TW201915806A - Fingerprint recognition method and electronic device using the same - Google Patents

Abstract

A fingerprint recognition method adapted to an electronic device is provided. The electronic device includes a processing unit and a fingerprint sensor. The fingerprint recognition method includes steps of: obtaining a plurality of swiping frames; extracting a plurality of feature points respectively from the plurality of swiping frames to generate a plurality of pre-registered fingerprint datasets accordingly; merging the plurality of pre-registered fingerprint datasets; generating a registration template according to the merged pre-registered fingerprint datasets; obtaining a pressing frame; extracting a plurality of feature points from the pressing frame to generate a verifying fingerprint dataset; and comparing the verifying fingerprint dataset with the registration template, so as to determine whether the verifying fingerprint dataset matches the registration template. The above electronic device is also provided.

Description

Fingerprint identification method and electronic device using fingerprint identification method

The present invention relates to fingerprint recognition technology, and more specifically, to a fingerprint recognition method and an electronic device using the fingerprint recognition method.

In recent years, biometric technology has developed rapidly. Because security codes and access cards are easily stolen or lost, more attention is paid to fingerprint recognition technology. Fingerprints are unique and unchanged, and each person has multiple fingers for identification. In addition, fingerprints can be easily obtained using a fingerprint sensor. Therefore, fingerprint recognition can improve security and convenience, and can better protect financial security and confidential information.

In a conventional method of fingerprint recognition, the user presses his finger on the fingerprint sensor several times to generate multiple registered fingerprint data sets, and then presses his finger on the fingerprint sensor again for verification. However, for a fingerprint sensor with a small sensing area, in order to obtain enough registered fingerprint data sets for identification, the user needs to press multiple times to complete the fingerprint registration process.

In another conventional method of fingerprint recognition, the user swipes his finger on the fingerprint sensor of the electronic device, and when the user swipes the finger on the fingerprint sensor, the electronic device will obtain multiple frames. The electronic device then combines multiple frames to generate a registered fingerprint data set. In order to obtain enough registered fingerprint data, the user may be required to swipe the finger on the fingerprint sensor several times. Therefore, multiple registered fingerprint data sets will be generated accordingly. In order to verify, the user must swipe the finger on the fingerprint sensor again, and the electronic device including the fingerprint sensor will generate the verification fingerprint data set accordingly. The electronic device compares the verification fingerprint data set with the registered fingerprint data set, and then decides whether the verification fingerprint data set passes the verification.

The invention relates to a fingerprint recognition method and an electronic device using the fingerprint recognition method, which can obtain a registration template by requiring a user to swipe their finger on the fingerprint sensor of the electronic device, and by requiring the user to press the finger on The fingerprint sensor is used to obtain the verification fingerprint information, and the verification fingerprint information is compared with the registration template for identification.

The fingerprint identification method of the present invention is suitable for electronic devices. The electronic device includes a processing unit and a fingerprint sensor. The fingerprint recognition method includes the following steps: acquiring multiple sliding frames by the fingerprint sensor; extracting multiple feature points from the multiple sliding frames, respectively, to generate multiple pre-registrations by the processing unit accordingly Fingerprint data set; the processing unit merges the plurality of pre-registered fingerprint data sets; the processing unit generates a registration template based on the merged pre-registered fingerprint data set; obtains the pressing by the fingerprint sensor A frame; extracting a plurality of feature points from the pressing frame to generate a verification fingerprint data set by the processing unit; and comparing the verification fingerprint data set and the registration template by the processing unit, to It is judged whether the verification fingerprint data set matches the registration template.

The electronic device of the present invention includes a fingerprint sensor and a processing unit. The fingerprint sensor is used to obtain a plurality of sliding frames and pressing frames. The processing unit is coupled to the fingerprint sensor and used to receive a plurality of sliding frame and pressing frame. The processing unit extracts a plurality of feature points from the plurality of sliding frames, respectively, to correspondingly generate a plurality of pre-registered fingerprint data sets. The processing unit merges multiple pre-registered fingerprint data sets, and generates a registration template based on the merged pre-registered fingerprint data sets. The processing unit extracts a plurality of feature points from the pressing frame to generate a verification fingerprint data set, and compares the verification fingerprint data set with the registration template to determine whether the verification fingerprint data set matches the registration template.

In order to make the above-mentioned features and advantages of the present invention more obvious and understandable, the embodiments are specifically described below in conjunction with the accompanying drawings for detailed description as follows.

In order to make the content of the present invention easier to understand, the following specific embodiments are taken as examples on which the present invention can indeed be implemented. In addition, wherever possible, elements / components / steps with the same reference numerals in the drawings and embodiments represent the same or similar components.

FIG. 1 is an electronic device 100 according to an embodiment of the invention. As shown in FIG. 1, the electronic device 100 includes a fingerprint sensor 110, a processing unit 120 and a storage unit 130. Figure 1 shows only a simplified block diagram of components related to the present invention. However, the present invention should not be limited to what is shown in FIG.

In the embodiment of the present invention, the fingerprint sensor 110 has a small sensing area of n × m. For example, the sensing area of the fingerprint sensor 110 may be 10 mm × 4 mm, 6 mm × 6 mm, or 4 mm × 3.2 mm. In other words, the sensing area of the fingerprint sensor 110 is small, and when the user swipes his finger on the fingerprint sensor or presses his finger on the fingerprint sensor, The area of the frame sensed by the fingerprint sensor 110 will also be smaller because the area of the frame is equal to the sensing area of the fingerprint sensor 110. The frames are small, so each frame may include very few detail points (for example, there may be less than 5 detail points).

In an embodiment of the present invention, when registering a fingerprint, the user can swipe his finger on the fingerprint sensor 110 once or several times (for example, 2 to 4 times). After each time the user's finger slides on the fingerprint sensor 110, the electronic device 100 will obtain a plurality of sliding frames.

2 is a schematic diagram of a fingerprint registration procedure according to an embodiment of the invention. During the registration process, the user is required to swipe their finger on the fingerprint sensor 110. Referring to FIGS. 1 and 2, in an embodiment of the present invention, when a user swipes a finger on the fingerprint sensor 110, the fingerprint sensor 110 senses and acquires multiple sliding frames 710_1, 710_2, 710_3 ~ 710_N. N is a positive integer and greater than 1. The processing unit 120 then performs a distortion correction operation on the sliding frame 710_1, 710_2, 710_3 ~ 710_N to generate a plurality of correction frames 720_1, 720_2, 720_3 ~ 720_N. Specifically, the distortion correction operation can reduce the distortion of the image caused by the sliding brush.

The processing unit 120 then extracts a plurality of feature points (ie, minutiae points) 721 from the calibration frames 720_1, 720_2, 720_3 ~ 720_N, respectively, to generate a plurality of pre-registered fingerprint datasets 722_1, 722_2, 722_3 ～ 722_N. In the embodiment of the present invention, the processing unit 120 may combine and merge pre-registered fingerprint data sets 722_1, 722_2, 722_3 ~ 722_N, and when the processing unit 120 judges that the pre-registered fingerprint data sets 722_1, 722_2, 722_3 ~ included in the merger are included When the number of feature points in 722_N, or the amount, area or height of the merged pre-registered fingerprint data set is greater than a predetermined registration threshold, the processing unit 120 generates a registration template (template) 730 and stores the registration template 730 in the storage unit 130. The processing unit 120 will combine according to the repeatability of the multiple feature points 721 in the pre-registered fingerprint data sets 722_1, 722_2, 722_3 ~ 722_N and the overlap between the pre-registered fingerprint data sets 722_1, 722_2, 722_3 ~ 722_N And merge.

Specifically, when a user swipes a finger on the fingerprint sensor 110, a plurality of sliding frames 710_1, 710_2, 710_3 to 710_N will be obtained in sequence. That is, the processing unit 120 will receive the sliding frame one by one. After the processing unit 120 receives the first sliding frame 710_1, the processing unit 120 will perform a distortion correction operation on the first sliding frame 710_1 to generate a first correction frame 720_1. Next, the processing unit 120 extracts a plurality of feature points 721 from the first correction frame 720_1 to generate a first pre-registered fingerprint data set 722_1.

After that, the processing unit 120 will receive the second sliding frame 710_2, perform a distortion correction operation on the second sliding frame 710_2 to generate a second correction frame 720_2, and extract multiple features from the second correction frame 720_2 Point 721 to generate a second pre-registered fingerprint data set 722_2. Next, the processing unit 120 combines and merges the first pre-registered fingerprint data set 722_1 and the second pre-registered fingerprint data set 722_2 to generate a pre-enrolled data set 724. The processing unit 120 will continue to receive the next sliding frame in sequence, correspondingly generate the correction frame and the pre-registered fingerprint data set, and then combine and merge the next pre-registered fingerprint data set into the pre-registered data set 724 Until the number of feature points included in the merged pre-registered fingerprint data set (ie, pre-registered data set 724) or the data amount, area, or height of the merged pre-registered fingerprint data set is greater than the predetermined registration threshold . When the number of feature points included in the merged pre-registered fingerprint data set (ie, pre-registered data set 724) or the data amount, area, or height of the merged pre-registered fingerprint data set is greater than a predetermined registration threshold, It means the registration process is completed because enough fingerprint information has been obtained for fingerprint identification. Therefore, the processing unit 120 stores the merged pre-registered fingerprint data set (ie, the pre-registered data set 724) as the registration template 730 in the storage unit 130.

FIG. 3 is a flowchart 800 of a fingerprint registration method according to an embodiment of the invention. Referring to FIGS. 1, 2 and 3, when a user swipes a finger on the fingerprint sensor 110, the fingerprint sensor 110 will sequentially sense and obtain multiple sliding frame 710_1, 710_2, 710_3 ~ 710_N . In step S810, the processing unit 120 receives a sliding frame (that is, one of the sliding frames 710_1, 710_2, and 710_3 to 710_N). In step S820, the processing unit 120 performs a distortion correction operation on this sliding frame to generate a correction frame (ie, one of the correction frames 720_1, 720_2, 720_3 ~ 720_N). The details of the distortion correction operation will be discussed below. In step S830, the processing unit 120 extracts a plurality of feature points 721 from a correction frame to obtain a pre-registered fingerprint data set (ie, one of the pre-registered fingerprint data sets 722_1, 722_2, 722_3 ~ 722_N) . In step S831, the processing unit 120 determines whether the generated pre-registered fingerprint is the first pre-registered fingerprint data set. If not, step S840 will be executed. If yes, step S842 will be executed. In step S842, the processing unit 120 generates a pre-registered data set 724 based on the first pre-registered fingerprint data set 722_1. Next, the processing unit 120 executes step S810 to receive the second sliding frame 710_2.

In step S840, the processing unit 120 merges the pre-registered fingerprint data set into the pre-register according to the repeatability of the plurality of feature points 721 and the overlap between the pre-registered fingerprint data set and the pre-registered data set 724 In data set 724. In step S850, the processing unit 120 is based on the number of multiple feature points 721 included in the merged pre-registered fingerprint data set (ie, the pre-registered data set 724), or the data of the merged pre-registered fingerprint data set The amount, area or height determines whether the registration template 730 is generated. Specifically, if the processing unit 120 determines the number of feature points included in the merged pre-registered fingerprint data set (ie, the pre-registered data set 724), or the data amount and area of the merged pre-registered fingerprint data set Or the height is greater than the predetermined registration threshold, the processing unit 120 will execute step S860. In S860, the processing unit 120 generates and stores the registration template 730 according to the merged pre-registered fingerprint data set (ie, the pre-registered data set 724). In other words, the previously registered material set 724 is stored as the registration template 730. Since enough fingerprint information has been obtained for fingerprint identification, the registration process will end.

If the processing unit 120 determines that the number of feature points included in the merged pre-registered fingerprint data set 722, or the data amount, area or height of the merged pre-registered fingerprint data set 722 is not greater than a predetermined registration threshold, the processing unit 120 will execute step S810 to receive the next sliding frame. If the registration process is not completed after the user swipes the finger for the first time, the user will be required to swipe the finger on the fingerprint sensor 110 again.

4 is a schematic diagram of a distortion correction operation according to an embodiment of the invention. Referring to FIGS. 1 and 4, in the embodiment of the present invention, in the registration process, the user is required to swipe the finger on the fingerprint sensor 110, and the fingerprint sensor 110 will sequentially sense and acquire multiple Swipe the frame. The processing unit 120 will then perform a distortion correction operation on each sliding frame in sequence. For example, a sliding brush frame 910 is obtained. First, the processing unit 120 vertically splits the sliding frame 910 into a plurality of vertical parts 910_1, 910_2 ~ 910_M. M is a positive integer and greater than 1. Next, the processing unit 120 calculates the vertical parts 910_1, 910_2 ~ 910_M using a Gaussian function, that is, the Gaussianized vertical parts 910_1, 910_2 ~ 910_M. The Gaussian function can be represented by a distribution curve (ie, Gaussian curve) 911, which will be discussed in detail below. After the Gaussianization, each vertical part 910_1, 910_2 ~ 910_M will be aligned and aligned with the adjacent vertical part according to the Gaussian curve 911. Finally, the processing unit 120 generates the correction frame 920 accordingly.

In addition, in the embodiment of the present invention, the Gaussian curve 911 is predetermined according to relevant experience, experiments, and / or statistics in the field of fingerprint recognition technology. For example, please refer to FIG. 5, which is a schematic diagram of Gaussian curves 1010, 1020, and 1030 according to an embodiment of the present invention. In an embodiment of the present invention, the above-mentioned distribution curve 911 may be any one of Gaussian curves 1010, 1020, and 1030 as shown in FIG. The variances (Variance, VAR) of Gaussian curves 1010, 1020, and 1030 are 5, 6, and 8, respectively, but the invention is not limited thereto. In the preferred embodiment, the variance is in the range of 5 to 8.

6 is a schematic diagram of a fingerprint verification procedure according to an embodiment of the invention. In the verification procedure, the user is required to press his finger on the fingerprint sensor 110. Referring to FIGS. 1 and 6, in an embodiment of the present invention, when a user presses a finger on the fingerprint sensor 110, the fingerprint sensor 110 senses and obtains the pressing frame 1110. The processing unit 120 extracts a plurality of feature points (ie, minutiae points) 1111 from the pressing frame 1110 to generate a verification fingerprint data set 1120. In the embodiment of the present invention, the processing unit 120 compares the verification fingerprint data set 1120 with the registration template 730 to determine whether the verification fingerprint data set 1120 matches the registration template 730. When the verification fingerprint data set 1120 matches the registration template 730, the processing unit 120 determines that the verification fingerprint data set 1120 passes verification. Specifically, since the registration template 730 is formed by combining multiple fingerprint data sets, it has a larger area than the verified fingerprint data set 1120, that is, the verified fingerprint data set 1120 will be registered with A part of the template 730 matches.

In addition, the processing unit 120 determines that the part of the registration template 730 that matches the verified fingerprint data set 1120 is generated from sliding the frame or pressing the frame. If this part of the registration template 730 is generated from the sliding frame, it means that this part is included in the registration template 730 generated in the registration process from the beginning. Next, the processing unit 120 will update the registration template 730 using the verified fingerprint data set 1120 that has been verified. In other words, this part of the registration template 730 will be replaced and updated by the verification fingerprint data set 1120 that has been verified. After the update, as shown in FIG. 6, the area of the registered template 730 may be enlarged (the striped portion in the template 730 is the enlarged portion), because the area of the verified fingerprint data set 1120 may be larger than the registration The area of the matching portion of the template 730. On the other hand, if this part of the registration template 730 is generated from pressing the frame, it means that this part was merged into the registration template 730 after the previous successful verification. Then, the processing unit 120 will not update the registration template 730 using the verified fingerprint data set 1120 that has been verified. As shown in FIG. 6, after several successful verifications, the area of the registration template 730 will be enlarged (the striped part in the registration template 730 represents the amplified part).

7 is a flowchart 1200 of a fingerprint verification method according to an embodiment of the invention. In order to perform fingerprint verification, the user will be required to press his finger on the fingerprint sensor 110. Referring to FIGS. 1, 6 and 7, in step S1210, when the user places a finger on the fingerprint sensor 110, the fingerprint sensor 110 senses and obtains the pressing frame 1110. In step S1220, the processing unit 120 analyzes the press frame 1110 to extract a plurality of feature points 1111 from the press frame 1110, and generates a verification fingerprint data set 1120 (ie, press the fingerprint data set) accordingly.

In step S1230, the processing unit 120 determines whether the verification fingerprint data set 1120 matches the registration template 730. In the embodiment of the present invention, the registration template 730 is stored in the storage unit 130. More specifically, the processing unit 120 compares the feature points included in the verification fingerprint data set 1120 with the feature points included in the registration template 730 to obtain similarity. When the similarity between the verification fingerprint data set 1120 and a part of the registration template 730 is greater than a predetermined similarity threshold, it means that the verification fingerprint data set 1120 and the registration template 730 match. When the verification fingerprint data set 1120 matches the registration template 730, the processing unit 120 determines that the verification fingerprint data set 1120 passes the verification and the user is a legally authorized user. As mentioned above, the verified fingerprint data set 1120 that matches will match a part of the registration template 730, because the registration template 730 is formed by combining multiple fingerprint data sets, so it has more than the verified fingerprint data set 1120 that is verified Large area.

In step S1235, the processing unit 120 determines that this part of the registration template 730 that matches the verified fingerprint data set 1120 is generated from sliding the frame or pressing the frame. If this part of the registration template 730 is generated from the sliding frame, it means that this part is included in the registration template 730 generated in the registration process from the beginning. Next, step S1240 will be executed. In step S1240, the processing unit 120 updates the registration template 730 with the verified fingerprint data set 1120 that has been verified. In other words, this part of the registration template 730 will be replaced by the verification fingerprint data set 1120 that has been verified and updated. As mentioned above, after the update, the area of the registration template 730 may be enlarged because the area of the verification fingerprint data set 1120 that passes verification may be larger than the area of the matching portion of the registration template 730.

On the other hand, if this part of the registration template 730 is generated from pressing the frame, it means that this part was merged into the registration template 730 after the previous successful verification. Then, the processing unit 120 will not update the registration template 730 using the verified fingerprint data set 1120 that has been verified.

Compared with the conventional fingerprint recognition method, according to the fingerprint recognition method of the present invention, the user can register his fingerprint by swiping his finger on the fingerprint sensor, and the user can press the finger on the fingerprint sensor To identify and verify. By swiping a finger of a user once, the fingerprint sensor can sense multiple sliding frames. The present invention may require the user to swipe the finger more than once, but usually does not require the user to swipe the finger too many times. In a preferred embodiment, after the user swipes the finger one to three times, the present invention can obtain sufficient fingerprint information to complete the registration process. Therefore, the present invention can improve the efficiency of the registration procedure. In addition, in the registration procedure, the present invention uses a Gaussian curve to correct the sliding frame, which can reduce the image distortion caused by the sliding brush.

In addition, after several successful verifications, the registration template will be replaced by the verified press data set and updated. When the registered template is completely updated by the verified press data set, the image distortion caused by the sliding brush will be completely removed. Therefore, the accuracy of fingerprint recognition can be improved. In summary, the present invention aims to provide an efficient registration experience by requiring users to swipe their fingers, and to provide convenient verification by requiring users to press their fingers. At the same time, the efficiency and accuracy of fingerprint recognition will also be improved.

The steps of the method described in connection with the aspects disclosed herein may be implemented directly in hardware, in a software module executed by a processor, or in a combination of both. Software modules (eg, containing executable instructions and related data) and other data can reside in data memory, such as RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hardware Discs, removable disks, CD-ROMs, or any other form of computer-readable storage media known in the art. The sample storage medium may be coupled to a machine such as a computer / processor (for convenience, the machine may be referred to herein as a "processor") so that the processor can read information from the storage medium (eg, code ) And write information to storage media. The example storage medium may be integrated with the processor. The processor and the storage medium may reside in the ASIC. The ASIC can reside in the user equipment. Alternatively, the processor and the storage medium may reside as discrete components in the user equipment. Furthermore, in some aspects, any suitable computer program product may include a computer-readable medium that includes code related to one or more of the various aspects of the invention. In some aspects, the computer program product may include packaging materials.

Reference throughout this specification to "one embodiment" or "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment is included in at least one embodiment of the present invention, but does not mean that it exists in every implementation Example. Therefore, the appearance of the phrases "in one embodiment" or "in this embodiment" in different places throughout this specification does not necessarily refer to the same embodiment of the invention.

Although the present invention has been disclosed as above with examples, it is not intended to limit the present invention. Any person with ordinary knowledge in the technical field can make some changes and modifications without departing from the spirit and scope of the present invention. The scope of protection of the present invention shall be subject to the scope defined in the appended patent application.

100‧‧‧Electronic device

110‧‧‧Fingerprint sensor

120‧‧‧Processing unit

130‧‧‧storage unit

800, 1200‧‧‧ Flowchart

710_1, 710_2, 710_3 ～ 710_N, 910‧‧‧swipe frame

720_1, 720_2, 720_3 ～ 720_N‧‧‧‧ correction frame

721, 1111‧‧‧ feature points

722_1, 722_2, 722_3 ～ 722_N‧‧‧ Fingerprint data set

724‧‧‧ pre-registered data set

730‧‧‧ registered template

910_1, 910_2 ～ 910_M ‧‧‧ vertical part

911‧‧‧distribution curve

920‧‧‧ correction frame

1010, 1020, 1030 ‧‧‧ Gaussian curve

1110‧‧‧Press the frame

1120‧‧‧Verification fingerprint data set

S810 ～ S860 、 S1210 ～ S1240‧‧‧Step

FIG. 1 is an electronic device 100 according to an embodiment of the invention. 2 is a schematic diagram of a fingerprint registration procedure according to an embodiment of the invention. FIG. 3 is a flowchart 800 of a fingerprint registration method according to an embodiment of the invention. 4 is a schematic diagram of a distortion correction operation according to an embodiment of the invention. FIG. 5 is a schematic diagram of Gaussian curves 1010, 1020, and 1030 according to an embodiment of the present invention. 6 is a schematic diagram of a fingerprint verification procedure according to an embodiment of the invention. 7 is a flowchart 1200 of a fingerprint verification method according to an embodiment of the invention.

Claims (18)

A fingerprint recognition method, which is suitable for an electronic device, and the electronic device includes a processing unit and a fingerprint sensor, wherein the fingerprint recognition method includes: obtaining a plurality of sliding brush pictures by the fingerprint sensor Frame; the processing unit extracts a plurality of feature points from the plurality of sliding frames, respectively, to correspondingly generate a plurality of pre-registered fingerprint data sets; the processing unit merges the plurality of pre-registered A registered fingerprint data set; a registration template is generated by the processing unit based on the merged pre-registered fingerprint data set; a pressing frame is obtained by the fingerprint sensor; The pressing frame extracts a plurality of feature points to generate a verification fingerprint data set; and the processing unit compares the verification fingerprint data set and the registration template to determine whether the verification fingerprint data set is Said registration template matching. The fingerprint recognition method as described in Item 1 of the patent application scope further includes: calibrating the plurality of sliding frame according to a distribution curve by the processing unit to generate a plurality of correction frames. The fingerprint recognition method according to item 2 of the patent application scope, wherein the step of generating the plurality of correction frames by the processing unit correcting the plurality of sliding frames according to the distribution curve includes: Vertically splitting each of the plurality of sliding brush frames into a plurality of vertical parts; and arranging and aligning each of the plurality of vertical parts and its adjacent vertical parts according to the distribution curve. The fingerprint identification method as described in item 2 of the patent application range, wherein the distribution curve is a Gaussian curve, and the variance of the Gaussian curve is in the range of 5-8. The fingerprint identification method according to item 1 of the patent application scope, wherein the step of merging the plurality of pre-registered fingerprint data sets by the processing unit includes: according to a repeatability of the plurality of feature points and The plurality of pre-registered fingerprint data sets are merged to overlap the plurality of pre-registered fingerprint data sets. The fingerprint identification method as described in item 1 of the patent application scope, wherein before the step of generating the registration template by the processing unit, the fingerprint identification method further includes: judging the pre-registration included in the merger Whether a number of the feature points in the fingerprint data set of the data set, or a data amount, area or height of the merged pre-registered fingerprint data set is greater than a predetermined registration threshold. The fingerprint identification method according to item 1 of the patent application scope, wherein the step of comparing the verification fingerprint data set with the registration template to determine whether the verification fingerprint data set matches the registration template includes: comparing The feature points of the verification fingerprint data set and the feature points of the registration template to obtain a similarity; and if the similarity is higher than a predetermined similarity threshold, determining the verification fingerprint data The set matches the registration template. The fingerprint identification method as described in item 1 of the patent application scope further includes: when the verification fingerprint data set matches the registration template, the processing unit determines that the verification fingerprint data set matches the verification fingerprint data set. Whether a part of the registration template is generated from one of the plurality of sliding brush frames; and if the part of the registration template matching the verification fingerprint data set is from the plurality of sliding brush frames One is generated, and the registration template is updated by the processing unit using the verification fingerprint data set. The fingerprint identification method according to item 8 of the patent application scope, wherein the step of updating the registration template by the processing unit includes: updating the registration template by using the verification fingerprint data set by the processing unit The part of the, wherein if the area of the verification fingerprint data set is larger than the area of the part of the registration template, the total area of the registration template will be expanded after the update. An electronic device includes: a fingerprint sensor for acquiring a plurality of sliding brush frames and a pressing frame; and a processing unit coupled to the fingerprint sensor and for receiving the plurality of sliding brushes A frame and the pressing frame, wherein the processing unit respectively extracts a plurality of feature points from the plurality of sliding frames to correspondingly generate a plurality of pre-registered fingerprint data sets, and merges the plurality of pre-registers Fingerprint data set, and generating a registration template based on the merged pre-registered fingerprint data set, wherein the processing unit extracts a plurality of feature points from the pressing frame to generate a verification fingerprint data set, and the The processing unit compares the verification fingerprint data set with the registration template to determine whether the verification fingerprint data set matches the registration template. The electronic device as claimed in item 10 of the patent application range, wherein the processing unit corrects the plurality of sliding frame according to a distribution curve to generate a plurality of correction frames. The electronic device as described in item 11 of the patent application range, wherein the processing unit vertically splits each of the plurality of sliding brush frames into multiple vertical parts, and the processing unit is based on the distribution curve Arranging and aligning each of the plurality of vertical portions and its adjacent vertical portion to obtain the plurality of correction frames. The electronic device as described in item 11 of the patent application range, wherein the distribution curve is a Gaussian curve, and the variance of the Gaussian curve is in the range of 5-8. The electronic device as described in item 10 of the patent application range, wherein the processing unit merges the said based on a repeatability of the plurality of feature points and an overlap between the plurality of pre-registered fingerprint data sets Multiple pre-registered fingerprint data sets. The electronic device according to item 10 of the patent application scope, wherein before the processing unit generates the registration template, the processing unit judges the number of the feature points included in the merged pre-registered fingerprint data set , Or whether a data amount, an area, or a height of the merged pre-registered fingerprint data set is greater than a predetermined registration threshold. The electronic device according to item 10 of the patent application scope, wherein the processing unit compares the feature points of the verification fingerprint data set with the feature points of the registration template to obtain a similarity, and if If the similarity is higher than a predetermined similarity threshold, the processing unit determines that the verification fingerprint data set matches the registration template. The electronic device according to item 10 of the patent application scope, wherein when the verification fingerprint data set matches the registration template, the processing unit determines whether a part of the registration template matching the verification fingerprint data set Generated from one of the plurality of slider frames, and if the portion of the registration template matching the verification fingerprint data set is generated from the one of the plurality of slider frames, then The processing unit updates the registration template using the verification fingerprint data set. The electronic device according to item 17 of the patent application range, wherein the processing unit updates the part of the registration template using the verification fingerprint data set, and if the area of the verification fingerprint data set is larger than the registration template The area of the part, the total area of the registered template will be expanded after the update.