CN105912920A - Fingerprint unlocking method and terminal - Google Patents

Abstract

The embodiment of the invention discloses a fingerprint unlocking method, which comprises the following steps: in the process that a user presses a fingerprint identification module, a capacitance value is acquired in each acquisition area of N acquisition areas which are divided in advance by the fingerprint identification module in parallel, wherein N is an integer greater than 1; converting the capacitance values acquired by each of the N acquisition regions into the N fingerprint images; selecting one fingerprint image with the best quality from the N fingerprint images as a target fingerprint image; matching the target fingerprint image with a preset fingerprint template; and unlocking the terminal when the target fingerprint image is successfully matched with the preset fingerprint template. The embodiment of the invention also provides the terminal. The fingerprint unlocking efficiency of the terminal can be improved through the embodiment of the invention.

Description

A fingerprint unlocking method and terminal

technical field

The invention relates to the technical field of electronic equipment, in particular to a fingerprint unlocking method and a terminal.

Background technique

With the rapid development of information technology, the use of terminals (such as mobile phones, tablet computers, etc.) is becoming more and more popular. As a standard technology on the terminal, fingerprint recognition technology can be widely used not only in unlocking, waking up, mobile payment, etc. of the terminal. While the fingerprint recognition technology is popular, in order to achieve fast unlocking, the unlocking time of the terminal is also a direct concern of the terminal manufacturer. In the prior art, often due to the low efficiency of fingerprint unlocking, user experience is reduced.

Contents of the invention

Embodiments of the present invention provide a fingerprint unlocking method and a terminal, which can improve the efficiency of fingerprint unlocking.

The first aspect of the embodiment of the present invention discloses a fingerprint unlocking method, including:

During the process when the user presses the fingerprint recognition module, each of the N collection regions pre-divided by the fingerprint recognition module is used in parallel to collect capacitance values, and the N is an integer greater than 1;

converting the capacitance value collected by each of the N collection regions into the N fingerprint images;

Select a fingerprint image with the best quality among the N fingerprint images as the target fingerprint image;

matching the target fingerprint image with a preset fingerprint template;

When the target fingerprint image matches the preset fingerprint template successfully, unlock the terminal.

The second aspect of the embodiment of the present invention discloses a terminal, including:

The acquisition unit is used to collect capacitance values in parallel using each of the N acquisition areas pre-divided by the fingerprint identification module when the user presses the fingerprint identification module, where N is an integer greater than 1;

a conversion unit, configured to convert the capacitance value collected by each of the N collection areas into the N fingerprint images;

A selection unit, configured to select a fingerprint image with the best quality among the N fingerprint images as the target fingerprint image;

a matching unit, configured to match the target fingerprint image with a preset fingerprint template;

An unlocking unit, configured to unlock the terminal when the target fingerprint image matches the preset fingerprint template successfully.

The third aspect of the embodiment of the present invention discloses a terminal, including:

processor, memory;

The processor is configured to invoke the executable program code in the memory to execute part or all of the steps in the first aspect.

Implementing the embodiment of the present invention has the following beneficial effects:

It can be seen that in the embodiment of the present invention, when the user presses the fingerprint recognition module, each of the N collection regions pre-divided by the fingerprint recognition module is used in parallel to collect capacitance values, where N is an integer greater than 1, Convert the capacitance value collected by each of the N collection areas into N fingerprint images, select the fingerprint image with the best quality among the N fingerprint images as the target fingerprint image, and combine the target fingerprint image with the preset fingerprint template Perform matching, and unlock the terminal when the target fingerprint image matches the preset fingerprint template successfully. Therefore, since fingerprint images can be collected in parallel from multiple collection areas, and the fingerprint image with the best image quality can be combined with the preset fingerprint template, the matching efficiency can be improved, that is, the terminal unlocking efficiency can be improved.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings that need to be used in the embodiments. Obviously, the drawings in the following description are some embodiments of the present invention. Those of ordinary skill in the art can also obtain other drawings based on these drawings without any creative effort.

FIG. 1 is a schematic flowchart of a first embodiment of a fingerprint unlocking method disclosed in an embodiment of the present invention;

FIG. 2 is a schematic flowchart of a second embodiment of a fingerprint unlocking method disclosed in an embodiment of the present invention;

Fig. 3a is a schematic structural diagram of a first embodiment of a terminal disclosed in an embodiment of the present invention;

FIG. 3b is a schematic structural diagram of a selection unit of the terminal described in FIG. 3a disclosed in an embodiment of the present invention;

Fig. 3c is another schematic structural diagram of the first embodiment of a terminal disclosed in the embodiment of the present invention;

Fig. 3d is a schematic structural diagram of the conversion unit of the terminal described in Fig. 3a disclosed by the embodiment of the present invention;

FIG. 3e is a schematic structural diagram of a selection unit of the terminal described in FIG. 3a disclosed in an embodiment of the present invention;

FIG. 4 is a schematic structural diagram of a second embodiment of a terminal disclosed in an embodiment of the present invention;

Fig. 5 is a schematic structural diagram of a mobile phone disclosed in an embodiment of the present invention.

detailed description

The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

The terms "first", "second", "third" and "fourth" in the description and claims of the present invention and the drawings are used to distinguish different objects, rather than to describe a specific order . Furthermore, the terms "include" and "have", as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but optionally also includes unlisted steps or units, or optionally further includes For other steps or units inherent in these processes, methods, products or apparatuses.

Reference herein to an "embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present invention. The occurrences of this phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is understood explicitly and implicitly by those skilled in the art that the embodiments described herein can be combined with other embodiments.

The terminal described in the embodiment of the present invention may include a smart phone (such as an Android phone, an iOS phone, a Windows Phone, etc.), a tablet computer, a palmtop computer, a notebook computer, a mobile Internet device (MID, Mobile Internet Devices) or a wearable device, etc. , the above-mentioned terminals are only examples, not exhaustive, including but not limited to the above-mentioned terminals.

Please refer to FIG. 1 , which is a schematic flowchart of a first embodiment of a fingerprint unlocking method provided by an embodiment of the present invention. The fingerprint unlocking method described in this embodiment includes the following steps:

101. When the user presses the fingerprint recognition module, use each of the N collection regions pre-divided by the fingerprint recognition module to collect capacitance values in parallel, where N is an integer greater than 1.

Among them, the terminal can divide the fingerprint identification module into N collection areas in advance, and N is an integer greater than or equal to 1. As shown in Figure 1a, the fingerprint identification module is divided into four areas, including the first area, the second area, and the second area. In the third area and the fourth area, when the user presses the fingerprint identification module of the terminal, each area can collect the capacitance value separately. Preferably, multiple processes or threads can be used to collect the capacitance value. If there are four areas, the capacitance value can be collected separately. Four processes or threads are used to collect capacitance values. For example, the four processes are: the first process, the second process, the third process and the fourth process. The first process collects the capacitance value of the first area, and the second process collects the second process. For the capacitance value of the second area, the third process collects the capacitance value of the third area and the fourth process collects the capacitance value of the fourth area. The above is only illustrated with 4 areas. In actual implementation, the fingerprint identification module can also be divided into 2, 3, or even more than 4 acquisition areas.

102. Convert the capacitance value collected by each of the N collection areas into the N fingerprint images.

Wherein, for the collection area i, the collected capacitance value can be converted into a fingerprint image, and the collection area i is one of the aforementioned N collection areas. Usually, the capacitance value is between 0 and 1, and the value of the fingerprint image is between 0 and 255, then the capacitance value can be mapped to the corresponding capacitance value, for example, if the capacitance value is 0.5, then the corresponding pixel value is for 125.

Optionally, the above step 102 may include the following steps:

21), respectively performing binarization processing on the capacitance values collected in each of the N collection regions to obtain the N groups of binarized capacitance values;

22). Converting the N groups of binarized capacitance values into the N fingerprint images.

Wherein, in step 21, the average value of all capacitance values can be used as the binarization threshold, and the capacitance values collected in each of the N collection areas are binarized according to the binarization threshold, to obtain N groups of two Value capacitance value. It is also possible to use the capacitance value of each collection area as the binarization threshold of the collection area, and perform binarization processing on the capacitance values collected in the collection area according to the binarization threshold to obtain a set of binarization capacitance values .

Correspondingly, after step 22, N sets of binarized capacitance values are converted into N fingerprint images, and each fingerprint image can also be called a binarized fingerprint image.

103. Select a fingerprint image with the best quality among the N fingerprint images as the target fingerprint image.

Among them, the better the image quality, the more information it contains. Therefore, the best fingerprint image among the N fingerprint images can be selected as the target fingerprint image.

It should be noted that the above-mentioned quality can preferably be: the largest signal-to-noise ratio, the largest number of feature points, the largest definition, etc. The best quality is not limited to this, and will not be repeated here.

Optionally, step 103 may include:

31) Extract feature points of the N fingerprint images respectively;

32) Taking the fingerprint image with the most feature points among the N fingerprint images as the target fingerprint image.

Wherein, in step 31, the feature points of N fingerprint images can be extracted respectively. Preferably, the same feature point extraction algorithm is used to perform feature extraction on the N fingerprint images. The feature point extraction algorithm can be: Harris corner point extraction algorithm, scale Invariant feature extraction (Scale Invariant Feature Transform, SIFT) algorithm and so on. In step 32, the fingerprint image with the largest number of feature points may be used as the target fingerprint image.

Optionally, step 103 may include the following steps:

33), performing image quality evaluation on the N fingerprint images respectively, to obtain the N image quality evaluation values;

34) Taking the fingerprint image corresponding to the maximum image quality evaluation value among the N image quality evaluation values as the target fingerprint image.

Wherein, step 33 may include the following steps:

331), using a plurality of preset evaluation indicators to evaluate the image quality of the fingerprint image i to obtain the plurality of evaluation values, the fingerprint image i is one of the N fingerprint images;

332). Determine the image quality evaluation value of the fingerprint image i according to the multiple evaluation values and the preset weights corresponding to the multiple preset evaluation indicators.

The above-mentioned evaluation indicators may include but not limited to: signal-to-noise ratio, average gradient, edge intensity, information entropy, average gray value, standard deviation, sharpness, etc., which are not limited here.

For example, three evaluation indicators can be selected to evaluate the image quality of fingerprint images, assuming that the three evaluation indicators are: A, B and C, and the preset weight value corresponding to evaluation indicator A is k1, 0<k1<1, The preset weight value corresponding to the evaluation index B is 0<k2<1, and the preset weight value corresponding to the evaluation index C is 0<k3<1, wherein, k1+k2+k3=1, then the image quality evaluation value=A *k1+B*k2+C*k3. For fingerprint image i, the values of its evaluation indexes A, B, and C can be calculated respectively. Assume that the value of evaluation index A is a, the value of evaluation index B is b, and the value of evaluation index C is c. Then, Image quality evaluation value of fingerprint image i=a*k1+b*k2+c*k3.

Of course, one evaluation index can also be used to evaluate the image quality of the above N fingerprint images, but more accurate evaluation results can be obtained by performing image quality evaluation on the above N fingerprint images with multiple evaluation indexes.

Optionally, between step 102 and step 103, if the N fingerprint images obtained in step 102 are not binary fingerprint images, then the N fingerprint images can be converted into binary fingerprint images to obtain N binary fingerprint images Then select a binary fingerprint image with the best image quality from the N binary fingerprint images in step 103 as the target fingerprint image.

104. Match the target fingerprint image with a preset fingerprint template.

Wherein, the features of the target fingerprint image and the features of the preset fingerprint template can be extracted respectively. Here, the features can be feature lines and feature points. Then, it is judged whether the similarity between the features of the target fingerprint image and the features of the preset fingerprint template is greater than A preset threshold. The preset threshold is a threshold used for unlocking settings. If the threshold is greater than the threshold, the terminal can be unlocked. If it is less than or equal to the threshold, the terminal cannot be unlocked.

Optionally, if step 103 is executed according to 31 and 32, then the feature points have been extracted, then, in step 104, feature point extraction can be performed on the preset fingerprint template according to the method of extracting feature points in 31, and then, the The feature points of the above-mentioned fingerprint image with the best image quality are matched with the feature points of the preset fingerprint template. If the two match successfully, step 105 can be performed. If the two match fails, the user is prompted to re-enter the fingerprint.

105. When the target fingerprint image matches the preset fingerprint template successfully, unlock the terminal.

Wherein, when the target fingerprint image matches the preset fingerprint template successfully, the terminal may be unlocked or an application in the terminal may be unlocked. For example, when the terminal is in the off-screen state, unlock the terminal, the display screen of the terminal lights up, and display the unlocked desktop; or, when the terminal is in the bright state, unlock the terminal, and display the unlocked desktop; Or, when the terminal is in an unlocked state, at least one application of the terminal can be unlocked, that is, start the at least one application or display a preset page of an application in the at least one application; or, when the terminal is in a screen-off state Next, at least one application of the terminal can be unlocked, that is, the at least one application can be started or a preset page of a certain application in the at least one application can be displayed.

It can be seen that in the embodiment of the present invention, when the user presses the fingerprint recognition module, each of the N collection regions pre-divided by the fingerprint recognition module is used in parallel to collect capacitance values, where N is an integer greater than 1, Convert the capacitance value collected by each of the N collection areas into N fingerprint images, select the fingerprint image with the best quality among the N fingerprint images as the target fingerprint image, and combine the target fingerprint image with the preset fingerprint template Perform matching, and unlock the terminal when the target fingerprint image matches the preset fingerprint template successfully. Therefore, since fingerprint images can be collected in parallel from multiple collection areas, the speed of fingerprint image collection can be accelerated, and the fingerprint image with the best image quality can be combined with the preset fingerprint template, thereby improving the matching efficiency, that is, improving the terminal unlocking efficiency.

Consistent with the above embodiment, please refer to FIG. 2 , which is a schematic flowchart of a second embodiment of a fingerprint unlocking method provided by an embodiment of the present invention. The fingerprint unlocking method described in this embodiment includes the following steps:

201. When the user presses the fingerprint recognition module, use each of the N collection regions pre-divided by the fingerprint recognition module to collect capacitance values in parallel, where N is an integer greater than 1.

202. Convert the capacitance value collected by each of the N collection areas into the N fingerprint images.

203. Extract feature points of the N fingerprint images respectively;

204. Use the fingerprint image with the most feature points among the N fingerprint images as the target fingerprint image.

205. Determine whether the number of feature points of the target fingerprint image is within a preset range.

Optionally, if yes, step 208 is performed.

206. Prompt the user to press the fingerprint identification module again when the number of feature points is lower than the preset range.

207. When the number of feature points is within the preset range, perform image enhancement processing on the target fingerprint image.

Wherein, if step 207 is executed, image enhancement processing may be performed on the target fingerprint image, and then, in step 208, the target fingerprint image after image enhancement processing may be matched with a preset fingerprint template. The methods of image enhancement processing may include but not limited to: histogram equalization, gray scale stretching, wavelet transform, image restoration and so on.

208. Match the target fingerprint image with a preset fingerprint template.

209. When the target fingerprint image matches the preset fingerprint template successfully, unlock the terminal.

Wherein, the specific implementation process of other steps not specifically described in FIG. 2 can refer to the fingerprint unlocking method described in FIG. 1 , which will not be repeated here.

In step 204, the preset range can be set by the user or defaulted by the system. The preset range can include but not limited to: [20, 50], (40, 80), (35, 70], etc., the specific value depends on the specific situation Depends, it is not limited here.

The following is a device for implementing the fingerprint unlocking method described in FIG. 1 or FIG. 2 , specifically as follows.

Please refer to FIG. 3 a , which is a schematic structural diagram of a first embodiment of a terminal provided by an embodiment of the present invention. The terminal described in this embodiment includes: an acquisition unit 301, a conversion unit 302, a selection unit 303, a matching unit 304, and an unlocking unit 305, specifically as follows:

The acquisition unit 301 is configured to collect capacitance values in parallel using each of the N acquisition areas pre-divided by the fingerprint identification module when the user presses the fingerprint identification module, where N is an integer greater than 1;

A conversion unit 302, configured to convert the capacitance value collected by each of the N collection areas into the N fingerprint images;

A selection unit 303, configured to select a fingerprint image with the best quality among the N fingerprint images as the target fingerprint image;

A matching unit 304, configured to match the target fingerprint image with a preset fingerprint template;

The unlocking unit 305 is configured to unlock the terminal when the target fingerprint image matches the preset fingerprint template successfully.

Optionally, as shown in FIG. 3b, the selecting unit 303 of the terminal described in FIG. 3a may include:

An extraction module 3031, configured to extract feature points of the N fingerprint images respectively;

The first determining module 3032 is configured to use the fingerprint image with the most feature points among the N fingerprint images as the target fingerprint image.

Optionally, as shown in FIG. 3c, the terminal described in FIG. 3a may further include: a judgment unit 306, a prompt unit 307, and a first processing unit 308, which are described in detail below:

A judging unit 306, configured to judge whether the number of feature points of the target fingerprint image is within a preset range after the selection unit 303 selects a fingerprint image with the best quality among the N fingerprint images as the target fingerprint image;

When the judging result of the judging unit 306 is that the number of feature points exceeds a preset range, the matching unit 304 matches the target fingerprint image with a preset fingerprint template;

A prompting unit 307, configured to prompt the user to press the fingerprint identification module again when the judgment result of the judging unit 306 is that the number of feature points is lower than the preset range;

The first processing unit 308 is configured to perform image enhancement processing on the target fingerprint image when the judging result of the judging unit 306 is that the number of feature points is within the preset range.

Optionally, as shown in FIG. 3d, the conversion unit 302 of the terminal described in FIG. 3a includes:

The second processing module 3021 is configured to perform binarization processing on the capacitance values collected in each of the N collection areas, respectively, to obtain the N sets of binarized capacitance values;

A conversion module 3022, configured to convert the N sets of binarized capacitance values into the N fingerprint images.

Optionally, as shown in FIG. 3e, the selecting unit 303 of the terminal described in FIG. 3a may include:

The first evaluation module 3033 is configured to perform image quality evaluation on the N fingerprint images respectively, to obtain the N image quality evaluation values;

The second determination module 3034 is configured to use the fingerprint image corresponding to the maximum image quality evaluation value among the N image quality evaluation values as the target fingerprint image.

Further, the first evaluation module 3033 includes:

The second evaluation module (not marked in the figure) is used to evaluate the image quality of the fingerprint image i by using a plurality of preset evaluation indicators to obtain the plurality of evaluation values, and the fingerprint image i is the N one of the fingerprint images;

A third determination module (not shown in the figure), configured to determine the image quality evaluation value of the fingerprint image i according to the plurality of evaluation values and the preset weights corresponding to the plurality of preset evaluation indicators.

It can be seen that the terminal described in the embodiment of the present invention can use each of the N collection areas pre-divided by the fingerprint identification module to collect capacitance values in parallel when the user presses the fingerprint identification module, where N is is greater than 1 integer, convert the capacitance value collected by each of the N collection areas into N fingerprint images, select a fingerprint image with the best quality among the N fingerprint images as the target fingerprint image, and combine the target fingerprint image with The preset fingerprint template is matched, and the terminal is unlocked when the target fingerprint image is successfully matched with the preset fingerprint template. Therefore, since fingerprint images can be collected in parallel from multiple collection areas, the fingerprint collection speed can be accelerated, and the fingerprint image with the best image quality can be combined with the preset fingerprint template, thereby improving the matching efficiency, that is, improving the terminal unlocking efficiency.

Please refer to FIG. 4 , which is a schematic structural diagram of a second embodiment of a terminal provided by an embodiment of the present invention. The terminal described in this embodiment includes: at least one input device 1000; at least one output device 2000; at least one processor 3000, such as a CPU; and a memory 4000, the above-mentioned input device 1000, output device 2000, processor 3000 and memory The 4000 is connected via the bus 5000.

Wherein, the above-mentioned input device 1000 may specifically be a touch panel, a physical button or a mouse, a fingerprint recognition module, and the like.

The aforementioned output device 2000 may specifically be a display screen.

The above-mentioned memory 4000 may be a high-speed RAM memory, or may be a non-volatile memory (non-volatile memory), such as a magnetic disk memory. The above-mentioned memory 4000 is used to store a set of program codes, and the above-mentioned input device 1000, output device 2000 and processor 3000 are used to call the program codes stored in the memory 4000, and perform the following operations:

The above-mentioned processor 3000 is used for:

During the process when the user presses the fingerprint recognition module, each of the N collection regions pre-divided by the fingerprint recognition module is used in parallel to collect capacitance values, and the N is an integer greater than 1;

converting the capacitance value collected by each of the N collection regions into the N fingerprint images;

Select a fingerprint image with the best quality among the N fingerprint images as the target fingerprint image;

matching the target fingerprint image with a preset fingerprint template;

When the target fingerprint image matches the preset fingerprint template successfully, unlock the terminal.

Optionally, the processor 3000 selects a fingerprint image with the best quality among the N fingerprint images as the target fingerprint image, including:

Extract feature points of the N fingerprint images respectively;

The fingerprint image with the most feature points among the N fingerprint images is used as the target fingerprint image.

Optionally, after the processor 3000 selects the fingerprint image with the best quality among the N fingerprint images as the target fingerprint image, it is also specifically used for:

judging whether the number of feature points of the target fingerprint image is within a preset range;

When the number of feature points exceeds a preset range, performing the matching of the target fingerprint image with a preset fingerprint template;

When the number of feature points is lower than the preset range, prompting the user to press the fingerprint identification module again;

When the number of feature points is within the preset range, image enhancement processing is performed on the target fingerprint image.

Optionally, the processor 3000 converts the capacitance value collected by each of the N collection areas into the N fingerprint images, including:

performing binarization processing on the capacitance values collected in each of the N collection regions, respectively, to obtain the N groups of binarized capacitance values;

Converting the N groups of binarized capacitance values into the N fingerprint images.

Optionally, the processor 3000 selects a fingerprint image with the best quality among the N fingerprint images as the target fingerprint image, including:

performing image quality evaluation on the N fingerprint images respectively to obtain the N image quality evaluation values;

The fingerprint image corresponding to the maximum image quality evaluation value among the N image quality evaluation values is used as the target fingerprint image.

Optionally, the processor 3000 performs image quality evaluation on the N fingerprint images respectively to obtain the N image quality evaluation values, including:

performing image quality evaluation on the fingerprint image i by using a plurality of preset evaluation indicators to obtain the plurality of evaluation values, the fingerprint image i being one of the N fingerprint images;

Determine the image quality evaluation value of the fingerprint image i according to the multiple evaluation values and the preset weights corresponding to the multiple preset evaluation indicators.

FIG. 5 shows a block diagram of a partial structure of a mobile phone related to a terminal provided by an embodiment of the present invention. Referring to FIG. 5 , the mobile phone includes: a radio frequency (Radio Frequency, RF) circuit 510, a memory 520, an input unit 530, a display unit 540, a sensor 550, an audio circuit 560, a wireless fidelity (Wireless Fidelity, WiFi) module 570, a processor 580 , and power supply 590 and other components. Those skilled in the art can understand that the structure of the mobile phone shown in FIG. 5 is not limited to the mobile phone, and may include more or less components than shown in the figure, or combine some components, or arrange different components.

The following is a specific introduction to each component of the mobile phone in conjunction with Figure 5:

The RF circuit 510 can be used for sending and receiving information or receiving and sending signals during a call. In particular, after receiving the downlink information from the base station, the processor 580 processes it; in addition, it sends the designed uplink data to the base station. Generally, the RF circuit 510 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier (Low Noise Amplifier, LNA), a duplexer, and the like. In addition, RF circuitry 510 may also communicate with networks and other devices via wireless communications. The above wireless communication can use any communication standard or protocol, including but not limited to Global System of Mobile Communication (Global System of Mobilecommunication, GSM), General Packet Radio Service (General Packet Radio Service, GPRS), Code Division Multiple Access (Code Division Multiple Access, CDMA), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (Long Term Evolution, LTE), email, Short Messaging Service (Short Messaging Service, SMS), etc.

The memory 520 can be used to store software programs and modules, and the processor 580 executes various functional applications and data processing of the mobile phone by running the software programs and modules stored in the memory 520 . The memory 520 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application program required by a function (such as a sound playback function, an image playback function, etc.); Data created by the use of mobile phones (such as audio data, phonebook, etc.), etc. In addition, the memory 520 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage devices.

The input unit 530 can be used to receive input numbers or character information, and generate key signal input related to user settings and function control of the mobile phone. Specifically, the input unit 530 may include a touch panel 531 and other input devices 532 . The touch panel 531, also referred to as a touch screen, can collect touch operations of the user on or near it (for example, the user uses any suitable object or accessory such as a finger or a stylus on the touch panel 531 or near the touch panel 531). operation), and drive the corresponding connection device according to the preset program. Optionally, the touch panel 531 may include two parts, a touch detection device and a touch controller. Among them, the touch detection device detects the user's touch orientation, and detects the 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 it into contact coordinates, and sends it to the to the processor 580, and can receive and execute commands sent by the processor 580. In addition, the touch panel 531 can be implemented in various types such as resistive, capacitive, infrared, and surface acoustic wave. In addition to the touch panel 531 , the input unit 530 may also include other input devices 532 . Specifically, other input devices 532 may include but not limited to one or more of a physical keyboard, function keys (such as volume control keys, switch keys, etc.), trackball, mouse, joystick, and the like.

The display unit 540 may be used to display information input by or provided to the user and various menus of the mobile phone. The display unit 540 may include a display panel 541. Optionally, the display panel 541 may be configured in the form of a liquid crystal display (Liquid Crystal Display, LCD) or an organic light-emitting diode (Organic Light-Emitting Diode, OLED). Further, the touch panel 531 may cover the display panel 541, and when the touch panel 531 detects a touch operation on or near it, it transmits to the processor 580 to determine the type of the touch event, and then the processor 580 determines the type of the touch event according to the touch event. The type provides a corresponding visual output on the display panel 541 . Although in FIG. 5 , the touch panel 531 and the display panel 541 are used as two independent components to realize the input and input functions of the mobile phone, in some embodiments, the touch panel 531 and the display panel 541 can be integrated to form a mobile phone. Realize the input and output functions of the mobile phone.

The handset may also include at least one sensor 550, such as a light sensor, motion sensor, and other sensors. Specifically, the light sensor can include an ambient light sensor and a proximity sensor, wherein the ambient light sensor can adjust the brightness of the display panel 541 according to the brightness of the ambient light, and the proximity sensor can turn off the display panel 541 and/or when the mobile phone is moved to the ear. or backlight. As a kind of motion sensor, the accelerometer sensor can detect the magnitude of acceleration in various directions (generally three axes), and can detect the magnitude and direction of gravity when it is stationary, and can be used to identify the application of mobile phone posture (such as horizontal and vertical screen switching, related Games, magnetometer attitude calibration), vibration recognition related functions (such as pedometer, tap), etc.; as for other sensors such as gyroscope, barometer, hygrometer, thermometer, infrared sensor, etc. repeat.

The audio circuit 560, the speaker 561, and the microphone 562 can provide an audio interface between the user and the mobile phone. The audio circuit 560 can transmit the electrical signal converted from the received audio data to the loudspeaker 561, and the loudspeaker 561 converts it into an audio signal output; After being received, it is converted into audio data, and then the audio data is processed by the output processor 580, and then sent to another mobile phone through the RF circuit 510, or the audio data is output to the memory 520 for further processing.

WiFi is a short-distance wireless transmission technology. The mobile phone can help users send and receive emails, browse web pages, and access streaming media through the WiFi module 570, which provides users with wireless broadband Internet access. Although Fig. 5 shows a WiFi module 570, it can be understood that it is not an essential component of the mobile phone, and can be completely omitted as required without changing the essence of the invention.

The processor 580 is the control center of the mobile phone. It uses various interfaces and lines to connect various parts of the entire mobile phone. By running or executing software programs and/or modules stored in the memory 520, and calling data stored in the memory 520, execution Various functions and processing data of the mobile phone, so as to monitor the mobile phone as a whole. Optionally, the processor 580 may include one or more processing units; preferably, the processor 580 may integrate an application processor and a modem processor, wherein the application processor mainly processes operating systems, user interfaces, and application programs, etc. , the modem processor mainly handles wireless communications. It can be understood that the foregoing modem processor may not be integrated into the processor 580 .

The mobile phone also includes a power supply 590 (such as a battery) for supplying power to each component. Preferably, the power supply can be logically connected to the processor 580 through the power management system, so as to realize functions such as managing charging, discharging, and power consumption management through the power management system.

Although not shown, the mobile phone may also include a camera, a Bluetooth module, etc., which will not be repeated here.

In the foregoing embodiments, the method flow of each step can be realized based on the structure of the terminal. Wherein the sensor 550 or the touch panel 531 can be used as a fingerprint identification module.

An embodiment of the present invention also provides a computer storage medium, wherein the computer storage medium can store a program, and when the program is executed, some or all steps of any fingerprint unlocking method described in the above method embodiments are included.

Although the present invention has been described in conjunction with various embodiments herein, in the process of implementing the claimed invention, those skilled in the art can understand and Other variations of the disclosed embodiments are implemented. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that these measures cannot be combined to advantage.

Those skilled in the art should understand that the embodiments of the present invention may be provided as methods, devices (devices), or computer program products. Accordingly, the present invention can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein. The computer program is stored/distributed on suitable media, supplied with or as part of other hardware, and may also take other forms of distribution, such as via the Internet or other wired or wireless telecommunication systems.

The present invention is described with reference to flowcharts and/or block diagrams of methods, apparatus (device) and computer program products according to embodiments of the present invention. It should be understood that each procedure and/or block in the flowchart and/or block diagram, and a combination of procedures and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions may be provided to a general purpose computer, special purpose computer, embedded processor, or processor of other programmable data processing equipment to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing equipment produce a An apparatus for realizing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions The device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby The instructions provide steps for implementing the functions specified in the flow chart or blocks of the flowchart and/or the block or blocks of the block diagrams.

Although the invention has been described in conjunction with specific features and embodiments thereof, it will be apparent that various modifications and combinations can be made therein without departing from the spirit and scope of the invention. Accordingly, the specification and drawings are merely illustrative of the invention as defined by the appended claims and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the invention. Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and equivalent technologies thereof, the present invention also intends to include these modifications and variations.

Claims (13)

1. a unlocked by fingerprint method, it is characterised in that including:

During user presses fingerprint recognition module, described fingerprint recognition module is utilized to split in advance parallel N number of pickup area in each pickup area gather capacitance, described N is more than 1 integer；

The capacitance that each pickup area in described N number of pickup area is gathered is converted into described N number of finger Print image；

Choose in described N number of fingerprint image a top-quality fingerprint image as target fingerprint image；

Described target fingerprint image is mated with preset fingerprint template；

When described target fingerprint image is with described preset fingerprint template matching success, terminal is unlocked.

Method the most according to claim 1, it is characterised in that described in choose described N number of fingerprint image In a top-quality fingerprint image as target fingerprint image, including:

Extract the characteristic point of described N number of fingerprint image respectively；

Using fingerprint images most for characteristic point in described N number of fingerprint image as target fingerprint image.

Method the most according to claim 2, it is characterised in that described in choose described N number of fingerprint image In a top-quality fingerprint image as target fingerprint image after, described method also includes:

Judge whether the feature point number of described target fingerprint image is in preset range；

When described feature point number exceedes preset range, perform described by described target fingerprint image with preset Fingerprint template mates；

When described feature point number is less than described preset range, prompting user re-presses described fingerprint recognition Module；

When described feature point number is in described preset range, described target fingerprint image is carried out image increasing Strength is managed.

4. according to the method described in any one of claims 1 to 3, it is characterised in that described by described N number of The capacitance that each pickup area in pickup area is gathered is converted into described N number of fingerprint image, including:

Respectively the capacitance that each pickup area in described N number of pickup area is gathered is carried out at binaryzation Reason, obtains described N group binaryzation capacitance；

Described N group binaryzation capacitance is converted into described N number of fingerprint image.

Method the most according to claim 1, it is characterised in that described in choose described N number of fingerprint image In a top-quality fingerprint image as target fingerprint image, including:

Respectively described N number of fingerprint image is carried out image quality evaluation, obtain described N number of image quality evaluation Value；

Using fingerprint image corresponding for the maximum image quality evaluation value in described N number of image quality evaluation values as Target fingerprint image.

Method the most according to claim 5, it is characterised in that described respectively to described N number of fingerprint image As carrying out image quality evaluation, obtain described N number of image quality evaluation values, including:

Use the multiple evaluation indexes preset that described fingerprint image i is carried out image quality evaluation, obtain described many Individual evaluation of estimate, described fingerprint image i is in described N number of fingerprint image；

Determine described according to the default weight that the plurality of evaluation of estimate and described default multiple evaluation indexes are corresponding The image quality evaluation values of fingerprint image i.

7. a terminal, it is characterised in that including:

Collecting unit, for during user presses fingerprint recognition module, utilizes described fingerprint to know parallel Each pickup area in N number of pickup area that other module is split in advance gathers capacitance, and described N is for being more than 1 integer；

Conversion unit, for turning the capacitance that each pickup area in described N number of pickup area is gathered Turn to described N number of fingerprint image；

Choose unit, be used for choosing in described N number of fingerprint image a top-quality fingerprint image as mesh Mark fingerprint image；

Matching unit, for mating described target fingerprint image with preset fingerprint template；

Solve lock unit, for when described target fingerprint image is with described preset fingerprint template matching success, right Terminal is unlocked.

Terminal the most according to claim 7, it is characterised in that described in choose unit and include:

Extraction module, for extracting the characteristic point of described N number of fingerprint image respectively；

First determines module, is used for fingerprint images most for characteristic point in described N number of fingerprint image as mesh Mark fingerprint image.

Terminal the most according to claim 8, it is characterised in that described terminal also includes:

Judging unit, for choosing in N number of fingerprint image described in unit selection top-quality one described After fingerprint image is as target fingerprint image, it is judged that whether the feature point number of described target fingerprint image is located In preset range；

Judged result at described judging unit is described feature point number when exceeding preset range, by described Join unit to be mated with preset fingerprint template by described target fingerprint image；

Tip element, being used in the judged result of described judging unit is that described feature point number is less than described pre- If during scope, prompting user re-presses described fingerprint recognition module；

First processing unit, is that described feature point number is in institute for the judged result at described judging unit When stating preset range, described target fingerprint image is carried out image enhancement processing.

10. according to the terminal described in any one of claim 7 to 9, it is characterised in that described conversion unit Including:

Second processing module, for gathered each pickup area in described N number of pickup area respectively Capacitance carries out binary conversion treatment, obtains described N group binaryzation capacitance；

Conversion module, for being converted into described N number of fingerprint image by described N group binaryzation capacitance.

11. terminals according to claim 7, it is characterised in that described in choose unit and include:

First evaluation module, for respectively described N number of fingerprint image being carried out image quality evaluation, obtains institute State N number of image quality evaluation values；

Second determines module, for by the maximum image quality evaluation value in described N number of image quality evaluation values Corresponding fingerprint image is as target fingerprint image.

12. terminals according to claim 11, it is characterised in that described first evaluation module includes:

Second evaluation module, for using default multiple evaluation indexes that described fingerprint image i is carried out figure picture element Amount is evaluated, and obtains the plurality of evaluation of estimate, and described fingerprint image i is in described N number of fingerprint image；

3rd determines module, for corresponding according to the plurality of evaluation of estimate and described default multiple evaluation indexes Default weight determine the image quality evaluation values of described fingerprint image i.

13. 1 kinds of terminals, it is characterised in that including:

Processor and memorizer；Wherein, described processor is by calling the code in described memorizer or instruction To perform the method as described in claim 1-6 any one.