WO2021197510A1 - 具有真假指纹识别功能的手机指纹识别系统和识别方法 - Google Patents

具有真假指纹识别功能的手机指纹识别系统和识别方法 Download PDF

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WO2021197510A1
WO2021197510A1 PCT/CN2021/096704 CN2021096704W WO2021197510A1 WO 2021197510 A1 WO2021197510 A1 WO 2021197510A1 CN 2021096704 W CN2021096704 W CN 2021096704W WO 2021197510 A1 WO2021197510 A1 WO 2021197510A1
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fingerprint
spectrum
module
mobile phone
pixel
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PCT/CN2021/096704
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English (en)
French (fr)
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任玉
蔡红星
王朔
张永生
唐伟利
姚治海
端木彦旭
张鹏波
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吉林求是光谱数据科技有限公司
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Publication of WO2021197510A1 publication Critical patent/WO2021197510A1/zh
Priority to US17/544,243 priority Critical patent/US20220091694A1/en

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    • 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
    • G06V40/1382—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/60—Extraction of image or video features relating to illumination properties, e.g. using a reflectance or lighting model
    • 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
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
    • G06F3/041—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means
    • G06F3/0416—Control or interface arrangements specially adapted for digitisers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
    • G06F3/041—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means
    • G06F3/042—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means by opto-electronic means
    • G06F3/0421—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means by opto-electronic means by interrupting or reflecting a light beam, e.g. optical touch-screen
    • 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
    • G06V40/1318—Sensors therefor using electro-optical elements or layers, e.g. electroluminescent sensing
    • 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
    • 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
    • G06V40/1382—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger
    • G06V40/1388—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger using image processing
    • 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
    • G06V40/1382—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger
    • G06V40/1394—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger using acquisition arrangements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04M—TELEPHONIC COMMUNICATION
    • H04M1/00—Substation equipment, e.g. for use by subscribers
    • H04M1/02—Constructional features of telephone sets
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04M—TELEPHONIC COMMUNICATION
    • H04M1/00—Substation equipment, e.g. for use by subscribers
    • H04M1/02—Constructional features of telephone sets
    • H04M1/0202—Portable telephone sets, e.g. cordless phones, mobile phones or bar type handsets
    • H04M1/026—Details of the structure or mounting of specific components

Definitions

  • the invention belongs to the field of optics, relates to fingerprint identification, and specifically relates to a mobile phone fingerprint identification system and an identification method with a true and false fingerprint identification function.
  • mobile phone fingerprint recognition mainly has three forms: capacitive fingerprint recognition, ultrasonic fingerprint recognition and fingerprint recognition under the optical screen.
  • Fingerprint recognition under the optical screen uses the CMOS sensor to obtain the reflected image of the fingerprint that is illuminated by the strong light through the small hole array. According to the light on the photosensitive module, the fingerprint image is read to complete the fingerprint recognition and unlocking [ ⁇ , fingerprint recognition under the screen Concept, technology and development [J], Patent Examination Collaboration of the Patent Office of the State Intellectual Property Office, Optoelectronics Department, Beijing Center, 2018].
  • fingerprint recognition technology is only limited to the use of image information, if you want to improve the recognition security performance, the only way is to improve the accuracy of the detector.
  • This method not only increases the complexity of the overall wiring of the fingerprint recognition system of the mobile phone, but also requires the production process. Higher, especially when the image features of the detected objects are highly similar, the accuracy of pattern recognition is low, which cannot meet actual application requirements. Therefore, it is necessary to study a brand new fingerprint identification system and identification method.
  • the first object of the present invention is to provide a mobile phone fingerprint recognition system with a true and false fingerprint recognition function.
  • the system recognizes a fingerprint, it can use spectral data to identify whether it is a real human finger or not, using image data Recognize finger fingerprint information, double recognition effectively guarantees the accuracy of fingerprint recognition and improves recognition security.
  • Mobile phone fingerprint identification system with true and false fingerprint identification function including: fingerprint acquisition module, spectrum chip, data storage module, identification module;
  • the fingerprint collection module is arranged under the screen of the mobile phone, and the screen of the mobile phone provides light sources in the three primary color bands of red, blue, and green to illuminate the fingerprint during fingerprint collection; after illumination, the light reflected by the finger becomes the incident light of the spectrum chip;
  • the spectrum chip is installed inside the mobile phone and used to split the incident light spectrum and convert the optical signal into an electrical signal. After amplification and analog-to-digital conversion, it is converted into a digital signal or coded output; at the same time, according to the intensity of the output optical signal Information and corresponding pixel location information, invert finger reflection spectrum data and fingerprint image data;
  • the data storage module is electrically connected to the spectrum chip, and is used to store the reflection spectrum data of the real finger of the human body and the image data of the fingerprint that are entered in advance;
  • the identification module is used to compare the collected reflection spectrum data with the human body's real finger reflection spectrum data pre-stored in the data storage module, and at the same time to compare the collected fingerprint with the pre-stored fingerprint image data. Successfully unlocked.
  • the spectrum chip includes a spectrum modulation module, an image and a spectrum inversion module; the spectrum modulation module is used to modulate the reflected light spectrum of the finger illuminated by the three primary color light source and convert the optical signal Become an electrical signal, which is converted into a digital signal or coded output after amplification and analog-to-digital conversion;
  • the image and spectrum inversion module is electrically connected to the spectrum modulation module, and is used to invert the image data of the finger fingerprint and the reflection spectrum data of the finger according to the optical signal intensity information output by the spectrum modulation module and the corresponding pixel position information.
  • the recognition module adopts a distance calculation method or a discrimination test method when performing recognition, and the distance calculation method includes the Euclidean distance method and the similar information clustering method.
  • the inversion method of the image and spectrum inversion module is: according to the known spectral transmittance information corresponding to the spectrum on each pixel, the intensity value of the light signal on the corresponding pixel is corrected, and the correction method It is the light signal intensity value on the pixel divided by the spectral transmittance value on the pixel; combined with the combination of all pixels, the image information can be reversed to achieve high-precision imaging function; at the same time, due to the spectral transmission on the pixel The rate is known.
  • N pixels are combined, and the incident spectral values of N pixels are inversely calculated.
  • the calculation method is as shown in formula (3).
  • S is the intensity value of the optical signal output by the photoelectric conversion substrate
  • I is the incident spectrum, which is the signal to be solved
  • T is the spectral transmittance of the filter film
  • ⁇ is the quantum efficiency of the photoelectric conversion substrate
  • ⁇ is the incident wavelength.
  • the photoelectric conversion substrate is a silicon-based image sensor, specifically a CMOS image sensor or a CCD image sensor.
  • the preparation method of the spectrum modulation module is:
  • Step S1 select a suitable photoelectric conversion substrate according to the usage scenario
  • Step S2 Select N kinds of filter film materials with different spectral transmittances, first coat the first filter film material on the photoelectric conversion substrate, and then coat an etching layer, according to the correspondence with the pixels of the photoelectric conversion substrate Retain the necessary places and etch away the unneeded places; then apply the second filter film material, and then coat an etching layer, according to the corresponding relationship with the photoelectric conversion substrate pixels, the required Keep the place and etch away the unneeded places; cycle in turn until all N kinds of filter film materials are coated on the photoelectric conversion substrate.
  • each period includes T 1 , T 2 ??T n units, and each unit covers M pixels on the photoelectric conversion substrate, and M is greater than Equal to 1, and the filter film corresponding to each pixel has the same or different spectral transmittance.
  • the second object of the present invention is to provide a mobile phone fingerprint identification method with true and false fingerprint identification function, which specifically includes the following steps:
  • Step S1 Start the fingerprint recognition function of the mobile phone, and the fingerprint recognition system of the mobile phone starts self-checking. After the self-checking is normal, the spectrum chip, the recognition module, and the data processing module are in a warm-up standby state;
  • Step S2 The fingerprint to be tested presses the fingerprint collection module on the screen of the mobile phone, and the three-primary color light source emits light waves at the same time, irradiates the fingerprint to be tested, and is illuminated by the light source, and the surface of the fingerprint to be tested forms reflected light;
  • Step S3 The spectrum chip is started. Under the condition of the three primary colors, the light signal reflected by the finger enters the spectrum chip, passes through the spectrum modulation module of the spectrum chip to perform light splitting, and converts the split light signal into an electrical signal. After amplification and analog-to-digital conversion, it is converted into a digital signal or coded output; then the image and spectrum inversion module inverts according to the optical signal intensity information output by the spectrum modulation module and the corresponding pixel position information to obtain the spectrum data of the finger and the image information of the fingerprint;
  • the inversion method of the image and spectrum inversion module is: according to the known spectral transmittance information corresponding to the spectrum on each pixel, the intensity value of the light signal on the corresponding pixel is corrected, and the correction method is the light signal on the pixel
  • the intensity value is divided by the spectral transmittance value on the pixel; combined with the combination of all pixels, the image information can be inverted to achieve high-precision imaging functions; at the same time, since the spectral transmittance on the pixel is known, it is determined by N
  • N pixels are combined, and the incident spectral values of N pixels are inversely calculated.
  • the calculation method is as shown in formula (3).
  • S is the intensity value of the optical signal output by the spectral modulation module
  • I is the incident spectrum, which is the signal to be solved
  • T is the spectral transmittance of the filter film
  • ⁇ is the quantum efficiency of the spectral modulation module
  • ⁇ is the incident wavelength
  • Step S4 After the data is collected, it directly enters the recognition module and compares it with the human body's real finger reflection spectrum data and fingerprint image data pre-stored in the data storage module. When the spectrum and the image are matched, it is judged to be a true fingerprint.
  • the fingerprint identification system recognizes fingerprints through integrated image and spectral data to determine the authenticity of fingerprints, realizes more accurate fingerprint identification, greatly improves the security of mobile phones, and effectively avoids the use of silica gel and other materials for criminals Fake fingerprints (fake fingerprints) for unlocking; and spectroscopy can also realize fast and accurate fingerprint identification.
  • the spectrum modulation module used by the spectrum chip in the fingerprint identification system provided by the present invention is a single-layer structure, simple in structure, small in size, thin in thickness (in the order of micrometers), light in weight, with high spectral resolution and space. With high resolution, high accuracy, and fast detection speed, it can be integrated into existing mobile phones to extract the spectrum and achieve high-precision imaging functions, making the extracted fingerprints clearer and more accurate.
  • the fingerprint true and false pattern recognition method that integrates image and spectral information of the present invention realizes more accurate fingerprint recognition, using three primary color light sources to excite the finger, and then obtaining reflection spectrum information and fingerprint images that can reflect the unique human skin through the spectrum chip Information, combined with the data processing system, constitutes a low-cost, ultra-convenient fingerprint identification system.
  • Fig. 1 is a schematic diagram of a mobile phone fingerprint identification system according to the present invention.
  • Figure 2 is a schematic diagram of a spectrum modulation module of the present invention.
  • Fig. 3 is a flow chart of the fingerprint identification method of the mobile phone of the present invention.
  • Figure 4 shows the reflection spectra of fingers and fingerprint films under red, blue, and green light.
  • Embodiment 1 Mobile phone fingerprint identification system with true and false fingerprint identification function
  • the present invention provides a mobile phone fingerprint identification system with a true and false fingerprint identification function, including: a fingerprint collection module 1, a spectrum chip 2, a data storage module 3, and an identification module 4;
  • the fingerprint collection module 1 is arranged below the screen of the mobile phone, and the mobile phone screen will provide red (central wavelength 630nm), blue (central wavelength 460nm), and green (central wavelength 520nm) light sources in the three primary color bands to illuminate the fingerprint to be tested during fingerprint collection; After illumination, the light reflected by the finger becomes the incident light of the spectrum chip;
  • the spectrum chip (product name: hyperspectral pixel-level coating chip, model specification: QS-A-8-400-001, the size of the spectrum chip is 4.5mm ⁇ 4.5mm, the thickness is 100 ⁇ m, the spectrum range is 200nm ⁇ 1100nm, the spectrum The resolution is 10nm, and the data acquisition time is 1ms) 2 is installed inside the mobile phone, used to modulate the incident light spectrum, and convert the optical signal into an electrical signal, which is amplified and converted into a digital signal or coded output; At the same time, invert the reflection spectrum data of the finger and the image data of the fingerprint according to the detected light signal intensity information and the corresponding pixel position information;
  • the data storage module 3 is electrically connected to the spectrum chip 2, and is used to store the reflection spectrum data of the real finger of the human body and the image data of the fingerprint that are entered in advance;
  • the identification module 4 is used to compare the collected reflection spectrum data with the human body's real finger reflection spectrum data pre-stored in the data storage module, and compare the collected fingerprint with the pre-stored fingerprint image data after confirming that they are consistent. It can be successfully unlocked after matching.
  • Embodiment 2 Mobile phone fingerprint identification system with true and false fingerprint identification function
  • the spectrum chip 2 includes a spectrum modulation module 21, an image and spectrum inversion module 22;
  • the light intensity information at each pixel position that is, the output light intensity information has a one-to-one correspondence with the pixel position information; the filter film is used to distinguish the incident light spectrum; the filter film has a single-layer structure , Which is made of N materials with known and different light transmittances through coating and etching one by one.
  • the filter film includes N periods, each period represents a channel, and each period includes T 1 , T 2 —T n units, each unit covers M pixels on the photoelectric conversion substrate, where M is greater than or equal to 1, all units constitute a periodic structure, covering all pixels on the photoelectric conversion substrate, and each The filter film corresponding to each pixel has the same or different spectral transmittance to achieve spectral splitting; in addition, the spectral transmittance of the filter film corresponding to each pixel is known, and the spectral transmittance information , Correct the light signal intensity value on the corresponding pixel, combine the combination of all pixels, and then reverse the image information.
  • the image and spectrum inversion module is electrically connected to the spectrum modulation module, and is used to invert the image data of the finger fingerprint and the reflection spectrum data of the finger according to the optical signal intensity information output by the spectrum modulation module and the corresponding pixel position information; the image
  • the inversion method of the spectral inversion module is as follows: According to the known spectral transmittance information corresponding to the spectrum on each pixel, the intensity value of the optical signal on the corresponding pixel is corrected. The correction method is to divide the intensity value of the optical signal on the pixel.
  • the image information can be reversed to achieve high-precision imaging; at the same time, since the spectral transmittance of the pixel is known, it is composed of N pixels In the periodic structure of, according to the spectral transmittance curve, N pixels are combined, and the incident spectral values of N pixels are calculated by inversion.
  • the calculation method is as shown in the following formula:
  • S is the intensity value of the optical signal output by the photoelectric conversion substrate
  • I is the incident spectrum, which is the signal to be solved
  • T is the spectral transmittance of the filter film
  • ⁇ is the quantum efficiency of the photoelectric conversion substrate
  • ⁇ is the incident wavelength.
  • distance calculation methods can be used, including Euclidean distance method, similar information clustering method, and other distance calculations.
  • the discrimination test method can also be used to distinguish whether the finger is the same, and the discrimination test method is used. During identification, the same finger is tested every 1S, and the average of 10 sets of spectrum data is taken as the reference spectrum data and stored in the data storage module. After the fingerprint is unlocked, the collected fingerprint spectrum data is directly compared with the reference spectrum data. If the maximum discrimination degree is less than 2.38 in multiple measurements, it can be considered as the same finger.
  • Embodiment 3 The preparation method of the spectrum modulation module in the spectrum chip of the present invention is:
  • Step S1 select a suitable photoelectric conversion substrate according to the usage scenario
  • Step S2 Select N kinds of filter film materials with different spectral transmittances, first coat the first filter film material on the photoelectric conversion substrate, and then coat an etching layer, according to the correspondence with the pixels of the photoelectric conversion substrate Retain the necessary places and etch away the unneeded places; then apply the second filter film material, and then coat an etching layer, according to the corresponding relationship with the photoelectric conversion substrate pixels, the required Keep the place and etch away the unneeded places; cycle in turn until all N kinds of filter film materials are coated on the photoelectric conversion substrate.
  • each period includes T 1 , T 2 ??T n units, and each unit covers M pixels on the photoelectric conversion substrate, and M is greater than Equal to 1, and the filter film corresponding to each pixel has the same or different spectral transmittance.
  • etching in step S2 a laser direct writing etching method, a mask photolithography etching method, an ion beam etching method, an electron beam etching method, etc. are used; when a mask photolithography etching method is used, A layer of photoresist is coated on each filter film material; then the etching is completed by standard photolithography processes such as exposure, development, drying, etching, and post-drying; when the laser direct writing etching method is used, In the ion beam etching method and the electron beam etching method, the preparation process is similar to the mask photolithography etching method, and the existing method is used for etching.
  • the filter film material used in the present invention is a polyimide material.
  • Embodiment 4 Mobile phone fingerprint identification method with true and false fingerprint identification function
  • a mobile phone fingerprint identification method with a true and false fingerprint identification function provided by the present invention specifically includes the following steps:
  • Step S1 Start the fingerprint recognition function of the mobile phone, and the fingerprint recognition system of the mobile phone starts self-checking. After the self-checking is normal, the spectrum chip, the recognition module, and the data processing module are in a warm-up standby state;
  • Step S2 The fingerprint to be tested presses the fingerprint collection module on the screen of the mobile phone, and the three-primary color light source emits light waves at the same time, irradiates the fingerprint to be tested, and is illuminated by the light source, and the surface of the fingerprint to be tested forms reflected light;
  • Step S3 The spectrum chip is activated. Under the condition of the three primary colors, the light signal reflected by the finger enters the spectrum chip, and the light is split through the filter film of the spectrum modulation module, and the light signal intensity information and corresponding pixel position information after the light are split It is output by the photoelectric conversion substrate, and then the image and spectrum inversion module inverts according to the optical signal intensity information output by the spectrum modulation module and the corresponding pixel position information to obtain the spectral data of the finger and the image information of the fingerprint;
  • the inversion method of the image and spectrum inversion module is: according to the known spectral transmittance information corresponding to the spectrum on each pixel, the intensity value of the light signal on the corresponding pixel is corrected, and the correction method is the light signal on the pixel
  • the intensity value is divided by the spectral transmittance value on the pixel; combined with the combination of all pixels, the image information can be inverted to achieve high-precision imaging functions; at the same time, since the spectral transmittance on the pixel is known, it is determined by N
  • N pixels are combined, and the incident spectral values of N pixels are calculated by inversion.
  • the calculation method is as shown in the following formula:
  • S is the intensity value of the optical signal output by the photoelectric conversion substrate
  • I is the incident spectrum, which is the signal to be solved
  • T is the spectral transmittance of the filter film
  • ⁇ is the quantum efficiency of the photoelectric conversion substrate
  • ⁇ is the incident wavelength
  • Step S4 After the data is processed, it directly enters the recognition module and compares it with the human body's real finger reflection spectrum data and fingerprint image data pre-stored in the data storage module. When the spectrum and the image are matched, it is judged to be a true fingerprint.
  • the present invention uses the chip provided in embodiment 1 to measure the reflectance spectrum of the real finger fingerprint of the human body, and also measures the reflectance spectrum of the fingerprint film engraved with the fingerprint of the finger.
  • the specific spectrum is shown in Figure 4, where (a) finger The reflection spectrum and (b) are the reflection spectrum of the fingerprint film. It can be seen from Figure 4 that even if the fingerprint is the same, the reflection spectrum of the finger is completely different because the real human body is different from the fingerprint film; therefore, the reflection spectrum information can be accurate Identify whether it is the fingerprint of a real human finger and prevent others from using fake fingerprints to unlock the phone.

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Abstract

具有真假指纹识别功能的手机指纹识别系统和识别方法，该系统包括指纹采集模块、光谱芯片、数据存储模块、识别模块；指纹采集模块设置在手机屏幕下方，手机屏幕会提供红、蓝、绿三基色波段的光源对指纹进行照明；光谱芯片用于将入射光光谱进行调制，并将光信号转换成为电信号，经过放大及模数转换后转为数字信号或者编码输出；根据输出的光信号强度信息和对应像素位置信息，反演手指的反射光谱数据以及指纹的图像数据；数据存储模块存储有提前录入的真实手指的光谱数据以及图像数据；识别模块，将采集到的数据与预存的数据进行对比。该系统综合图像和光谱数据对指纹进行识别，实现手机指纹解锁过程中的真假指纹识别，防止其他人用假指纹解锁手机。

Description

具有真假指纹识别功能的手机指纹识别系统和识别方法 技术领域
本发明属于光学领域，涉及指纹识别，具体涉及一种具有真假指纹识别功能的手机指纹识别系统和识别方法。
背景技术
随着手机逐渐成为个人信息集合体之后，指纹识别这种安全性极高的解锁方式开始进入手机领域。目前，手机指纹识别主要有三种形式：电容式指纹识别、超声波指纹识别和光学屏下指纹识别。光学屏下指纹识别是利用CMOS传感器获取强光穿过小孔阵列照射指纹的反射图像，根据感光模块上的光线，读取指纹图像，完成指纹识别解锁[李鹏飞淡美俊,屏下指纹识别的概念、技术与发展[J]，国家知识产权局专利局专利审查协作北京中心光电部，2018]。由于指纹识别技术仅局限于对图像信息的利用，若想提高识别安全性能，唯一的办法是提高探测器精度，此种方式不仅增加了手机指纹识别系统整体布线的复杂程度，而且对生产工艺要求较高，尤其当检测对象的图像特征高度相似时，模式识别的精度较低，无法满足实际应用需求。因此，有必要研究一种全新的指纹识别系统和识别方法。
发明内容
鉴于上述问题，本发明的第一个目的在于提供一种具有真假指纹识别功能的手机指纹识别系统，该系统在对指纹进行识别时，可利用光谱数据识别是否为真实人体手指，利用图像数据识别手指指纹信息，双重识别有效保证指纹识别的准确性，提高识别安全性。
为实现上述目的，本发明具体是采用如下技术方案实现的：
具有真假指纹识别功能的手机指纹识别系统，包括：指纹采集模块、光谱芯片、数据存储模块、识别模块；
所述指纹采集模块设置在手机屏幕下方，指纹采集时手机屏幕会提供红、蓝、绿三基色波段的光源对指纹进行照明；照明后，经过手指反射的光成为光谱芯片的入射光；
所述光谱芯片安装在手机内部，用于将入射光光谱进行分光，并将光信号转换成为电信号，经过放大及模数转换后转为数字信号或者编码输出；同时，根据输出的光信号强度信息和对应像素位置信息，反演手指的反射光谱数据以及指纹 的图像数据；
所述数据存储模块与光谱芯片电连接，用于存储提前录入的人体真实手指的反射光谱数据以及指纹的图像数据；
所述识别模块，用于将采集到的反射光谱数据与数据存储模块预存的人体真实手指反射光谱数据进行对比，同时将采集到的指纹与预存的指纹图像数据进行对比，两者均匹配后方可成功解锁。
作为本发明的优选，所述光谱芯片包括光谱调制模块、图像和光谱反演模块；所述光谱调制模块，用于将经过三基色光源照射的手指的反射光光谱进行调制，并将光信号转换成为电信号，经过放大及模数转换后转为数字信号或者编码输出；
所述图像和光谱反演模块与光谱调制模块电连接，用于根据光谱调制模块输出的光信号强度信息和对应像素位置信息，反演出手指指纹的图像数据以及手指的反射光谱数据。
作为本发明的优选，所述识别模块进行识别时采用距离计算法或区分度测试法，所述距离计算法包括欧氏距离法、相似信息聚类法。
作为本发明的进一步优选，所述光谱调制模块，包括光电转换基底、设置在光电转换基底上面的滤光薄膜；其中，所述光电转换基底，用于将光信号转化为电信号并以数字信号或者编码输出；所述滤光薄膜，用于将入射光光谱进行区分；所述滤光薄膜为单层结构，其是由已知且透光率不同的N种材料通过逐一涂覆、刻蚀后拼接而成，滤光薄膜包括N个周期，每个周期均代表一个通道，每个周期包括T 1、T 2......T n个单元，每个单元覆盖光电转换基底上的M个像素，其中M大于等于1，所有单元构成周期性结构，覆盖光电转换基底上的所有像素，与每个像素对应的滤光薄膜具有相同或者不同的光谱透过率，实现光谱分光；另外，与每个像素对应的滤光薄膜的光谱透过率均为已知的，通过该光谱透过率信息，修正对应像素上的光信号强度值，结合所有像素的组合，进而反演出图像信息。
作为本发明的进一步优选，所述图像和光谱反演模块的反演方式为：根据每个像素上的光谱对应已知的光谱透过率信息，修正对应像素上的光信号强度值，修正方法为该像素上的光信号强度值除以该像素上的光谱透过率值；结合所有像素的组合，即可反演出图像信息，实现高精度的成像功能；同时由于该像素上的 光谱透过率已知，在由N个像素组成的周期性结构中，根据光谱透过率曲线，N个像素组合，反演计算出N个像素的入射光谱值，计算方法如公式(3)所示，
S i＝∫I(λ)T i(λ)η(λ)dλ，       (3)
其中，S为光电转换基底输出的光信号强度值，I为入射光谱，是待求解信号，T为滤光薄膜的光谱透过率，η为光电转换基底的量子效率，λ为入射波长。
作为本发明的更进一步优选，所述光电转换基底为硅基图像传感器，具体为CMOS图像传感器或CCD图像传感器。
作为本发明的更进一步优选，所述光谱调制模块的制备方法为：
步骤S1、根据使用场景情况，选择合适的光电转换基底；
步骤S2、选择N种光谱透过率不同的滤光薄膜材料，先在光电转换基底上涂覆第一种滤光薄膜材料，再涂覆一层刻蚀层，根据与光电转换基底像素的对应关系，将需要的地方保留，将不需要的地方刻蚀掉；之后涂覆第二种滤光薄膜材料，再涂覆一层刻蚀层，根据与光电转换基底像素的对应关系，将需要的地方保留，将不需要的地方刻蚀掉；依次循环，直至将N种滤光薄膜材料全部涂覆到光电转换基底上，上述N种滤光薄膜材料经过逐一的涂覆和刻蚀后，最后形成一层完整的具有N个周期性的滤光薄膜，每个周期包括T 1、T 2......T n个单元，每个单元覆盖光电转换基底上的M个像素，M大于等于1，与每个像素对应的滤光薄膜具有相同或者不同的光谱透过率。
本发明的第二个目的在于提供一种具有真假指纹识别功能的手机指纹识别方法，具体包括以下步骤：
步骤S1、启动手机指纹识别功能，手机指纹识别系统开始自检，自检正常后，光谱芯片、识别模块、数据处理模块处于预热待机状态；
步骤S2、待测指纹按压手机屏幕上的指纹采集模块，三基色光源同时发出光波，照射到待测指纹上，受光源照射，待测指纹表面形成反射光；
步骤S3、光谱芯片启动，在三基色光光照情况下，由手指反射回来的光信号进入光谱芯片中，经过光谱芯片的光谱调制模块进行分光，并将分光后的光信号转换成为电信号，经过放大及模数转换后转为数字信号或者编码输出；之后图像和光谱反演模块根据光谱调制模块输出的光信号强度信息和对应像素位置信 息反演，获取手指的光谱数据及指纹的图像信息；
所述图像和光谱反演模块的反演方式为：根据每个像素上的光谱对应已知的光谱透过率信息，修正对应像素上的光信号强度值，修正方法为该像素上的光信号强度值除以该像素上的光谱透过率值；结合所有像素的组合，即可反演出图像信息，实现高精度的成像功能；同时由于该像素上的光谱透过率已知，在由N个像素组成的周期性结构中，根据光谱透过率曲线，N个像素组合，反演计算出N个像素的入射光谱值，计算方法如公式(3)所示，
S i＝∫I(λ)T i(λ)η(λ)dλ，     (3)
其中，S为光谱调制模块输出的光信号强度值，I为入射光谱，是待求解信号，T为滤光薄膜的光谱透过率，η为光谱调制模块的量子效率，λ为入射波长；
步骤S4、数据被采集后，直接进入识别模块，与数据存储模块预存的人体真实手指反射光谱数据以及指纹图像数据进行对比，当光谱和图像均匹配后判断为真指纹。
本发明的优点及积极效果是：
1、本发明提供的指纹识别系统综合图像和光谱数据对指纹进行识别，来判断指纹的真假，实现了指纹更精准的识别，大大提高了手机的安全性，有效避免不法分子用硅胶等材料仿造指纹(假指纹)进行解锁；而且光谱法还可实现指纹的快速、准确识别。
2、本发明提供的指纹识别系统中光谱芯片采用的光谱调制模块是单层结构，结构简单、体积小、厚度薄(为微米量级)、重量轻、具有较高光谱分辨率的同时具有空间分辨率、精准度高、检测速度快，可集成在现有手机内，即可实现对光谱的提取，还可实现高精度的成像功能，使提取的指纹更加清晰，准确率更高。
3、本发明综合图像和光谱信息的指纹真假模式识别方法，实现了指纹更精准的识别，利用三基色光源激发手指，再通过光谱芯片获得能够反应出人体皮肤特有的反射光谱信息和指纹图像信息，结合数据处理系统构成低成本、超便捷式的指纹识别系统。
附图说明
通过参考以下结合附图的说明，并且随着对本发明的更全面理解，本发明的 其它目的及结果将更加明白及易于理解。在附图中：
图1为根据本发明手机指纹识别系统的原理图。
图2为本发明光谱调制模块的示意图；
图3为本发明手机指纹识别方法的流程图。
图4为红光、蓝光、绿光照射下手指和指纹膜的反射光谱图。
具体实施方式
在下面的描述中，出于说明的目的，为了提供对一个或多个实施例的全面理解，阐述了许多具体细节。然而，很明显，也可以在没有这些具体细节的情况下实现这些实施例。在其它例子中，为了便于描述一个或多个实施例，公知的结构和设备以方框图的形式示出。
实施例1 具有真假指纹识别功能的手机指纹识别系统
参阅图1，本发明提供的一种具有真假指纹识别功能的手机指纹识别系统，包括：指纹采集模块1、光谱芯片2、数据存储模块3、识别模块4；
所述指纹采集模块1设置在手机屏幕下方，指纹采集时手机屏幕会提供红(中心波长630nm)、蓝(中心波长460nm)、绿(中心波长520nm)三基色波段的光源对待测指纹进行照明；照明后，经过手指反射的光成为光谱芯片的入射光；
所述光谱芯片(产品名称：高光谱像素级镀膜芯片，型号规格：QS-A-8-400-001，光谱芯片尺寸为4.5mm×4.5mm，厚度为100μm，光谱范围为200nm～1100nm，光谱分辨率为10nm，数据采集时间为1ms)2安装在手机内部，用于将入射光光谱进行调制，并将光信号转换成为电信号，经过放大及模数转换后转为数字信号或者编码输出；同时，根据探测到的光信号强度信息和对应像素位置信息反演手指的反射光谱数据以及指纹的图像数据；
所述数据存储模块3与光谱芯片2电连接，用于存储提前录入的人体真实手指的反射光谱数据以及指纹的图像数据；
所述识别模块4，用于将采集到的反射光谱数据与数据存储模块预存的人体真实手指反射光谱数据进行对比，确定一致后将采集到的指纹与预存的指纹图像数据进行对比，两者均匹配后方可成功解锁。
实施例2 具有真假指纹识别功能的手机指纹识别系统
参阅图1、图2，与实施例1的区别在于光谱芯片，所述光谱芯片2包括光谱调制模块21、图像和光谱反演模块22；所述光谱调制模块包括光电转换基底、设置在光电转换基底上面的滤光薄膜；其中，所述光电转换基底为硅基图像传感器，具体为CMOS图像传感器或CCD图像传感器，用于将光信号转化为电信号并以数字信号或者编码输出，输出的为每个像素位置上的光强度信息，即输出的光强度信息与像素位置信息有一一对应关系；所述滤光薄膜，用于将入射光光谱进行区分；所述滤光薄膜为单层结构，其是由已知且透光率不同的N种材料通过逐一涂覆、刻蚀后拼接而成，滤光薄膜包括N个周期，每个周期均代表一个通道，每个周期包括T 1、T 2......T n个单元，每个单元覆盖光电转换基底上的M个像素，其中M大于等于1，所有单元构成周期性结构，覆盖光电转换基底上的所有像素，与每个像素对应的滤光薄膜具有相同或者不同的光谱透过率，实现光谱分光；另外，与每个像素对应的滤光薄膜的光谱透过率均为已知的，通过该光谱透过率信息，修正对应像素上的光信号强度值，结合所有像素的组合，进而反演出图像信息。
所述图像和光谱反演模块与光谱调制模块电连接，用于根据光谱调制模块输出的光信号强度信息和对应像素位置信息，反演出手指指纹的图像数据以及手指的反射光谱数据；所述图像和光谱反演模块的反演方式为：根据每个像素上的光谱对应已知的光谱透过率信息，修正对应像素上的光信号强度值，修正方法为该像素上的光信号强度值除以该像素上的光谱透过率值；结合所有像素的组合，即可反演出图像信息，实现高精度的成像功能；同时由于该像素上的光谱透过率已知，在由N个像素组成的周期性结构中，根据光谱透过率曲线，N个像素组合，反演计算出N个像素的入射光谱值，计算方法如下述公式所示，
S i＝∫I(λ)T i(λ)η(λ)dλ，
其中，S为光电转换基底输出的光信号强度值，I为入射光谱，是待求解信号，T为滤光薄膜的光谱透过率，η为光电转换基底的量子效率，λ为入射波长。
所述识别模块进行识别时，可以采用距离计算法，包括欧氏距离法、相似信息聚类法以及其他距离计算，还可以采用区分度测试方法来区分是否为同一手指，采用区分度测试方法进行识别时，同一手指每隔1S测试一次，取10组光谱 数据的平均作为基准光谱数据，存储在数据存储模块内，之后指纹解锁时，直接将采集到的指纹光谱数据与基准光谱数据进行对比，如多次测量时其区分度最大值小于2.38，可以认为是同一手指。
实施例3 本发明光谱芯片中光谱调制模块的制备方法为：
步骤S1、根据使用场景情况，选择合适的光电转换基底；
步骤S2、选择N种光谱透过率不同的滤光薄膜材料，先在光电转换基底上涂覆第一种滤光薄膜材料，再涂覆一层刻蚀层，根据与光电转换基底像素的对应关系，将需要的地方保留，将不需要的地方刻蚀掉；之后涂覆第二种滤光薄膜材料，再涂覆一层刻蚀层，根据与光电转换基底像素的对应关系，将需要的地方保留，将不需要的地方刻蚀掉；依次循环，直至将N种滤光薄膜材料全部涂覆到光电转换基底上，上述N种滤光薄膜材料经过逐一的涂覆和刻蚀后，最后形成一层完整的具有N个周期性的滤光薄膜，每个周期包括T 1、T 2......T n个单元，每个单元覆盖光电转换基底上的M个像素，M大于等于1，与每个像素对应的滤光薄膜具有相同或者不同的光谱透过率。
进一步，所述步骤S2进行刻蚀时，采用激光直写刻蚀方法、掩膜光刻刻蚀方法、离子束刻蚀方法、电子束刻蚀方法等；当采用掩膜光刻刻蚀时，在每种滤光薄膜材料上均涂覆一层光刻胶；之后经过曝光、显影、烘干、刻蚀、后烘干等标准光刻工艺完成刻蚀；当采用激光直写刻蚀方法、离子束刻蚀方法、电子束刻蚀方法时，制备过程与掩膜光刻刻蚀方法类似，均是采用现有方法进行刻蚀。
另外，本发明所用的滤光薄膜材料为聚酰亚胺类材料。
实施例4 具有真假指纹识别功能的手机指纹识别方法
参阅图3，本发明提供的一种具有真假指纹识别功能的手机指纹识别方法，具体包括以下步骤：
步骤S1、启动手机指纹识别功能，手机指纹识别系统开始自检，自检正常后，光谱芯片、识别模块、数据处理模块处于预热待机状态；
步骤S2、待测指纹按压手机屏幕上的指纹采集模块，三基色光源同时发出光波，照射到待测指纹上，受光源照射，待测指纹表面形成反射光；
步骤S3、光谱芯片启动，在三基色光光照情况下，由手指反射回来的光信号进入光谱芯片中，经过光谱调制模块的滤光薄膜进行分光，分光后的光信号强 度信息和对应像素位置信息由光电转换基底输出，之后图像和光谱反演模块根据光谱调制模块输出的光信号强度信息和对应像素位置信息反演，获取手指的光谱数据及指纹的图像信息；
所述图像和光谱反演模块的反演方式为：根据每个像素上的光谱对应已知的光谱透过率信息，修正对应像素上的光信号强度值，修正方法为该像素上的光信号强度值除以该像素上的光谱透过率值；结合所有像素的组合，即可反演出图像信息，实现高精度的成像功能；同时由于该像素上的光谱透过率已知，在由N个像素组成的周期性结构中，根据光谱透过率曲线，N个像素组合，反演计算出N个像素的入射光谱值，计算方法如下述公式所示，
S i＝∫I(λ)T i(λ)η(λ)dλ，
其中，S为光电转换基底输出的光信号强度值，I为入射光谱，是待求解信号，T为滤光薄膜的光谱透过率，η为光电转换基底的量子效率，λ为入射波长；
步骤S4、数据被处理后，直接进入识别模块，与数据存储模块预存的人体真实手指反射光谱数据以及指纹图像数据进行对比，当光谱和图像均匹配后判断为真指纹。
本发明采用实施例1提供的芯片对人体的真实手指指纹的反射光谱进行测量，同时还对刻有该手指指纹的指纹膜的反射光谱进行测量，具体光谱见图4，其中，(a)手指反射光谱、(b)为指纹膜反射光谱，从图4可以看出，即便指纹相同，但是由于真实人体与指纹膜不同，所以手指的反射光谱完全不同；因此，通过反射光谱信息可以做到准确识别是否为真实人体手指的指纹，防止其他人用假指纹解锁手机。
以上，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应以权利要求的保护范围为准。

Claims (7)

  1. 具有真假指纹识别功能的手机指纹识别系统，其特征在于，包括：指纹采集模块、光谱芯片、数据存储模块、识别模块；
    所述指纹采集模块设置在手机屏幕下方，指纹采集时手机屏幕会提供红、蓝、绿三基色波段的光源对指纹进行照明；照明后，经过手指反射的光成为光谱芯片的入射光；
    所述光谱芯片安装在手机内部，用于将入射光光谱进行调制，并将光信号转换成为电信号，经过放大及模数转换后转为数字信号或者编码输出；同时，根据输出的光信号强度信息和对应像素位置信息，反演手指的反射光谱数据以及指纹的图像数据；
    所述数据存储模块与光谱芯片电连接，用于存储提前录入的人体真实手指的反射光谱数据以及指纹的图像数据；
    所述识别模块，用于将采集到的反射光谱数据与数据存储模块预存的人体真实手指反射光谱数据进行对比，同时将采集到的指纹与预存的指纹图像数据进行对比，两者均匹配后方可成功解锁。
  2. 根据权利要求1所述的具有真假指纹识别功能的手机指纹识别系统，其特征在于，所述光谱芯片包括光谱调制模块、图像和光谱反演模块；所述光谱调制模块，用于将经过三基色光源照射的手指的反射光光谱进行调制，并将光信号转换成为电信号，经过放大及模数转换后转为数字信号或者编码输出；
    所述图像和光谱反演模块与光谱调制模块电连接，用于根据光谱调制模块输出的光信号强度信息和对应像素位置信息，反演出手指指纹的图像数据以及手指的反射光谱数据。
  3. 根据权利要求1所述的具有真假指纹识别功能的手机指纹识别系统，其特征在于，所述识别模块进行识别时采用采用距离计算法或区分度测试法，所述距离计算法包括欧氏距离法、相似信息聚类法。
  4. 根据权利要求2所述的具有真假指纹识别功能的手机指纹识别系统，其特征在于，所述光谱调制模块，包括光电转换基底、设置在光电转换基底上面的滤光薄膜；其中，所述光电转换基底，用于将光信号转化为电信号并以数字信号或者编码输出；所述滤光薄膜，用于将入射光光谱进行区分；所述滤光薄膜为单层结构，其是由已知且透光率不同的N种材料通过逐一涂覆、刻蚀后拼接而成， 滤光薄膜包括N个周期，每个周期均代表一个通道，每个周期包括T 1、T 2......T n个单元，每个单元覆盖光电转换基底上的M个像素，其中M大于等于1，所有单元构成周期性结构，覆盖光电转换基底上的所有像素，与每个像素对应的滤光薄膜具有相同或者不同的光谱透过率，实现光谱分光；另外，与每个像素对应的滤光薄膜的光谱透过率均为已知的，通过该光谱透过率信息，修正对应像素上的光信号强度值，结合所有像素的组合，进而反演出图像信息。
  5. 根据权利要求2所述的具有真假指纹识别功能的手机指纹识别系统，其特征在于，所述图像和光谱反演模块的反演方式为：根据每个像素上的光谱对应已知的光谱透过率信息，修正对应像素上的光信号强度值，修正方法为该像素上的光信号强度值除以该像素上的光谱透过率值；结合所有像素的组合，即可反演出图像信息，实现高精度的成像功能；同时由于该像素上的光谱透过率已知，在由N个像素组成的周期性结构中，根据光谱透过率曲线，N个像素组合，反演计算出N个像素的入射光谱值，计算方法如公式(3)所示，
    S i＝∫I(λ)T i(λ)η(λ)dλ，  (3)
    其中，S为光电转换基底输出的光信号强度值，I为入射光谱，是待求解信号，T为滤光薄膜的光谱透过率，η为光电转换基底的量子效率，λ为入射波长。
  6. 根据权利要求2所述的具有真假指纹识别功能的手机指纹识别系统，其特征在于，所述光谱调制模块的制备方法为：
    步骤S1、根据使用场景情况，选择合适的光电转换基底；
    步骤S2、选择N种光谱透过率不同的滤光薄膜材料，先在光电转换基底上涂覆第一种滤光薄膜材料，再涂覆一层刻蚀层，根据与光电转换基底像素的对应关系，将需要的地方保留，将不需要的地方刻蚀掉；之后涂覆第二种滤光薄膜材料，再涂覆一层刻蚀层，根据与光电转换基底像素的对应关系，将需要的地方保留，将不需要的地方刻蚀掉；依次循环，直至将N种滤光薄膜材料全部涂覆到光电转换基底上，上述N种滤光薄膜材料经过逐一的涂覆和刻蚀后，最后形成一层完整的具有N个周期性的滤光薄膜，每个周期包括T 1、T 2......T n个单元，每个单元覆盖光电转换基底上的M个像素，M大于等于1，与每个像素对应的滤光薄膜具有相同或者不同的光谱透过率。
  7. 权利要求1所述的具有真假指纹识别功能的手机指纹识别方法，其特征在于，包括以下步骤：
    步骤S1、启动手机指纹识别功能，手机指纹识别系统开始自检，自检正常后，光谱芯片、识别模块、数据处理模块处于预热待机状态；
    步骤S2、待测指纹按压手机屏幕上的指纹采集模块，三基色光源同时发出光波，照射到待测指纹上，受光源照射，待测指纹表面形成反射光；
    步骤S3、光谱芯片启动，在三基色光光照情况下，由手指反射回来的光信号进入光谱芯片中，经过光谱芯片的光谱调制模块进行分光，并将分光后的光信号转换成为电信号，经过放大及模数转换后转为数字信号或者编码输出；之后图像和光谱反演模块根据光谱调制模块输出的光信号强度信息和对应像素位置信息反演，获取手指的光谱数据及指纹的图像信息；
    所述图像和光谱反演模块的反演方式为：根据每个像素上的光谱对应已知的光谱透过率信息，修正对应像素上的光信号强度值，修正方法为该像素上的光信号强度值除以该像素上的光谱透过率值；结合所有像素的组合，即可反演出图像信息，实现高精度的成像功能；同时由于该像素上的光谱透过率已知，在由N个像素组成的周期性结构中，根据光谱透过率曲线，N个像素组合，反演计算出N个像素的入射光谱值，计算方法如公式(3)所示，
    S i＝∫I(λ)T i(λ)η(λ)dλ，  (3)
    其中，S为光谱调制模块输出的光信号强度值，I为入射光谱，是待求解信号，T为滤光薄膜的光谱透过率，η为光谱调制模块的量子效率，λ为入射波长；
    步骤S4、数据被采集后，直接进入识别模块，与数据存储模块预存的人体真实手指反射光谱数据以及指纹图像数据进行对比，当光谱和图像均匹配后判断为真指纹。
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