WO2017067271A1

WO2017067271A1 - Fingerprint recognition method, fingerprint recognition apparatus, and mobile terminal

Info

Publication number: WO2017067271A1
Application number: PCT/CN2016/092698
Authority: WO
Inventors: 张强; 王立中; 周海涛; 蒋奎; 贺威
Original assignee: 广东欧珀移动通信有限公司
Priority date: 2015-10-19
Filing date: 2016-08-01
Publication date: 2017-04-27
Also published as: CN105243370A

Abstract

Disclosed are a fingerprint recognition method, a fingerprint recognition apparatus, and a mobile terminal. The method comprises: using a preset calibration value to obtain a first fingerprint image by means of a fingerprint sensor; extracting feature information of said first fingerprint image; comparing the feature information of said first fingerprint image with fingerprint features in an inventory; if the comparison is successful, then determining the recognition to be successful. In the present invention, it is possible to save fingerprint recognition time, improving user experience.

Description

Fingerprint identification method, fingerprint identification device and mobile terminal

This application claims priority to Chinese Patent Application No. 201510681119.4, entitled "A Fingerprint Identification Method, Fingerprint Identification Device, and Mobile Terminal", filed on October 19, 2015, the entire contents of which are hereby incorporated by reference. Combined in this application.

Technical field

The invention relates to a fingerprint identification technology, in particular to a fingerprint identification method, a fingerprint identification device and a mobile terminal.

Background technique

Human body fingerprints are unique features and their complexity can provide a sufficient number of features for identification.

Fingerprint recognition technology has been widely used by its advantages in cost, popularity and security. Fingerprint recognition technology is not only used in access control, attendance systems, but also more applications of fingerprint recognition technology in the market: such as laptops, mobile phones, automobiles, and bank payments. At present, mobile phone smart terminal devices are increasingly demanding security and confidentiality, and fingerprint recognition technology is also applied in the fields of unlocking mobile phones, protecting private information, and protecting transaction security.

At present, the fingerprint sensor calibrates the fingerprint sensor before acquiring the fingerprint, and uses the calibration parameters obtained by multiple calibrations to acquire the image, so that the obtained image quality is clear, but the fingerprint sensor needs to be calibrated multiple times before each image is acquired. The correct calibration parameters are available, so the fingerprinting process wastes time.

technical problem

The invention provides a fingerprint identification method, a fingerprint identification device and a mobile terminal, so as to achieve the purpose of improving the speed of fingerprint recognition.

Technical solution

In a first aspect, an embodiment of the present invention provides a fingerprint identification method, including:

Acquiring a first fingerprint image by using a preset calibration value by the fingerprint sensor;

Extracting feature information of the first fingerprint image;

Comparing the feature information of the first fingerprint image with the fingerprint feature in the inventory;

If the comparison is successful, it is determined that the recognition is successful.

In a second aspect, the embodiment of the present invention further provides a fingerprint identification device, which is disposed in the fingerprint sensor, and includes:

a first image obtaining module, configured to acquire a first fingerprint image by using a preset calibration value;

a first feature extraction module, configured to extract feature information of the first fingerprint image;

a first feature comparison module, configured to compare feature information of the first fingerprint image with fingerprint features in an inventory;

The recognition success determination module determines that the recognition is successful when the feature information of the first fingerprint image is compared with the fingerprint feature in the inventory.

In a third aspect, an embodiment of the present invention further provides a mobile terminal, including a fingerprint sensor, and a fingerprint identification device according to any embodiment of the present invention.

Beneficial effect

The invention stores the preset calibration value in the mobile terminal, acquires the first fingerprint image with the preset calibration value, extracts the feature information of the first fingerprint image, and performs the feature information of the first fingerprint image and the fingerprint feature in the inventory. If the comparison is successful, the identification is successful. Since the preset calibration value is stored in the mobile terminal, the first fingerprint image can be directly obtained by using the preset calibration value, and the subsequent operation can be performed, thereby saving fingerprint recognition. Time to enhance the user experience.

DRAWINGS

1 is a flowchart of a fingerprint identification method according to Embodiment 1 of the present invention;

2 is a flowchart of a fingerprint identification method according to Embodiment 2 of the present invention;

3 is a flowchart of a fingerprint identification method according to Embodiment 3 of the present invention;

4 is a schematic structural diagram of a fingerprint identification apparatus according to Embodiment 4 of the present invention;

FIG. 5 is a schematic structural diagram of a mobile terminal according to Embodiment 5 of the present invention;

FIG. 6 is a schematic structural diagram of a mobile terminal according to an embodiment of the present invention.

BEST MODE FOR CARRYING OUT THE INVENTION

The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. It should also be noted that, for ease of description, only some, but not all, of the structures related to the present invention are shown in the drawings.

Embodiment 1

1 is a flowchart of a fingerprint identification method according to Embodiment 1 of the present invention. The present embodiment is applicable to the case of fingerprint identification. The method may be implemented by hardware or software in a mobile terminal, and specifically includes the following steps:

Step 110: Acquire a first fingerprint image by using a preset calibration value by using a fingerprint sensor.

Wherein, before using the fingerprint sensor, the fingerprint sensor is calibrated according to environmental conditions, wherein the calibration value means that when the fingerprint sensor is unloaded, the program in the fingerprint sensor obtains a preset calibration value according to the environmental condition, and presets The calibration value is stored in the mobile terminal, and is used to acquire a fingerprint image with a preset calibration value when the fingerprint is triggered to the fingerprint sensor.

Step 120: Extract feature information of the first fingerprint image.

After the first fingerprint image is obtained, the first fingerprint image may be processed and its feature information obtained.

Step 130: Compare feature information of the first fingerprint image with fingerprint features in an inventory;

Before using fingerprint recognition, the fingerprint sensor first inputs the required fingerprint into the fingerprint sensor, and stores the feature of the fingerprint in the inventory. After the fingerprint sensor processes the collected first fingerprint image and extracts the feature information, It is possible to compare the feature information of the fingerprints previously entered in the inventory.

Step 140: If the comparison is successful, it is determined that the recognition is successful.

If the comparison is successful, it can be determined that the fingerprint triggering the fingerprint sensor at this time is a fingerprint already stored in the inventory, and then the fingerprint sensor determines that the fingerprint recognition is successful.

In the technical solution of the embodiment, the fingerprint image is obtained by using the preset calibration value by the fingerprint sensor; then the feature information of the fingerprint image is extracted; and then the feature information of the fingerprint image is compared with the fingerprint feature in the inventory; If the comparison is successful, it is determined that the recognition is successful. The invention stores the preset calibration value in the mobile terminal, acquires the first fingerprint image with the preset calibration value, extracts the feature information of the first fingerprint image, and compares the feature information of the first fingerprint image with the fingerprint feature in the inventory. Yes, if the comparison is successful, the recognition is successful, which can save the time of fingerprint recognition and improve the user experience.

Embodiment 2

FIG. 2 is a flowchart of a fingerprint identification method according to Embodiment 2 of the present invention. The present embodiment is applicable to the case of fingerprint identification. The present embodiment is optimized based on the first embodiment, and specifically includes the following steps:

Step 210: Acquire a first fingerprint image by using a preset calibration value by using a fingerprint sensor.

Step 220: Extract feature information of the first fingerprint image.

Step 230: Compare feature information of the first fingerprint image with fingerprint features in inventory;

Step 240: If the comparison is unsuccessful, adjust the preset calibration value according to the first setting rule to obtain a new calibration value;

The first setting rule means that if the comparison with the preset calibration value is unsuccessful, the fingerprint sensor analyzes the defect of the preset calibration value, and the new calibration value can be obtained by overcoming the defect of the preset calibration value. .

Specifically, the fingerprint sensor may adjust the preset calibration value by adjusting the gain and offset in the circuit corresponding to each pixel point in the fingerprint sensor to overcome the defect of the previously acquired image, and then obtain a new calibration value.

Step 250: Acquire a second fingerprint image by using the new calibration value by using a fingerprint sensor;

The image is captured using the obtained new calibration value to obtain a second fingerprint image.

Step 260: Extract feature information of the second fingerprint image.

After obtaining the second fingerprint image, the second fingerprint image is processed and its feature information is obtained.

Step 270: Compare feature information of the second fingerprint image with fingerprint features in inventory.

The feature information of the second fingerprint image is compared with the fingerprint feature in the fingerprint sensor inventory.

Step 280: If the comparison is successful, it is determined that the recognition is successful.

After the comparison is performed in step 230 or step 270, if the comparison is successful, it may be determined that the fingerprint triggering the fingerprint sensor at this time is the fingerprint already stored in the inventory, and then the fingerprint sensor determines that the fingerprint recognition is successful.

Further, after comparing the feature information of the second fingerprint image with the fingerprint feature in the inventory, if the comparison is unsuccessful, determining that there is no fingerprint corresponding to the second fingerprint image in the inventory, that is, performing the step 290.

If the second fingerprint image is acquired with the new calibration value, then the feature information of the second fingerprint image is extracted, and the feature information of the second fingerprint image is compared with the fingerprint feature in the inventory, and if the comparison is unsuccessful, the feature is not performed. The comparison determines that there are no fingerprint features corresponding to the fingerprint in the inventory.

In the technical solution of the embodiment, when the quality of the first fingerprint image acquired by the fingerprint sensor with the preset calibration value is not good, the feature information of the extracted first fingerprint image may not be related to the fingerprint feature in the inventory. Performing matching, causing the comparison to be unsuccessful, then adjusting the preset calibration value according to the first setting rule to obtain a new calibration value; acquiring the second fingerprint image by using the new calibration value by the fingerprint sensor; extracting The feature information of the second fingerprint image; comparing the feature information of the second fingerprint image with the fingerprint feature in the inventory; if the comparison is unsuccessful, determining that the inventory does not correspond to the second fingerprint image fingerprint. This can avoid the result that the fingerprint identification cannot be matched because the calibration value is not good when the image is captured, and the user can be provided with an opportunity to compare and improve the user experience.

Embodiment 3

FIG. 3 is a flowchart of a fingerprint identification method according to Embodiment 3 of the present invention. The present embodiment is applicable to the case of fingerprint identification. The present embodiment is optimized based on the first embodiment, and specifically includes the following steps:

Step 310: Acquire a first fingerprint image by using a preset calibration value by using a fingerprint sensor.

Step 320: Extract feature information of the first fingerprint image.

Step 330: Compare feature information of the first fingerprint image with fingerprint features in inventory;

Step 340: If the comparison is successful, it is determined that the recognition is successful.

Further, based on the foregoing technical solutions, the method further includes:

Step 350: Count the number of times the first fingerprint image is acquired and compared by using a preset calibration value;

After the first fingerprint image is acquired with the preset calibration value and compared for a period of time, the first fingerprint image is acquired with the preset calibration value and the number of comparisons is performed.

Step 360: When the first fingerprint image is acquired by using the preset calibration value and the number of comparisons reaches the first set number of times, the number of unsuccessful comparisons in the number of comparisons is counted;

When the first fingerprint image is acquired by using the preset calibration value and the number of comparisons reaches the first set number of times, the number of times set for the first time may be randomly taken, as long as the user feels that the number of times is appropriate, for example, 50 times, then the number of unsuccessful comparisons in the number of these 50 comparisons can be counted.

Step 370: When the number of unsuccessful comparisons exceeds the second set number of times, adjusting the preset calibration value according to the second setting rule to obtain a second preset calibration value, and replacing the second preset calibration value. The preset calibration value.

When the number of unsuccessful comparisons obtained by the statistics reaches the second set number of times, the preset calibration value can be replaced by the second preset calibration value. The second set number of times may be obtained according to a proportional relationship with the first set number of times. For example, the second set number of times may reach 50%-100% of the first set number of times, and specifically may be 80%. Once the number of settings is 50, then when the second set number of times reaches 40, then the preset calibration value can be adjusted according to the second setting rule to obtain the second preset calibration value, and then The preset calibration value is replaced with the second preset calibration value, and the second preset calibration value is stored in the mobile terminal.

The second setting rule means that if the comparison is not successful by using the preset calibration value, the fingerprint sensor analyzes the defect of the preset calibration value, and overcomes the defect existing in the preset calibration value. A second preset calibration value can be obtained.

Specifically, the fingerprint sensor may adjust a preset calibration value by adjusting a gain and an offset in a circuit corresponding to each pixel point in the fingerprint sensor, so as to overcome the defect of the previously acquired fingerprint image, and then obtain a second preset. The calibration value is stored in the mobile terminal, and the preset calibration value is replaced, and when the fingerprint is triggered to the fingerprint sensor, the fingerprint image is acquired by using the second preset calibration value.

In the technical solution of the embodiment, after the preset calibration value is used for a period of time, the first fingerprint image is obtained by using the preset calibration value, and the number of comparisons reaches the first set number of times, and the number of comparisons is counted. The number of times the comparison is unsuccessful; when the number of unsuccessful comparisons exceeds the second set number of times, the preset calibration value is adjusted according to the second setting rule to obtain a second preset calibration value, and the second is used. The preset calibration value replaces the preset calibration value, and the second preset calibration value is stored in the mobile terminal, and then the fingerprint image can be acquired by using the second preset calibration value, which is beneficial for saving fingerprint recognition time. Improve the user's experience by improving the matching of fingerprint sensors.

On the basis of the above technical solution, after acquiring the first fingerprint image by using the preset calibration value by the fingerprint sensor, before extracting the feature information of the first fingerprint image, the method further preferably includes:

Image enhancement processing is performed on the first fingerprint image.

After the first fingerprint image is acquired by using the preset calibration value, it may be that the first fingerprint image is not particularly clear, and the feature information of the fingerprint is extracted later, so that the acquired first fingerprint image can be enhanced when needed. The processing is convenient for extracting the feature information of the first fingerprint image later.

Embodiment 4

4 is a schematic structural diagram of a fingerprint identification apparatus according to Embodiment 4 of the present invention. The apparatus is configured in a mobile terminal. The method may be performed in the foregoing embodiment. The apparatus includes:

The first image obtaining module 401 is configured to acquire a first fingerprint image by using a preset calibration value;

The first feature extraction module 402 is configured to extract feature information of the first fingerprint image;

The first feature comparison module 403 is configured to compare the feature information of the first fingerprint image with the fingerprint feature in the inventory;

The recognition success determination module 404 determines that the recognition is successful when the feature information of the first fingerprint image is compared with the fingerprint feature in the inventory.

Preferably, the fingerprint identification device further includes:

And an image enhancement module, configured to perform image enhancement processing on the first fingerprint image after extracting the feature information of the first fingerprint image after acquiring the first fingerprint image by using a preset calibration value by using the fingerprint sensor.

Further, the device further includes:

a calibration value obtaining module, configured to: after comparing the feature information of the first fingerprint image with the fingerprint feature in the inventory, if the comparison is unsuccessful, the preset calibration value is according to the first setting rule Make adjustments to get new calibration values.

a second image acquisition module, configured to acquire a second fingerprint image by using the new calibration value by using a fingerprint sensor;

a second feature extraction module, configured to extract feature information of the second fingerprint image;

The second feature comparison module is configured to compare the feature information of the second fingerprint image with the fingerprint feature in the inventory.

Further, the device further includes:

The information determining module is configured to compare the feature information of the second fingerprint image with the fingerprint feature in the inventory, and if the comparison is unsuccessful, determine that there is no fingerprint corresponding to the second fingerprint image in the inventory.

Further, the device further includes:

The comparison number statistics module is configured to count the number of times the first fingerprint image is acquired and compared by using a preset calibration value;

Comparing the unsuccessful statistics module, when the first fingerprint image is acquired by using the preset calibration value, and the number of comparisons reaches the first set number of times, the number of unsuccessful comparisons in the number of comparisons is counted;

a calibration value replacement module, configured to adjust the preset calibration value according to a second setting rule when the number of unsuccessful comparisons exceeds a second set number, obtain a second preset calibration value, and use the second preset Let the calibration value replace the preset calibration value.

The above device can perform the method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

Embodiment 5

FIG. 5 is a schematic structural diagram of a mobile terminal according to Embodiment 5 of the present invention. The mobile terminal 50 includes: a fingerprint sensor 51, and further includes: the fingerprint identification device 52 described in any one of the foregoing embodiments.

Specifically, the mobile terminal may be a device held by a user such as a mobile phone or a tablet computer.

The technical solution of the embodiment provides a mobile terminal, where the mobile terminal includes a fingerprint sensor and a fingerprint identification device, and the mobile terminal having the fingerprint identification device stores the preset calibration value in the mobile terminal, and uses the preset calibration. The value is obtained as a fingerprint image, and the feature information of the fingerprint image is extracted, and the feature information of the fingerprint image is compared with the fingerprint feature in the inventory. If the comparison is successful, the recognition is successful, which can save the time of fingerprint recognition and improve the user experience.

As shown in FIG. 6, the mobile terminal 50 may further include RF (Radio). Frequency (RF) circuit 110, memory 120 including one or more (only one shown) computer readable storage medium, input unit 130, display unit 140, sensor 150, audio circuit 160, transmission module 170, including There are one or more (only one shown in the figure) processing core processor 180 and power supply 190 and the like. It will be understood by those skilled in the art that the structure of the mobile terminal 50 shown in FIG. 6 does not constitute a limitation of the mobile terminal 50, may include more or less components than those illustrated, or combine some components, or different components. Arrangement. among them:

The RF circuit 110 is configured to receive and transmit electromagnetic waves, and realize mutual conversion between electromagnetic waves and electrical signals, thereby communicating with a communication network or other devices. The RF circuit 110 may include various existing circuit elements for performing these functions, such as an antenna, a radio frequency transceiver, a digital signal processor, an encryption/decryption chip, a Subscriber Identity Module (SIM) card, a memory, and the like. The RF circuit 110 can communicate with various networks such as the Internet, an intranet, a wireless network, or communicate with other devices over a wireless network. The wireless network described above may include a cellular telephone network, a wireless local area network, or a metropolitan area network. The above wireless networks may use various communication standards, protocols and technologies, including but not limited to global mobile communication systems (Global System for Mobile Communication, GSM), Enhanced Data GSM Environment (Enhanced Data GSM Environment, EDGE), Wideband Code Division Multiple Access (WCDMA), Code Division Multiple Access (Code) Division Access, CDMA), Time Division Multiple Access (Time Division Multiple Access, TDMA), Wireless Fidelity (Wi-Fi) (eg American Institute of Electrical and Electronics Engineers Standard IEEE 802.11a, IEEE) 802.11b, IEEE802.11g and/or IEEE 802.11n), Voice over Internet Protocol (Voice over Internet Protocol, VoIP), Worldwide Interoperability for Microwave Access, Wi-Max, other protocols for mail, instant messaging, and short messages, as well as any other suitable communication protocol, may even include protocols that are not currently being developed.

The memory 120 can be used to store software programs and modules, such as the program instructions/modules corresponding to the fingerprint recognition method/fingerprint recognition device in the above embodiment, and the processor 180 executes various functions by running software programs and modules stored in the memory 120. Application and data processing, that is, the function of fingerprint recognition. Memory 120 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid state memory. In some examples, memory 120 can further include memory remotely located relative to processor 180, which can be connected to mobile terminal 50 over a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The input unit 130 can be configured to receive input numeric or character information and to generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function controls. In particular, input unit 130 can include touch-sensitive surface 131 as well as other input devices 132. Touch-sensitive surface 131, also referred to as a touch display or trackpad, can collect touch operations on or near the user (such as a user using a finger, stylus, etc., on any suitable object or accessory on touch-sensitive surface 131 or The operation near the touch-sensitive surface 131) and driving the corresponding connecting device according to a preset program. Alternatively, the touch-sensitive surface 131 can include two portions of a touch detection device and a touch controller. Wherein, the touch detection device detects the touch orientation of the user, and detects a signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts the touch information into contact coordinates, and sends the touch information. The processor 180 is provided and can receive commands from the processor 180 and execute them. In addition, the touch-sensitive surface 131 can be implemented in various types such as resistive, capacitive, infrared, and surface acoustic waves. In addition to the touch-sensitive surface 131, the input unit 130 can also include other input devices 132. Specifically, other input devices 132 may include, but are not limited to, one or more of a physical keyboard, function keys (such as volume control buttons, switch buttons, etc.), trackballs, mice, joysticks, and the like.

The display unit 140 can be used to display information input by the user or information provided to the user and various graphical user interfaces of the mobile terminal 50, which can be composed of graphics, text, icons, video, and any combination thereof. The display unit 140 may include a display panel 141, and optionally, an LCD (Liquid may be used) Crystal Display, LCD (Organic Light-Emitting) The display panel 141 is configured in the form of a Diode, an organic light emitting diode, or the like. Further, the touch-sensitive surface 131 may cover the display panel 141, and when the touch-sensitive surface 131 detects a touch operation thereon or nearby, it is transmitted to the processor 180 to determine the type of the touch event, and then the processor 180 according to the touch event The type provides a corresponding visual output on display panel 141. Although in FIG. 6, touch-sensitive surface 131 and display panel 141 are implemented as two separate components to implement input and input functions, in some embodiments, touch-sensitive surface 131 can be integrated with display panel 141 for input. And output function.

Mobile terminal 50 may also include at least one type of sensor 150, such as a light sensor, motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may adjust the brightness of the display panel 141 according to the brightness of the ambient light, and the proximity sensor may close the display panel 141 when the mobile terminal 50 moves to the ear. And / or backlight. As a kind of motion sensor, the gravity acceleration sensor can detect the magnitude of acceleration in all directions (usually three axes). When it is stationary, it can detect the magnitude and direction of gravity. It can be used to identify the gesture of the mobile phone (such as horizontal and vertical screen switching, related Game, magnetometer attitude calibration), vibration recognition related functions (such as pedometer, tapping), etc.; Other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor, and the like that can be configured in the mobile terminal 50 are not described herein.

The audio circuit 160, the speaker 161, and the microphone 162 can provide an audio interface between the user and the mobile terminal 50. The audio circuit 160 can transmit the converted electrical data of the received audio data to the speaker 161 for conversion to the sound signal output by the speaker 161; on the other hand, the microphone 162 converts the collected sound signal into an electrical signal by the audio circuit 160. After receiving, it is converted into audio data, and then processed by the audio data output processor 180, transmitted to the terminal, for example, via the RF circuit 110, or outputted to the memory 120 for further processing. The audio circuit 160 may also include an earbud jack to provide communication of the peripheral earphones with the mobile terminal 50.

The mobile terminal 50 can help the user to send and receive emails, browse web pages, access streaming media, etc. through the transmission module 170 (for example, a Wi-Fi module), which provides wireless broadband Internet access to the user. Although FIG. 13 shows the transmission module 170, it can be understood that it does not belong to the essential configuration of the mobile terminal 50, and may be omitted as needed within the scope of not changing the essence of the invention.

The processor 180 is the control center of the mobile terminal 50, connecting various portions of the entire handset with various interfaces and lines, by running or executing software programs and/or modules stored in the memory 120, and recalling data stored in the memory 120. The various functions and processing data of the mobile terminal 50 are executed to perform overall monitoring of the mobile phone. Optionally, the processor 180 may include one or more processing cores; preferably, the processor 180 may integrate an application processor and a modem processor, where the application processor mainly processes an operating system, a user interface, an application, and the like. The modem processor primarily handles wireless communications. It can be understood that the above modem processor may not be integrated into the processor 180.

The mobile terminal 50 also includes a power source 190 (such as a battery) for powering various components. Preferably, the power source can be logically coupled to the processor 180 through a power management system to manage functions such as charging, discharging, and power management through the power management system. . Power supply 190 may also include any one or more of a DC or AC power source, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, and the like.

Although not shown, the mobile terminal 50 may further include a camera, a Bluetooth module, and the like, and details are not described herein. Specifically, in this embodiment, the display unit of the mobile terminal is a touch screen display, the mobile terminal further includes a memory, and one or more programs, wherein one or more programs are stored in the memory and configured to be one or one The above processor executes one or more programs that include instructions for performing the following operations:

Extracting feature information of the first fingerprint image;

The mobile terminal provided by the embodiment of the present invention may be applied to the foregoing corresponding method embodiment. For details, refer to the description of the foregoing embodiment, and details are not described herein again.

A person skilled in the art may understand that all or part of the various steps of the foregoing embodiments may be performed by a program to instruct related hardware. The program may be stored in a computer readable storage medium, and the storage medium may include: Read only memory (ROM, Read Only Memory), Random Access Memory (RAM), disk or CD.

Note that the above are only the preferred embodiments of the present invention and the technical principles applied thereto. Those skilled in the art will appreciate that the present invention is not limited to the specific embodiments described herein, and that various modifications, changes and substitutions may be made without departing from the scope of the invention. Therefore, the present invention has been described in detail by the above embodiments, but the present invention is not limited to the above embodiments, and other equivalent embodiments may be included without departing from the inventive concept. The scope is determined by the scope of the appended claims.

Claims

A fingerprint identification method, wherein the fingerprint identification method comprises:

Extracting feature information of the first fingerprint image;

The fingerprint identification method according to claim 1, wherein after comparing the feature information of the first fingerprint image with the fingerprint feature in the inventory, the method further includes:

If the comparison is unsuccessful, the preset calibration value is adjusted according to the first setting rule to obtain a new calibration value;

Acquiring a second fingerprint image by using the new calibration value by the fingerprint sensor;

Extracting feature information of the second fingerprint image;

The feature information of the second fingerprint image is compared with the fingerprint feature in the inventory.

The fingerprint identification method according to claim 2, wherein after comparing the feature information of the second fingerprint image with the fingerprint feature in the inventory, the method further includes:

If the comparison is unsuccessful, it is determined that there is no fingerprint corresponding to the second fingerprint image in the inventory.

The fingerprint identification method according to claim 1, wherein the fingerprint identification method further comprises:

Counting the number of times the first fingerprint image is acquired using a preset calibration value and compared;

When the first fingerprint image is acquired by using the preset calibration value and the number of comparisons reaches the first set number of times, the number of unsuccessful comparisons in the number of comparisons is counted;

When the number of unsuccessful comparisons exceeds the second set number of times, adjusting the preset calibration value according to the second setting rule to obtain a second preset calibration value, and replacing the pre-preparation with the second preset calibration value Set the calibration value.

The fingerprint identification method according to any one of claims 1 to 4, wherein after acquiring the first fingerprint image by using a preset calibration value by the fingerprint sensor, before extracting the feature information of the first fingerprint image, include:

Image enhancement processing is performed on the first fingerprint image.

The fingerprint identification method according to claim 2, wherein the step of adjusting the preset calibration value according to the first setting rule to obtain a new calibration value comprises:

The fingerprint sensor adjusts the preset calibration value by adjusting the gain and offset in the circuit corresponding to each pixel point in the fingerprint sensor to obtain a new calibration value.

The fingerprint identification method according to claim 4, wherein the step of adjusting the preset calibration value according to the second setting rule to obtain the second preset calibration value comprises:

The fingerprint sensor adjusts a preset calibration value by adjusting a gain and an offset in a circuit corresponding to each pixel point in the fingerprint sensor to obtain the second preset calibration value.

A fingerprint identification device, wherein the fingerprint identification device is disposed in a fingerprint sensor, the fingerprint recognition device comprising:

9. The fingerprint identification device of claim 8, wherein the fingerprint identification device further comprises:

10. The fingerprint identification device of claim 9, wherein the fingerprint identification device further comprises:

The fingerprint identification device of claim 8, wherein the fingerprint identification device further comprises:

The fingerprint identification device according to any one of claims 8-11, wherein the fingerprint identification device further comprises:

13. The fingerprint recognition device according to claim 9, wherein the new calibration value is a preset calibration value adjusted by adjusting a gain and an offset in a circuit corresponding to each pixel point in the fingerprint sensor by the fingerprint sensor. To get the new calibration value.

14. A mobile terminal, comprising a fingerprint sensor, the mobile terminal further comprising a fingerprint identification device, the fingerprint sensor being coupled to the fingerprint recognition device; wherein the fingerprint recognition device comprises:

The mobile terminal of claim 14, wherein the fingerprint identification device further comprises:

The mobile terminal of claim 15, wherein the fingerprint identification device further comprises:

The mobile terminal of any of claims 14-17, wherein the fingerprint identification device further comprises:

19. The mobile terminal of claim 15, wherein the new calibration value is adjusted by a fingerprint sensor by adjusting a gain and an offset in a circuit corresponding to each pixel point in the fingerprint sensor to The new calibration value is obtained.

20. The mobile terminal of claim 17, wherein the second preset calibration value is a preset calibration value adjusted by adjusting a gain and an offset in a circuit corresponding to each pixel point in the fingerprint sensor by the fingerprint sensor And obtaining the second preset calibration value.