level 128). If the brightness of the image does not reach this brightness value, increase the Gain (signal magnification) and increase the exposure time to achieve the brightness of the image. Value, and if it is greater than this value, reduce Gain and reduce exposure time.
  • the specific signal magnification is 1, 2 or 3, and so on.
  • the difference between the existing brightness value and the target brightness value may also be used to determine whether the exposure time is increased or decreased, and the signal amplification factor or signal is not amplified. For example, when the Y value of the existing brightness, that is, the gray level is 12, the exposure time may be increased by 10 ms, and the signal amplification factor is 3 times. Specifically, the adjustment of the exposure time and the signal amplification factor is determined as needed.
  • Step S200 Position the eyeball by image processing, and obtain a brightness parameter of the position where the eyeball is located.
  • the mobile terminal when the camera is turned on, the mobile terminal previews the facial information of the person, and the position of the eyeball is located through image processing.
  • image processing There are many prior art image processing methods, and the present invention will not be described again.
  • the mobile terminal After the image processing method is adopted, after positioning the eyeball position, the mobile terminal acquires the brightness parameter of the position where the eyeball is located.
  • Step S300 Query the pre-stored exposure parameters corresponding to the brightness parameter according to the acquired brightness parameter, adjust the exposure parameter, and expose the eyeball position according to the adjusted exposure parameter.
  • the area exposure method means that the hue or gray tone of a black and white photo can be divided into ten "areas", from zero area (the darkest part that the paper can represent) to the tenth area (the color of the photo paper - white) ).
  • the fifth area is a medium gray scale that can be derived from the exposure of the meter reading.
  • the fifth area refers to an area where the reflection coefficient is 18%.
  • the correct way to get the correct exposure standard for the camera is to calculate the mean of the Y value of the current image in the YUV space.
  • the various exposure parameter settings (automatic or manual) are adjusted so that the mean falls near a target value, the correct exposure is considered to be obtained.
  • 18% ash is defined as an average value, and it is generally considered that the indoor and outdoor scenes have an average reflection coefficient of about 18% under normal circumstances, and the color mean value, as described above, can be regarded as a kind. Gray tones.
  • the exposure parameters can be adjusted by taking a gray board with a light reflectance of 18% so that the color is close to a medium-intensity gray (Y value is 128). Then, for the usual scene, you can automatically get the correct exposure.
  • the step S300 specifically includes:
  • the eye pattern recognition uses an image of a part of the blood vessel of the eye, the position of the eye can be found by an algorithm, and the exposure is adjusted for the white part of the eye. Excessive exposure will lose eye tracking information. Use a weak exposure to get clearer eye pattern information. You can increase the speed of recognition.
  • the method further includes:
  • Step S400 verifying the image obtained after the exposure and the eyeprint data stored in advance, and unlocking the mobile terminal.
  • the exposed eye pattern is compared with the pre-stored eye pattern data, and if it matches, the mobile terminal is unlocked, and if it does not match, the unlocking failure is prompted.
  • the eyeball used in the eyeprint recognition in the present invention may be the left eye or/and the right eye.
  • the exposure of the left and right eyes is different, and one eye can be exposed to one eye.
  • Light control to obtain high-quality images of one eye, use this eye for eye recognition, speed up the recognition.
  • Eye pattern recognition can also be performed using both left and right eyes. There is no specific limitation on the specific use of several eyes for eye mark recognition.
  • a specific application embodiment of an image exposure method based on eye mark recognition of a mobile terminal of the present invention includes the steps of:
  • Step S10 detecting that the mobile terminal starts to activate the eye pattern recognition and unlocking, and then performing step S20;
  • Step S20 eye pattern recognition opens the camera, starts previewing, and acquires image data, and then proceeds to step S30;
  • Step S30 the eye pattern recognition software processes the image, finds the position of the eye, and transmits the position information to the camera hardware abstraction layer, and then performs step S40;
  • Step S40 The camera hardware abstraction layer performs exposure parameter calculation on the brightness of the position, and if the brightness is strong, step S50 is performed. If the brightness is weak, step S60 is performed. Specifically, the brightness here is stronger. In contrast, it is considered that the reflection coefficient of the object is less than 18%, and the brightness is weak. When the reflection coefficient of the object is greater than 18%, the brightness of the object is considered to be strong;
  • Step S50 reducing the exposure time and Gain, and then performing step S70;
  • Step S60 increasing the exposure time and Gain, and then performing step S70;
  • Step S70 the eyeprint recognition software obtains a better image, performs eyeprint recognition verification and unlocks, and then performs step S80;
  • Step S80 turning off the camera, and then performing step S90;
  • step S90 the eye pattern recognition ends.
  • the present invention provides an image exposure method based on eye pattern recognition in a mobile terminal.
  • an eyeball portion of a person is obtained through image processing, and is adjusted according to the brightness data of the eyeball portion of the person.
  • the exposure parameters of the camera finally obtain high-quality eye-pattern images for verification and recognition, thereby improving the recognition speed of the eye-pattern recognition and providing convenience for the user.
  • the present invention also provides an image exposure system based on eye pattern recognition of a mobile terminal.
  • a functional block diagram of a preferred embodiment of the system as shown in FIG. 3, the system includes:
  • the detecting and acquiring module 510 is configured to acquire image data by the camera when detecting that the mobile terminal opens the eye pattern recognition; as described above.
  • the positioning module 520 is configured to locate an eyeball position by image processing, and acquire a brightness parameter of a position where the eyeball is located; as described above.
  • the adjusting and exposing module 530 is configured to query the pre-stored exposure parameter corresponding to the brightness parameter according to the acquired brightness parameter, adjust the exposure parameter, and expose the eyeball position according to the adjusted exposure parameter; as described above.
  • the mobile terminal is based on an image recognition system for eye mark recognition, wherein the system further comprises:
  • the pre-storage module is configured to pre-acquire and store the corresponding relationship between the user's eye pattern data, the brightness parameter and the exposure parameter; as described above.
  • the mobile terminal is based on an image recognition system for eye mark recognition, wherein the system further comprises:
  • the verification and unlocking module is configured to verify the image obtained after the exposure and the pre-stored eyeprint data to unlock the mobile terminal; as described above.
  • the mobile terminal is based on an image recognition system for eye mark recognition, wherein the adjustment and exposure module comprises:
  • the query unit is configured to query, according to the acquired brightness parameter, the pre-stored exposure parameter corresponding to the brightness parameter; as described above.
  • the adjusting unit is configured to reduce the exposure time and Gain according to the correspondence or increase the exposure time and Gain; as described above.
  • An exposure module for exposing the position of the eyeball according to the adjusted exposure parameter as described above.
  • the eyeball used in the eyeprint recognition may be a left eye or/and a right eye; as described above.
  • the present invention provides an image exposure method and exposure of a mobile terminal based on eye pattern recognition.
  • the optical system includes: when detecting that the mobile terminal opens the eye pattern recognition, acquiring image data by using a camera; positioning the eyeball position by image processing, and acquiring a brightness parameter of the position where the eye ball is located; and querying the pre-stored according to the obtained brightness parameter The exposure parameter corresponding to the brightness parameter is adjusted, and the eye position is exposed according to the adjusted exposure parameter.
  • the exposure of the eyeball of the user is controlled by an area, and the exposure thereof is controlled, thereby speeding up the recognition of the eye pattern, and unlocking more safely and conveniently, thereby providing convenience for the user.

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Abstract

一种移动终端基于眼纹识别的图像曝光方法及图像曝光系统，其中，所述图像曝光方法包括：检测到移动终端开启眼纹识别时，通过相机获取图像数据（S100）；通过图像处理定位眼球位置，并获取眼球所在位置的亮度参数（S200）；根据获取的亮度参数，查询预先存储的与所述亮度参数对应的曝光参数，调整曝光参数，并根据调整后的曝光参数对眼球位置进行曝光（S300）。该方法通过在眼纹识别过程中，对用户的眼球曝光采用区域曝光的方法，控制其曝光，从而加快眼纹识别速度，更安全方便的解锁，为用户提供了方便。

Description

移动终端基于眼纹识别的图像曝光方法及图像曝光系统 技术领域
本发明涉及移动终端技术领域，尤其涉及一种移动终端基于眼纹识别的图像曝光方法及图像曝光系统。
背景技术
随着移动通信的发展和人们生活水平的不断提高，各种移动终端如手机的使用越来越普及，手机已经成为人们生活中不可缺少的通讯交流工具。
随着智能机的普及，很多用户利用锁屏软件来保护自己的手机隐私，美化手机和减少误操作。
眼纹识别锁屏软件是一款保护用户手机隐私的锁屏软件。由于每个人的眼部纹理都是不一样的，而且一般情况都不会有很大变化，眼纹识别锁屏软件就利用了这个原理，通过分析眼纹来确定是否是该手机的主人。
眼纹识别锁屏软件使用过程：首次使用，用户必须录入自己的眼部纹理信息，就像脸部识别锁屏软件类似。同时需要输入备选的解锁方式。因为图像识别锁屏软件都一定概率解不开屏幕，设置备选的解锁方法，如密码或者九宫图案，这样可以在眼纹识别失败时，启用备用的解锁方法。
眼纹识别锁屏软件的原理：使用前置摄像头获取用户的若干眼部图像，接着对这些图片进行数据处理，获取用户的眼纹信息，并保存到手机本地。当用户进行解锁时，眼纹识别软件会打开前置摄像头(即camera)，再次获取用户的眼纹信息，把这些信息和预存的眼部信息进行对比来确定是否是该手机主人。
眼纹识别锁屏软件使用前置摄像头来获取用户的眼部图片信息。然后对这些图片数据进行处理分析。所以对前置摄像头图像质量要求比较高。
但是在同一图片中的不同区域出现曝光程度不同的问题，导致无法获得正 确的曝光配置，眼部太暗或者太亮，图像质量差，降低眼纹识别的速度，为用户解锁提供了不便。
因此，现有技术还有待于改进和发展。
发明内容
本发明要解决的技术问题在于，针对现有技术的上述缺陷，提供一种移动终端基于眼纹识别的图像曝光方法及曝光系统，旨在解决现有技术中移动终端在用户的移动终端采用眼纹识别是地，因曝光不足或过量造成眼纹识别失败或速度较慢的缺陷。
本发明解决技术问题所采用的技术方案如下：
一种移动终端基于眼纹识别的图像曝光方法，其中，所述图像曝光方法包括：
A、检测是否启动眼纹识别解锁；
B、若启动眼纹识别解锁，则打开摄像头，以获取用户的脸部图像，并将获取的脸部图像预览显示在显示屏上；
C、利用眼纹识别软件对所述脸部图像进行处理，以定位出所述脸部图像中的眼球位置；
D、根据所述眼球位置获取眼球所在位置的亮度参数；
E、根据获取的亮度参数查询预先存储的与所述亮度参数对应的曝光参数，并对查询到的曝光参数进行调整，以使利用经调整后的曝光参数曝光后的图像的亮度为128灰阶；
F、利用调整后的曝光参数对所述眼球位置进行曝光；
G、将曝光后获得的眼纹图像与预先存储的眼纹数据进行匹配；其中，若匹配成功，则解锁移动终端；若匹配不成功，则提示解锁失败。
进一步地，在步骤E中，对查询到的曝光参数进行调整的具体方法包括： 若所述亮度参数小于128灰阶，则增加信号放大倍数和曝光时间；若所述亮度参数大于128灰阶，则减少信号放大倍数和曝光时间。
本发明还提供了一种移动终端基于眼纹识别的图像曝光方法，其中，所述图像曝光方法包括：
A、检测到移动终端开启眼纹识别时，通过相机获取图像数据；
B、通过图像处理定位眼球位置，并获取眼球所在位置的亮度参数；
C、根据获取的亮度参数，查询预先存储的与所述亮度参数对应的曝光参数，调整曝光参数，并根据调整后的曝光参数对眼球位置进行曝光。
所述的移动终端基于眼纹识别的图像曝光方法，其中，所述步骤A之前还包括：
S、预先获取用户的眼纹数据、亮度参数与曝光参数的对应关系并进行存储。
所述的移动终端基于眼纹识别的图像曝光方法，其中，所述步骤C之后还包括：
D、将曝光后获得的图像与预先存储的眼纹数据进行验证，解锁移动终端。
所述的移动终端基于眼纹识别的图像曝光方法，其中，所述步骤C具体包括：
C1、根据获取的亮度参数，查询预先存储的与所述亮度参数对应的曝光参数；
C2、根据对应关系降低曝光时间和信号放大倍数或是增加曝光时间和信号放大倍数；
C3、根据调整后曝光参数对眼球位置进行曝光。
上述任一项所述的移动终端基于眼纹识别的图像曝光方法，其中，
眼纹识别时采用的眼球可为左眼或/和右眼。
本发明又提供了一种移动终端基于眼纹识别的图像曝光系统，其中，所述图像曝光系统包括：
检测与获取模块，用于检测到移动终端开启眼纹识别时，通过相机获取图像数据；
定位模块，用于通过图像处理定位眼球位置，并获取眼球所在位置的亮度参数；
调整与曝光模块，用于根据获取的亮度参数，查询预先存储的与所述亮度参数对应的曝光参数，调整曝光参数，并根据调整后的曝光参数对眼球位置进行曝光。
所述的移动终端基于眼纹识别的图像曝光系统，其中，所述系统还包括：
预先存储模块，用于预先获取用户的眼纹数据、亮度参数与曝光参数的对应关系并进行存储。
所述的移动终端基于眼纹识别的图像曝光系统，其中，所述系统还包括：
验证与解锁模块，用于将曝光后获得的图像与预先存储的眼纹数据进行验证，解锁移动终端。
所述的移动终端基于眼纹识别的图像曝光系统，其中，所述调整与曝光模块包括：
查询单元，用于根据获取的亮度参数，查询预先存储的与所述亮度参数对应的曝光参数；
调整单元，用于根据对应关系降低曝光时间和信号放大倍数或是增加曝光时间和信号放大倍数；
曝光模块，用于根据调整后曝光参数对眼球位置进行曝光。
上述任一项所述的移动终端基于眼纹识别的图像曝光系统，其中，眼纹识别时采用的眼球可为左眼或/和右眼。
本发明提供了一种移动终端基于眼纹识别的图像曝光方法及图像曝光系统，其中，所述图像曝光方法包括：检测到移动终端开启眼纹识别时，通过相机获取图像数据；通过图像处理定位眼球位置，并获取眼球所在位置的亮度参数；根据获取的亮度参数，查询预先存储的与所述亮度参数对应的曝光参数，调整曝光参数，并根据调整后的曝光参数对眼球位置进行曝光。本发明中通过对眼纹识别过程中，对用户的眼球曝光采用区域曝光的方法，控制其曝光，从而加快眼纹识别速度，更安全方便的解锁，为用户提供了方便。
附图说明
图1是本发明的一种移动终端基于眼纹识别的图像曝光方法的较佳实施例的流程图；
图2是本发明的一种移动终端基于眼纹识别的图像曝光方法的一种具体应用实施例的流程图；
图3是本发明的一种移动终端基于眼纹识别的图像曝光系统的较佳实施例的功能原理框图。
具体实施方式
为使本发明的目的、技术方案及优点更加清楚、明确，以下参照附图并举实施例对本发明进一步详细说明。应当理解，此处所描述的具体实施例仅仅用以解释本发明，并不用于限定本发明。
本发明第一实施例所述的一种移动终端基于眼纹识别的图像曝光方法，如图1所示，包括：
步骤S100、检测到移动终端开启眼纹识别时，通过相机获取图像数据。
具体实施时，当用户启动眼纹识别解锁时，移动终端打开相机，并打开摄像头获取图像。优选的，打开前置摄像头获取人的脸部数据，并将数据预览显示在移动终端显示屏上。
具体地，在所述步骤S100之前还包括：
S1、预先获取用户的眼纹数据、亮度参数与曝光参数的对应关系并进行存 储。
具体实施时，用户将移动终端的解锁方式设置为眼纹识别解锁。人类每一只眼睛里都有两个眼纹，分别位于虹膜的两边。眼纹可以显示出人体的许多生理信息，比如血管、静脉等。这些看似不相关的数据，恰恰成为了识别用户身份的重要指标。智能移动终端都可以捕捉人的眼纹信息。
当设置为眼纹识别解锁时，移动终端要采集用户的眼纹数据，并将采集到的眼纹数据进行存储，用于后来的眼纹识别。此处的获取用户的眼纹数据可通过移动终端摄像头直接获取，也可采用相机进行获取并存储到移动终端中。优选的，采用移动终端摄像头直接获取用户的眼纹数据。
具体的亮度参数与曝光参数的对应关系，由多次实验测定获得。本发明中优选的定义图像在YUV空间中Y值(即亮度值)为128为一阈值，当图像中的Y值大于或小于128时，则通过调整曝光参数包括曝光时间、Gain(即信号放大倍数)等使Y值等于128。
有个目标亮度值大概是18度灰(灰阶128)左右，如果图像的亮度没达到这个亮度值，就用增加Gain(信号放大倍数)和增长曝光时间的方法来做图像的亮度达到这个目标值，反之如果大于这个值，就减小Gain和减短曝光时间。具体的信号放大倍数为1、2或3等。例如也可采用现有亮度值与目标亮度值的差值判断曝光时间增加或缩减，同时信号放大倍数或信号不放大。例当现有亮度的Y值即灰阶为12时，可能曝光时间增加10ms，信号放大倍数为3倍，具体地，曝光时间和信号放大倍数的调整根据需要确定。
步骤S200、通过图像处理定位眼球位置，并获取眼球所在位置的亮度参数。
具体实施时，当打开摄像头时，移动终端预览的是人的脸部信息，通过图像处理定位眼球位置，具体的图像处理方法现有技术有很多，本发明不再赘述。当采用图像处理方法后，定位出眼球位置后，移动终端并获取眼球所在位置的亮度参数。
步骤S300、根据获取的亮度参数，查询预先存储的与所述亮度参数对应的曝光参数，调整曝光参数，并根据调整后的曝光参数对眼球位置进行曝光。
区域曝光法是指将黑白照片的色调或灰调可以分为十个“区域”，由零区域(相纸能够表现出的最黑的部分)至第十区域(相纸的底色——白色)。第五区域是中等的灰度，它可以根据测光表的读数曝光而得出来。第五区域是指反光系数为18％的区域。
对于摄像头来说获得正确的曝光标准的做法就是在YUV空间计算当前图像的Y值的均值。调节各种曝光参数设定(自动或手动)，使得该均值落在一个目标值附近的时候，就认为得到了正确的曝光。本发明中将18％灰定义为一个均值，一般认为室内室外的景物，在通常的情况下，其平均的反光系数大约为18％，而色彩均值，如前所述，可以认为是一种中灰的色调。这样，可以通过对反光率为18％的灰板拍摄，调整曝光参数，使其颜色接近为中等亮度的灰色(Y值为128)。然后，对于通常的景物，就能自动的得到正确的曝光了。
因此当景物的亮度参数后，将其曝光调整为接近中等亮度的灰色，获得最佳曝光效果。具体实施时，所述步骤S300具体包括方法为：
S301、根据获取的亮度参数，查询预先存储的与所述亮度参数对应的曝光参数；
S302、根据对应关系降低曝光时间和Gain或是增加曝光时间和Gain；
S303、根据调整后曝光参数对眼球位置进行曝光。
因为眼纹识别使用的是眼白部分血管的图像，可以通过算法找出眼睛的位置，针对眼白部分调节曝光。过强的曝光，会失去眼纹信息。使用弱曝光就可以获得更清晰地眼纹信息。可以调高识别的速度。
所述步骤S300之后还包括：
步骤S400、将曝光后获得的图像与预先存储的眼纹数据进行验证，解锁移动终端。具体后，将曝光后的眼纹图像与预先存储的眼纹数据进行对比验证，若匹配则解锁移动终端，若不匹配则提示解锁失败。
本发明中眼纹识别时采用的眼球可为左眼或/和右眼。具体实施时，由于用户阴阳脸的环境下，左右眼部的曝光是不一样的，可以集中对一只眼睛进行曝 光控制，获得一只眼的高质量图像，使用这一只眼做眼部识别，加快识别的速度。也可采用左右两只眼进行眼纹识别。对于具体采用几只眼睛用作眼纹识别不作具体的限制。
本发明的一种移动终端基于眼纹识别的图像曝光方法的一具体应用实施例，如图2所示，所述方法包括步骤：
步骤S10、检测移动终端开始启动眼纹识别解锁，之后执行步骤S20；
步骤S20、眼纹识别打开相机，开始预览，并获取图像数据，之后执行步骤S30；
步骤S30、眼纹识别软件对图像处理，找出眼睛的位置，并将位置信息传递给相机硬件抽象层，之后执行步骤S40；
步骤S40、相机硬件抽象层对该位置的亮度进行曝光参数计算，配置，如果亮度较强，则执行步骤S50，如果亮度较弱，则执行步骤S60，具体地，这里的亮度较强较弱是相对的，其中认为到物体的反光系数小于18％为亮度较弱，当物体的反光系数大于18％，则认为物体的亮度较强；
步骤S50、降低曝光时间和Gain，之后执行步骤S70；
步骤S60、增加曝光时间和Gain，之后执行步骤S70；
步骤S70、眼纹识别软件获得较好的图像，进行眼纹识别验证并解锁，之后执行步骤S80；
步骤S80、关闭相机，之后执行步骤S90；
步骤S90、眼纹识别结束。
由上述实施例可知，本发明提供了一种移动终端基于眼纹识别的图像曝光方法，在眼纹识别过程中，通过图像处理获取人的眼球部位，并根据人的眼球部位的亮底数据调整相机的曝光参数，最终获得高质量眼纹图像进行验证识别，从而提高了眼纹识别的识别速度，为用户提供了方便。
基于上述实施例，本发明还提供一种移动终端基于眼纹识别的图像曝光系 统的较佳实施例的功能原理框图，如图3所示，所述系统包括：
检测与获取模块510，用于检测到移动终端开启眼纹识别时，通过相机获取图像数据；具体如上所述。
定位模块520，用于通过图像处理定位眼球位置，并获取眼球所在位置的亮度参数；具体如上所述。
调整与曝光模块530，用于根据获取的亮度参数，查询预先存储的与所述亮度参数对应的曝光参数，调整曝光参数，并根据调整后的曝光参数对眼球位置进行曝光；具体如上所述。
所述的移动终端基于眼纹识别的图像曝光系统，其中，所述系统还包括：
预先存储模块，用于预先获取用户的眼纹数据、亮度参数与曝光参数的对应关系并进行存储；具体如上所述。
所述的移动终端基于眼纹识别的图像曝光系统，其中，所述系统还包括：
验证与解锁模块，用于将曝光后获得的图像与预先存储的眼纹数据进行验证，解锁移动终端；具体如上所述。
所述的移动终端基于眼纹识别的图像曝光系统，其中，所述调整与曝光模块包括：
查询单元，用于根据获取的亮度参数，查询预先存储的与所述亮度参数对应的曝光参数；具体如上所述。
调整单元，用于根据对应关系降低曝光时间和Gain或是增加曝光时间和Gain；具体如上所述。
曝光模块，用于根据调整后曝光参数对眼球位置进行曝光；具体如上所述。
上述任一项所述的移动终端基于眼纹识别的图像曝光系统，其中，眼纹识别时采用的眼球可为左眼或/和右眼；具体如上所述。
综上所述，本发明提供了一种移动终端基于眼纹识别的图像曝光方法及曝 光系统，所述方法包括：检测到移动终端开启眼纹识别时，通过相机获取图像数据；通过图像处理定位眼球位置，并获取眼球所在位置的亮度参数；根据获取的亮度参数，查询预先存储的与所述亮度参数对应的曝光参数，调整曝光参数，并根据调整后的曝光参数对眼球位置进行曝光。本发明中通过对眼纹识别过程中，对用户的眼球曝光采用区域曝光的方法，控制其曝光，从而加快眼纹识别速度，更安全方便的解锁，为用户提供了方便。
应当理解的是，本发明的应用不限于上述的举例，对本领域普通技术人员来说，可以根据上述说明加以改进或变换，所有这些改进和变换都应属于本发明所附权利要求的保护范围。

Claims (11)

  1. 一种移动终端基于眼纹识别的图像曝光方法，其中，所述图像曝光方法包括：
    A、检测是否启动眼纹识别解锁；
    B、若启动眼纹识别解锁，则打开摄像头，以获取用户的脸部图像，并将获取的脸部图像预览显示在显示屏上；
    C、利用眼纹识别软件对所述脸部图像进行处理，以定位出所述脸部图像中的眼球位置；
    D、根据所述眼球位置获取眼球所在位置的亮度参数；
    E、根据获取的亮度参数查询预先存储的与所述亮度参数对应的曝光参数，并对查询到的曝光参数进行调整，以使利用经调整后的曝光参数曝光后的图像的亮度为128灰阶；
    F、利用调整后的曝光参数对所述眼球位置进行曝光；
    G、将曝光后获得的眼纹图像与预先存储的眼纹数据进行匹配；其中，若匹配成功，则解锁移动终端；若匹配不成功，则提示解锁失败。
  2. 根据权利要求1所述的移动终端基于眼纹识别的图像曝光方法，其中，在步骤E中，对查询到的曝光参数进行调整的具体方法包括：
    若所述亮度参数小于128灰阶，则增加信号放大倍数和曝光时间；
    若所述亮度参数大于128灰阶，则减少信号放大倍数和曝光时间。
  3. 一种移动终端基于眼纹识别的图像曝光方法，其中，所述方法包括：
    A、检测到移动终端开启眼纹识别时，通过相机获取图像数据；
    B、通过图像处理定位眼球位置，并获取眼球所在位置的亮度参数；
    C、根据获取的亮度参数，查询预先存储的与所述亮度参数对应的曝光参数，调整曝光参数，并根据调整后的曝光参数对眼球位置进行曝光。
  4. 根据权利要求3所述的移动终端基于眼纹识别的图像曝光方法，其中，所述步骤A之前还包括：
    S、预先获取用户的眼纹数据、亮度参数与曝光参数的对应关系并进行存储。
  5. 根据权利要求4所述的移动终端基于眼纹识别的图像曝光方法，其中，所述步骤C之后还包括：
    D、将曝光后获得的图像与预先存储的眼纹数据进行验证，解锁移动终端。
  6. 根据权利要求5所述的移动终端基于眼纹识别的图像曝光方法，其中，所述步骤C具体包括:
    C1、根据获取的亮度参数，查询预先存储的与所述亮度参数对应的曝光参数；
    C2、根据对应关系降低曝光时间和信号放大倍数或是增加曝光时间和信号放大倍数；
    C3、根据调整后曝光参数对眼球位置进行曝光。
  7. 根据权利要求3所述的移动终端基于眼纹识别的图像曝光方法，其中，眼纹识别时采用的眼球可为左眼或/和右眼。
  8. 一种移动终端基于眼纹识别的图像曝光系统，其中，所述图像曝光系统包括：
    检测与获取模块，用于检测到移动终端开启眼纹识别时，通过相机获取图像数据；
    定位模块，用于通过图像处理定位眼球位置，并获取眼球所在位置的亮度参数；
    调整与曝光模块，用于根据获取的亮度参数，查询预先存储的与所述亮度参数对应的曝光参数，调整曝光参数，并根据调整后的曝光参数对眼球位置进行曝光。
  9. 根据权利要求8所述的移动终端基于眼纹识别的图像曝光系统，其中，所述图像曝光系统还包括：
    预先存储模块，用于预先获取用户的眼纹数据、亮度参数与曝光参数的对应关系并进行存储。
  10. 根据权利要求9所述的移动终端基于眼纹识别的图像曝光系统，其中，所述图像曝光系统还包括：
    验证与解锁模块，用于将曝光后获得的图像与预先存储的眼纹数据进行验证，解锁移动终端。
  11. 根据权利要求10所述的移动终端基于眼纹识别的图像曝光系统，其中，所述调整与曝光模块包括：
    查询单元，用于根据获取的亮度参数，查询预先存储的与所述亮度参数对应的曝光参数；
    调整单元，用于根据对应关系降低曝光时间和信号放大倍数或是增加曝光时间和信号放大倍数；
    曝光模块，用于根据调整后曝光参数对眼球位置进行曝光。
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3584740A4 (en) * 2017-04-21 2020-03-18 Shenzhen Goodix Technology Co., Ltd. BIOLOGICAL CHARACTERISTIC DATA DETECTION METHOD, BIOLOGICAL CHARACTERISTIC RECOGNITION APPARATUS AND ELECTRONIC TERMINAL
CN114694191A (zh) * 2022-03-11 2022-07-01 北京极豪科技有限公司 图像处理方法、计算机程序产品、设备以及存储介质

Families Citing this family (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104834908B (zh) * 2015-05-07 2018-09-07 惠州Tcl移动通信有限公司 一种移动终端基于眼纹识别的图像曝光方法及曝光系统
CN106066951B (zh) * 2016-05-24 2019-02-22 Oppo广东移动通信有限公司 一种电子终端的屏幕解锁方法、图像采集方法及装置
US9940519B2 (en) * 2016-06-24 2018-04-10 Fotonation Limited Image processing method and system for iris recognition
CN107621870A (zh) * 2016-07-15 2018-01-23 中兴通讯股份有限公司 一种在虚拟现实环境中处理现实事件的方法和装置
CN105956437A (zh) * 2016-07-19 2016-09-21 百度在线网络技术（北京）有限公司 用于终端屏幕解锁的方法与装置
CN108322664A (zh) * 2017-01-16 2018-07-24 上海聚虹光电科技有限公司 一种基于红外眼部灰度图像的曝光控制方法
CN106982333B (zh) * 2017-05-12 2020-03-27 深圳怡化电脑股份有限公司 一种图像传感器快速校正方法、装置及设备
RU2667790C1 (ru) 2017-09-01 2018-09-24 Самсунг Электроникс Ко., Лтд. Способ автоматической регулировки экспозиции для инфракрасной камеры и использующее этот способ вычислительное устройство пользователя
CN107622246B (zh) * 2017-09-26 2020-07-10 Oppo广东移动通信有限公司 人脸识别方法及相关产品
CN107992866B (zh) * 2017-11-15 2018-06-29 上海聚虹光电科技有限公司 基于视频流眼部反光点的活体检测方法
CN109960064A (zh) * 2017-12-14 2019-07-02 上海聚虹光电科技有限公司 具有电子可调液晶减光镜的虹膜采集摄像头及其应用方法
CN109002796B (zh) * 2018-07-16 2020-08-04 阿里巴巴集团控股有限公司 一种图像采集方法、装置和系统以及电子设备
CN109190509B (zh) * 2018-08-13 2023-04-25 创新先进技术有限公司 一种身份识别方法、装置和计算机可读存储介质
CN113132643B (zh) * 2019-12-30 2023-02-07 Oppo广东移动通信有限公司 图像处理方法及相关产品
CN113132613A (zh) * 2019-12-31 2021-07-16 中移物联网有限公司 一种摄像头补光装置、电子设备和补光方法
CN113612932B (zh) * 2021-08-09 2022-10-04 荣耀终端有限公司 曝光参数的调节方法、设备和存储介质

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103218142A (zh) * 2013-04-24 2013-07-24 深圳市中兴移动通信有限公司 终端设备的解锁方法和系统
CN104360732A (zh) * 2014-10-16 2015-02-18 南京大学 提高视线跟踪系统准确度的补偿方法与装置
US20150077329A1 (en) * 2013-09-17 2015-03-19 Electronics And Telecommunications Research Institute Eye tracking-based user interface method and apparatus
CN104834908A (zh) * 2015-05-07 2015-08-12 惠州Tcl移动通信有限公司 一种移动终端基于眼纹识别的图像曝光方法及曝光系统

Family Cites Families (30)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100289534B1 (ko) * 1998-09-16 2001-05-02 김순택 플라즈마표시패널의계조표시방법및장치
US20040252867A1 (en) * 2000-01-05 2004-12-16 Je-Hsiung Lan Biometric sensor
US7248736B2 (en) * 2004-04-19 2007-07-24 The Trustees Of Columbia University In The City Of New York Enhancing images superimposed on uneven or partially obscured background
US20070002163A1 (en) * 2005-06-29 2007-01-04 Dariusz Madej Imager settings
US8260008B2 (en) * 2005-11-11 2012-09-04 Eyelock, Inc. Methods for performing biometric recognition of a human eye and corroboration of same
US8953849B2 (en) * 2007-04-19 2015-02-10 Eyelock, Inc. Method and system for biometric recognition
WO2008131201A1 (en) * 2007-04-19 2008-10-30 Global Rainmakers, Inc. Method and system for biometric recognition
WO2010129074A1 (en) * 2009-01-14 2010-11-11 Indiana University Research & Technology Corporation System and method for identifying a person with reference to a sclera image
US8533815B1 (en) * 2009-02-03 2013-09-10 Scout Analytics, Inc. False reject mitigation using non-biometric authentication
US9087238B2 (en) * 2010-01-22 2015-07-21 Iritech Inc. Device and method for iris recognition using a plurality of iris images having different iris sizes
KR20120139100A (ko) * 2011-06-16 2012-12-27 삼성전자주식회사 얼굴 인증을 이용한 보안 장치 및 방법
US9808154B2 (en) * 2012-07-13 2017-11-07 Retina Biometrix, Llc Biometric identification via retina scanning with liveness detection
KR20140013548A (ko) * 2012-07-25 2014-02-05 삼성전자주식회사 사용자 단말 장치 및 그의 제어 방법
US9773169B1 (en) * 2012-11-06 2017-09-26 Cross Match Technologies, Inc. System for capturing a biometric image in high ambient light environments
CN103247282B (zh) * 2013-04-24 2015-03-25 天津三星电子有限公司 一种显示终端屏幕亮度的控制方法及其显示终端
CN104182721A (zh) * 2013-05-22 2014-12-03 华硕电脑股份有限公司 提升人脸识别率的图像处理系统及图像处理方法
US9582716B2 (en) * 2013-09-09 2017-02-28 Delta ID Inc. Apparatuses and methods for iris based biometric recognition
US9836647B2 (en) * 2013-10-08 2017-12-05 Princeton Identity, Inc. Iris biometric recognition module and access control assembly
US9758116B2 (en) * 2014-01-10 2017-09-12 Sony Corporation Apparatus and method for use in configuring an environment of an automobile
KR102160636B1 (ko) * 2014-02-21 2020-09-28 삼성전자주식회사 전자 장치 및 입출력 장치를 제어하는 방법
US9323435B2 (en) * 2014-04-22 2016-04-26 Robert H. Thibadeau, SR. Method and system of providing a picture password for relatively smaller displays
CN104065823A (zh) * 2014-06-30 2014-09-24 惠州Tcl移动通信有限公司 移动终端的基于虹膜识别技术的用户模式控制方法及系统
US20160019421A1 (en) * 2014-07-15 2016-01-21 Qualcomm Incorporated Multispectral eye analysis for identity authentication
US20170091550A1 (en) * 2014-07-15 2017-03-30 Qualcomm Incorporated Multispectral eye analysis for identity authentication
CN104291171A (zh) * 2014-10-30 2015-01-21 合肥指南针电子科技有限责任公司 一种智能小区的眼纹识别自动电梯控制方法及系统
US9672341B2 (en) * 2014-10-30 2017-06-06 Delta ID Inc. Systems and methods for spoof detection in iris based biometric systems
US11120110B2 (en) * 2015-01-26 2021-09-14 Microsoft Technology Licensing, Llc. Authenticating a user with a mobile apparatus
US20160283789A1 (en) * 2015-03-25 2016-09-29 Motorola Mobility Llc Power-saving illumination for iris authentication
US10068078B2 (en) * 2015-10-15 2018-09-04 Microsoft Technology Licensing, Llc Electronic devices with improved iris recognition and methods thereof
CN106940766A (zh) * 2016-01-04 2017-07-11 由田新技股份有限公司 视线轨迹认证系统及方法

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103218142A (zh) * 2013-04-24 2013-07-24 深圳市中兴移动通信有限公司 终端设备的解锁方法和系统
US20150077329A1 (en) * 2013-09-17 2015-03-19 Electronics And Telecommunications Research Institute Eye tracking-based user interface method and apparatus
CN104360732A (zh) * 2014-10-16 2015-02-18 南京大学 提高视线跟踪系统准确度的补偿方法与装置
CN104834908A (zh) * 2015-05-07 2015-08-12 惠州Tcl移动通信有限公司 一种移动终端基于眼纹识别的图像曝光方法及曝光系统

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3584740A4 (en) * 2017-04-21 2020-03-18 Shenzhen Goodix Technology Co., Ltd. BIOLOGICAL CHARACTERISTIC DATA DETECTION METHOD, BIOLOGICAL CHARACTERISTIC RECOGNITION APPARATUS AND ELECTRONIC TERMINAL
US10726114B2 (en) 2017-04-21 2020-07-28 Shenzhen GOODIX Technology Co., Ltd. Biological feature data detection method, biological feature identification apparatus and electronic terminal
CN114694191A (zh) * 2022-03-11 2022-07-01 北京极豪科技有限公司 图像处理方法、计算机程序产品、设备以及存储介质

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