Fingerprint unlocking method and device, electronic equipment and storage medium

Abstract

This application discloses a fingerprint unlocking method, apparatus, electronic device, and storage medium, belonging to the field of electronic device technology. The method includes: acquiring a user's first fingerprint information; determining the similarity between the first fingerprint information and second fingerprint information, wherein the second fingerprint information is pre-stored user fingerprint information; if the similarity between the first fingerprint information and the pre-stored second fingerprint information is less than a first threshold, comparing the first fingerprint information with a training fingerprint, wherein the training fingerprint is determined based on multiple fingerprints of the user previously acquired that meet preset conditions; and unlocking the electronic device if the similarity between the first fingerprint information and the training fingerprint is greater than a second threshold.

Description

Technical Field

[0001] This application belongs to the field of electronic equipment technology, specifically relating to a fingerprint unlocking method, device, electronic device, and storage medium. Background Technology

[0002] With the development of biometric technology, fingerprint recognition technology has been widely used in mobile phones and other electronic devices. Users are increasingly demanding fast and accurate fingerprint recognition technology, especially the ability to unlock fingerprints accurately in various harsh environments.

[0003] External factors can interfere with the effectiveness of fingerprint unlocking on electronic devices, preventing successful unlocking and thus affecting the accuracy of fingerprint unlocking. For example, when fingers are immersed in water for a long time, noticeable wrinkles often form on the surface of the fingers, a phenomenon known as "water wrinkling," which can severely affect the accuracy of fingerprint unlocking. Summary of the Invention

[0004] The purpose of this application is to provide a fingerprint unlocking method, apparatus, electronic device, and storage medium to improve the accuracy of fingerprint unlocking.

[0005] In a first aspect, embodiments of this application provide a fingerprint unlocking method, the method comprising:

[0006] Obtain the user's first fingerprint information;

[0007] Determine the similarity between the first fingerprint information and the second fingerprint information, wherein the second fingerprint information is pre-stored user fingerprint information;

[0008] If the similarity between the first fingerprint information and the second fingerprint information is less than a first threshold, the first fingerprint information is compared with the training fingerprint, which is determined based on multiple fingerprint information of the user that meet preset conditions previously obtained from the first fingerprint information.

[0009] If the similarity between the first fingerprint information and the training fingerprint is determined to be greater than a second threshold, the electronic device is unlocked.

[0010] Secondly, embodiments of this application provide a fingerprint unlocking device, the device comprising:

[0011] The first acquisition module is used to acquire the user's first fingerprint information;

[0012] A first determining module is used to determine the similarity between the first fingerprint information and the second fingerprint information, wherein the second fingerprint information is pre-stored user fingerprint information;

[0013] The first comparison module is used to compare the first fingerprint information with the training fingerprint when the similarity between the first fingerprint information and the second fingerprint information is less than a first threshold. The training fingerprint is determined based on multiple fingerprint information of the user that meet preset conditions previously obtained from the first fingerprint information.

[0014] The first determining module is used to unlock the electronic device when it is determined that the similarity between the first fingerprint information and the training fingerprint is greater than a second threshold.

[0015] Thirdly, embodiments of this application provide a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect.

[0016] Fourthly, embodiments of this application provide a chip, the chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the method as described in the first aspect.

[0017] Fifthly, embodiments of this application provide a computer program product stored in a storage medium, which is executed by at least one processor to implement the method described in the first aspect.

[0018] In this embodiment of the application, when using fingerprint unlocking, if the similarity between the user's first fingerprint information and the pre-stored second fingerprint information of the user is less than a first threshold, that is, when fingerprint unlocking cannot be used using the traditional method, the first fingerprint information can be compared with the training fingerprint. Since the training fingerprint is determined based on multiple previously acquired fingerprint information of the user that meet preset conditions, the solution of this embodiment of the application introduces the training fingerprint to perform fingerprint verification on the first fingerprint information on the basis of the traditional fingerprint unlocking solution, thereby improving the accuracy of fingerprint unlocking. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating a fingerprint unlocking method provided in some embodiments of this application;

[0020] Figure 2 These are schematic diagrams illustrating fingerprint information provided in some embodiments of this application;

[0021] Figure 3 This is a flowchart illustrating a fingerprint unlocking method provided in some embodiments of this application;

[0022] Figure 4 These are schematic diagrams illustrating the generation of training fingerprints provided in some embodiments of this application;

[0023] Figure 5These are schematic diagrams illustrating the generation process of training fingerprints provided in some embodiments of this application;

[0024] Figure 6 These are schematic diagrams illustrating the structure of a fingerprint unlocking device according to some embodiments of this application;

[0025] Figure 7 These are schematic diagrams illustrating the structure of an electronic device according to some embodiments of this application;

[0026] Figure 8 These are schematic diagrams illustrating the hardware structure of an electronic device according to some embodiments of this application. Detailed Implementation

[0027] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0028] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and are not limited in number; for example, a first object can be one or N objects. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0029] Before introducing the technical solutions of the embodiments of this application, the background technology of the embodiments of this application will be introduced first:

[0030] The traditional fingerprint unlocking method works as follows: when a user's finger touches the touch sensor, the sensor emits a small amount of radio frequency signal or uses other technologies (such as optical or capacitive) to penetrate the epidermis of the finger and detect the patterns in the inner layer, thereby obtaining the user's fingerprint information. The electronic device then compares the obtained fingerprint information with the unlock fingerprint template pre-stored in the electronic device. If the two match, the verification is successful and the electronic device unlocks successfully; otherwise, the verification fails and the electronic device remains locked.

[0031] Currently, external factors can interfere with the effectiveness of fingerprint unlocking on electronic devices, preventing successful unlocking and thus affecting the accuracy of fingerprint unlocking. For example, when fingers are immersed in water for a long time, noticeable wrinkles often form on the surface of the fingers, a phenomenon known as "water wrinkling," which can severely affect the accuracy of fingerprint unlocking.

[0032] To address the aforementioned issues, embodiments of this application provide a fingerprint unlocking method, apparatus, electronic device, and storage medium. When using fingerprint unlocking, if the similarity between the user's first fingerprint information and the pre-stored second fingerprint information of the user is less than a first threshold, i.e., when fingerprint unlocking cannot be achieved using traditional methods, the first fingerprint information can be compared with a training fingerprint. Since the training fingerprint is determined based on multiple previously acquired fingerprints of the user that meet preset conditions, the solution of this application introduces a training fingerprint to verify the first fingerprint information based on traditional fingerprint unlocking methods, thereby improving the accuracy of fingerprint unlocking.

[0033] The technical solution of this application embodiment can be applied to scenarios where fingerprints fail to unlock due to fingerprint wrinkles caused by external environmental factors, such as when fingers are immersed in water for a long time and a "water wrinkling reaction" occurs, resulting in fingerprint unlocking failure.

[0034] The fingerprint unlocking method provided in this application will be described in detail below with reference to the accompanying drawings, through specific embodiments and application scenarios.

[0035] Figure 1 This is a schematic flowchart of a fingerprint unlocking method provided in an embodiment of this application. The subject executing the fingerprint unlocking method can be an electronic device, which can be, but is not limited to, a personal computer (PC), a smartphone, a tablet computer, or a personal digital assistant (PDA).

[0036] like Figure 1 As shown, the fingerprint unlocking method provided in this application embodiment may include steps 110-140.

[0037] Step 110: Obtain the user's first fingerprint information.

[0038] The first fingerprint information can be the user's fingerprint information obtained when the user wants to unlock the electronic device with their fingerprint.

[0039] In some embodiments of this application, the first fingerprint information may be acquired using a fingerprint acquisition device in an electronic device. This first fingerprint information may be fingerprint information resulting from external factors causing fingerprint creases or other phenomena, such as fingerprint information exhibiting a "water wrinkle reaction."

[0040] Step 120: Determine the similarity between the first fingerprint information and the second fingerprint information.

[0041] The second fingerprint information can be pre-stored user fingerprint information. This second fingerprint information can be fingerprint information that can successfully unlock the electronic device. This second fingerprint information can be used to verify the first fingerprint information to verify whether the first fingerprint information can successfully unlock the electronic device.

[0042] In some embodiments of this application, reference is made to Figure 2 Fingerprint information can be composed of multiple feature pixels, such as Figure 2 Feature pixels 21, 22 and 23 are shown in the image.

[0043] It should be noted that, Figure 2 The example shown is merely one example and does not limit fingerprint information to only 3 feature pixels.

[0044] To accurately determine the similarity between the first fingerprint information and the second fingerprint information, step 120 may specifically include:

[0045] The fifth feature pixel set corresponding to the first fingerprint information is compared with the second feature pixel set corresponding to the second fingerprint information;

[0046] The similarity between the first fingerprint information and the second fingerprint information is determined based on the number of identical feature pixels between the fifth feature pixel set and the second feature pixel set.

[0047] The fifth feature pixel set can be a set of feature pixels corresponding to the first fingerprint information.

[0048] The second feature pixel set can be a set of feature pixels corresponding to the second fingerprint information.

[0049] In some embodiments of this application, when comparing the first fingerprint information and the second fingerprint information, the fifth feature pixel set corresponding to the first fingerprint information may be compared with the second feature pixel set corresponding to the second fingerprint information. The similarity between the first fingerprint information and the second fingerprint information can be determined based on the number of identical feature pixels between the fifth feature pixel set and the second feature pixel set.

[0050] In one example, taking the fifth feature pixel set corresponding to the first fingerprint information as feature pixel set c and the second feature pixel set corresponding to the second fingerprint information as feature pixel set a, the number of identical feature pixels in feature pixel set c and feature pixel set a can be compared, and the similarity between the first fingerprint information and the second fingerprint information can be determined based on this number.

[0051] In the embodiments of this application, by comparing the fifth feature pixel set corresponding to the first fingerprint information with the second feature pixel set corresponding to the second fingerprint information, and then accurately determining the similarity between the first fingerprint information and the pre-stored second fingerprint information of the user based on the number of identical feature pixels between the fifth feature pixel set and the second feature pixel set, the accuracy of determining the similarity between the first fingerprint information and the pre-stored second fingerprint information of the user is improved.

[0052] Step 130: If the similarity between the first fingerprint information and the second fingerprint information is less than the first threshold, compare the first fingerprint information with the training fingerprint.

[0053] The first threshold can be a pre-set threshold representing the similarity between the first fingerprint information and the second fingerprint information. Specifically, the first threshold can be a threshold indicating that the electronic device can be successfully unlocked by comparing the first fingerprint information and the second fingerprint information. The specific value of the first threshold can be set according to user needs and is not limited in this embodiment.

[0054] Training fingerprints can be fingerprint information other than the second fingerprint information used to verify the first fingerprint information when the electronic device is not successfully unlocked using the first fingerprint information, and the second fingerprint information is used to verify the first fingerprint information.

[0055] The training fingerprint can be determined based on multiple fingerprints of the user that meet preset conditions, obtained prior to the acquisition of the first fingerprint information. In other words, the training fingerprint is determined based on multiple fingerprints of the user that meet preset conditions acquired before the acquisition of the first fingerprint information. These preset conditions can be pre-set conditions that can be used as training fingerprints, and these preset conditions will be described in detail in subsequent embodiments.

[0056] In some embodiments of this application, when it is determined that the similarity between the first fingerprint information and the second fingerprint information is less than a first threshold, that is, when the electronic device is not successfully unlocked when the first fingerprint information is used to unlock it, the first fingerprint information can be compared with the training fingerprint.

[0057] The determination that the similarity between the first fingerprint information and the second fingerprint information is less than a first threshold can specifically include:

[0058] If the number of identical feature pixels between the fifth feature pixel set and the second feature pixel set is less than a first threshold, it is determined that the similarity between the first fingerprint information and the second fingerprint information is less than the first threshold.

[0059] In some embodiments of this application, the similarity between the first fingerprint information and the second fingerprint information can be determined based on the relationship between the number of identical feature pixels between the fifth feature pixel set and the second feature pixel set and the first threshold.

[0060] It should be noted that when comparing the first fingerprint information with the training fingerprint, the feature pixel set corresponding to the first fingerprint information is also compared with the feature pixel set corresponding to the training fingerprint.

[0061] In some embodiments of this application, if the similarity between the first fingerprint information and the pre-stored second fingerprint information of the user is greater than or equal to a first threshold, it indicates that the similarity between the first fingerprint information and the second fingerprint information is very high, that is, the electronic device can be successfully unlocked using the first fingerprint information.

[0062] Step 140: If the similarity between the first fingerprint information and the training fingerprint is greater than the second threshold, unlock the electronic device.

[0063] The second threshold can be a pre-set similarity threshold between the first fingerprint information and the training fingerprint. This second threshold is used to characterize the threshold at which the electronic device can be successfully unlocked by comparing the first fingerprint information with the training fingerprint. The second threshold can be the same as or different from the first threshold. The specific value of the second threshold can be set according to user needs and is not limited in this embodiment.

[0064] In some embodiments of this application, if the similarity between the first fingerprint information and the training fingerprint is greater than a second threshold, it indicates that the first fingerprint information and the training fingerprint are very similar, and the electronic device can be successfully unlocked using the first fingerprint information.

[0065] In some embodiments of this application, to enhance the diversity of unlocking methods, after step 120, the method described above may further include:

[0066] If the similarity between the first fingerprint information and the training fingerprint is less than or equal to the second threshold, a prompt message is output.

[0067] The prompt information can be information output when the similarity between the first fingerprint information and the training fingerprint is less than or equal to a second threshold, used to prompt the user whether to use other methods to unlock the electronic device. In other words, the prompt information is used to prompt the user whether to use other methods to unlock the electronic device.

[0068] In some embodiments of this application, if the similarity between the first fingerprint information and the training fingerprint is less than or equal to a second threshold, it indicates that the first fingerprint information cannot unlock the electronic device. Therefore, the electronic device can output a prompt message asking the user whether to use other biometric identification methods to unlock the electronic device, such as, but not limited to, facial recognition, iris recognition, pattern recognition, password recognition, etc. If the user confirms to use other biometric identification methods to unlock the electronic device, the electronic device can control the designated identification device to perform identification and unlocking. If the user still uses the fingerprint unlocking method, the above steps 110-140 are repeated until fingerprint unlocking is successful.

[0069] In the embodiments of this application, if the similarity between the first fingerprint information and the training fingerprint is less than or equal to a second threshold, a prompt message can be output to prompt the user whether to use other methods to unlock the electronic device. This allows the user to use other unlocking methods if fingerprint unlocking fails, thus improving the diversity of unlocking methods.

[0070] The above describes the workflow of unlocking electronic devices using fingerprint information. To better understand the fingerprint unlocking workflow described above, the following describes the workflow of the fingerprint unlocking method using a specific scenario.

[0071] Figure 3 This is a flowchart illustrating a fingerprint unlocking method provided in an embodiment of this application, as shown below. Figure 3 As shown, the fingerprint unlocking method provided in this application embodiment may include steps 301-306.

[0072] Step 301: Obtain the user's first fingerprint information.

[0073] Step 302: Determine whether the similarity between the first fingerprint information and the pre-stored second fingerprint information of the user is greater than or equal to the first threshold. If yes, proceed to step 306; otherwise, proceed to step 303.

[0074] Step 303: Determine whether the similarity between the first fingerprint information and the training fingerprint is greater than the second threshold. If yes, proceed to step 306; otherwise, proceed to step 304.

[0075] Step 304: Should other methods be used to unlock the electronic device? If yes, proceed to step 305; otherwise, return to step 301.

[0076] Step 305: Unlock the electronic device using other methods.

[0077] Step 306: Electronic device successfully unlocked.

[0078] The following describes the process of determining the training fingerprint:

[0079] In some embodiments of this application, in order to improve the accuracy of fingerprint unlocking, the method described above may further include the following steps before step 110:

[0080] Obtain multiple third-party fingerprint information of the user;

[0081] Each third fingerprint is compared with the second fingerprint.

[0082] If the similarity between the third fingerprint information and the second fingerprint information is less than the first threshold but greater than the third threshold, the third fingerprint information will be used as the pre-trained fingerprint.

[0083] If the electronic device is successfully unlocked using the pre-trained fingerprint within a preset time period, the third fingerprint information is determined to be the fingerprint to be trained.

[0084] The training fingerprint is determined based on multiple fingerprints to be trained.

[0085] The third fingerprint information can be the user's fingerprint information collected before the electronic device is unlocked using the first fingerprint information. The third fingerprint information can be the user's fingerprint information collected under any circumstances, such as the fingerprint information of the "water wrinkle reaction", or the fingerprint information of other circumstances, such as the fingerprint information collected when the finger has been soaked but has not yet reached a very obvious "water wrinkle reaction".

[0086] The third threshold can be a pre-set threshold for the similarity between the third fingerprint information and the second fingerprint information. This third threshold can be a threshold for judging whether the first fingerprint information is similar to the pre-stored fingerprints (second fingerprint information and training fingerprints) in the electronic device. If it is greater than the third threshold, the first fingerprint information is considered to be similar to the pre-stored fingerprints but with some differences. Although it cannot successfully unlock the device, it can be used as a potential training sample to generate training fingerprints. The value of this third threshold can be set by the user according to their needs, and is not limited in this embodiment.

[0087] Pre-trained fingerprints can be prepared fingerprints for training fingerprints. Specifically, if the similarity between the third fingerprint information and the second fingerprint information is determined to be less than a first threshold and greater than a third threshold, the third fingerprint information can be used as a pre-trained fingerprint.

[0088] The preset time period can be the time that a pre-set fingerprint can use to unlock an electronic device, and this time period can be used as the time period for the fingerprint to be trained.

[0089] It should be noted that the above-mentioned preset time period can be determined based on prior experience or user needs, based on the perceived time required to unlock the electronic device. For example, under normal circumstances, when unlocking an electronic device with a fingerprint, if it fails to unlock at first, it will try several more times, usually for a period of time (such as 30 seconds). If it still fails to unlock within this time period, it is considered that the fingerprint will not be able to unlock the electronic device. If it can unlock the electronic device within this time period, it is considered that the fingerprint can successfully unlock the electronic device. It is just that the fingerprint may not have been fully acquired at the beginning or other factors may have caused the fingerprint to fail to unlock. In this case, the preset time period can be 30 seconds.

[0090] The fingerprint to be trained can be a fingerprint that is intended to be used as a training fingerprint.

[0091] In some embodiments of this application, multiple third fingerprint information of a user can be obtained. Then, for each third fingerprint information, the third fingerprint information is compared with the second fingerprint information. If the similarity between the third fingerprint information and the second fingerprint information is less than a first threshold and greater than a third threshold, the third fingerprint information is used as a pre-training fingerprint. If the electronic device is successfully unlocked using the pre-training fingerprint within a preset time period, the third fingerprint information is determined as a fingerprint to be trained. Then, based on multiple fingerprints to be trained, a training fingerprint is determined.

[0092] It should be noted that when comparing the third fingerprint information with the second fingerprint information, the feature pixel set corresponding to the third fingerprint information is also compared with the feature pixel set corresponding to the second fingerprint information. It is determined whether the number of the same feature pixels in the feature pixel set corresponding to the third fingerprint information and the feature pixel set corresponding to the second fingerprint information is greater than the third threshold. If it is greater than the third threshold, it is determined that the similarity between the third fingerprint information and the second fingerprint information is less than the first threshold and greater than the third threshold.

[0093] In the embodiments of this application, multiple third fingerprint information obtained in advance, although these third fingerprint information cannot successfully unlock the electronic device, can be used as potential training samples to generate training fingerprints. In this way, when the randomness of the folds generated by the "water ripple reaction" causes the fingerprint unlocking to fail, the first fingerprint information can be verified based on the training fingerprint to improve the accuracy of fingerprint unlocking.

[0094] In some embodiments of this application, if the similarity between the third fingerprint information and the second fingerprint information is determined to be less than or equal to a third threshold, it is considered that the third fingerprint information cannot successfully unlock the electronic device, that is, the third fingerprint information does not belong to the holder of the electronic device, and therefore the third fingerprint information can be erased.

[0095] If the similarity between the third fingerprint information and the second fingerprint information is less than the first threshold and greater than the third threshold, but the electronic device still fails to unlock using the pre-trained fingerprint within a preset time period, then the third fingerprint information is considered to be insufficiently collected, and the third fingerprint information can be erased.

[0096] In some embodiments of this application, to improve the accuracy of determining the training fingerprint, the step of determining the training fingerprint based on multiple fingerprints to be trained may include:

[0097] Obtain the first feature pixel set corresponding to each fingerprint to be trained, and the second feature pixel set corresponding to the second fingerprint information;

[0098] The training fingerprint is determined based on the first feature pixel set and the second feature pixel set corresponding to each fingerprint to be trained.

[0099] Specifically, for each fingerprint to be trained, its corresponding first feature pixel set can be the set of feature pixels corresponding to that fingerprint.

[0100] In some embodiments of this application, since fingerprint information is composed of multiple feature pixels, the training fingerprint can be determined based on the first feature pixel set corresponding to each fingerprint to be trained and the second feature pixel set corresponding to the second fingerprint information.

[0101] In the embodiments of this application, the accuracy of training fingerprint determination is improved by determining the training fingerprint based on the first feature pixel set corresponding to each fingerprint to be trained and the second feature pixel set corresponding to the second fingerprint information.

[0102] In some embodiments of this application, in order to accurately obtain the training fingerprint, determining the training fingerprint based on the first feature pixel set and the second feature pixel set corresponding to each fingerprint to be trained may include:

[0103] Obtain the first feature pixel set corresponding to each fingerprint to be trained, and the feature pixels that exist in both the second feature pixel set, to obtain the third feature pixel set;

[0104] Obtain the feature pixels that exist in the second feature pixel set and whose occurrence frequency in the first feature pixel set corresponding to each fingerprint to be trained is greater than or equal to the fourth threshold, and obtain the fourth feature pixel set.

[0105] The training fingerprint is obtained based on the third feature pixel set and the fourth feature pixel set.

[0106] The third feature pixel set can be the set of feature pixels that exist in both the first feature pixel set and the second feature pixel set for each fingerprint to be trained.

[0107] The fourth feature pixel set can be a set of feature pixels that exist in the second feature pixel set and whose occurrence frequency in the first feature pixel set corresponding to each fingerprint to be trained is greater than the fourth threshold.

[0108] The fourth threshold can be a pre-set threshold for the number of times a feature pixel exists in the second feature pixel set. This threshold is the number of times a feature pixel appears in the first feature pixel set corresponding to each fingerprint to be trained. The fourth threshold can be determined based on the number of fingerprints to be trained and the number of second fingerprint information. Specifically, it can be half the number of fingerprints to be trained and the number of second fingerprint information. For example, if there are 10 fingerprints to be trained and 1 second fingerprint information, then the fourth threshold can be 6.

[0109] In some embodiments of this application, feature pixels that exist in both the first feature pixel set and the second feature pixel set corresponding to each fingerprint to be trained can be obtained to obtain a third feature pixel set. Then, feature pixels that exist in the second feature pixel set and whose occurrence frequency in the first feature pixel set corresponding to each fingerprint to be trained is greater than or equal to a fourth threshold can be obtained to obtain a fourth feature pixel set. The sum of the third feature pixel set and the fourth feature pixel set is used as the pixel feature point set of the training fingerprint.

[0110] Continue to refer to the above example, see Figure 4The fingerprints to be trained include training fingerprint 41 and training fingerprint 42. The feature pixel set corresponding to training fingerprint 41 includes: feature pixels 1, 2, 4, 5, 6, 8, 9, 10, 11, 13, and 14. The feature pixel set corresponding to training fingerprint 42 includes: feature pixels 1, 2, 3, 4, 5, 6, 10, 14, 15, and 16. The feature pixel set a corresponding to the second fingerprint information includes: feature pixels 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10. Taking a fourth threshold of 1 as an example, the feature pixels 1, 2, 4, 5, 6, and 10 are included in both training fingerprint 41, training fingerprint 42, and the second fingerprint information. The feature pixels 3, 8, 9, and 14 appear more than or equal to 1 time in training fingerprint 41 and training fingerprint 42. Therefore, feature pixels 1, 2, 4, 5, 6, 10, 3, 8, 9, and 14 can be used as the feature pixel set b corresponding to the training fingerprint.

[0111] It should be noted that the above Figure 4 The feature pixel set corresponding to the fingerprint to be trained and the feature pixel set corresponding to the second fingerprint information are only for illustration and do not limit the number and position of feature pixels in the feature pixel set corresponding to the fingerprint to be trained and the feature pixel set corresponding to the second fingerprint information. Figure 4 The quantities and positions are shown.

[0112] It should be noted that the third feature pixel set can be used as the basic feature pixel set, and the fourth feature pixel set can be used as the trust feature pixel set. The feature pixel set for training fingerprints = basic feature pixel set + trust feature pixel set.

[0113] The aforementioned basic feature pixel set and trust feature pixel set can be understood as follows: After a finger is immersed for a long time and a "water wrinkling reaction" occurs, most fingerprint features will still be retained, that is, feature pixels contained in all samples (the fingerprint to be trained and the second fingerprint information). This part constitutes the basic feature pixels; some fingerprint features will disappear or change, and each change is random. Feature pixels that appear more frequently in all samples can be identified as "new features" generated by the fingerprint after the "water wrinkling reaction". These pixels constitute the trust feature pixels.

[0114] In the embodiments of this application, a third set of feature pixels is obtained by acquiring feature pixels that exist in both the first and second set of feature pixels corresponding to each fingerprint to be trained; and a fourth set of feature pixels is obtained by acquiring feature pixels that exist in the second set of feature pixels and whose occurrence frequency in the first set of feature pixels corresponding to each fingerprint to be trained is greater than or equal to a fourth threshold; then, the training fingerprint can be accurately obtained based on the third and fourth set of feature pixels.

[0115] In some embodiments of this application, when the number of training fingerprint samples is insufficient, fingerprint recognition may fail due to the randomness of the folds generated by the water ripple reaction. However, as the number of training fingerprint samples collected increases, the unlocking accuracy and speed can be further improved. Therefore, after each acquisition of fingerprint information, the above method can be used to increase the feature pixel set of the training fingerprint, thereby enriching the feature pixel set of the training fingerprint and improving the fingerprint unlocking accuracy and speed.

[0116] Therefore, after obtaining the first fingerprint information, if the similarity between the first fingerprint information and the second fingerprint information is less than a first threshold, the feature pixels in the first fingerprint information can also be used as rows and columns of feature pixels for training fingerprints. Specifically, if the similarity between the first fingerprint information and the pre-stored second fingerprint information of the user is less than a first threshold, the method described above can further include:

[0117] If the similarity between the first fingerprint information and the second fingerprint information is greater than a third threshold, and the electronic device is successfully unlocked using the first fingerprint information within a preset time period, the training fingerprint is updated based on the first fingerprint information.

[0118] In some embodiments of this application, when the similarity between the first fingerprint information and the pre-stored second fingerprint information of the user is less than a first threshold, that is, when the electronic device is not successfully unlocked when the first fingerprint information is compared with the second fingerprint information, if the similarity between the first fingerprint information and the second fingerprint information is greater than a third threshold, and the electronic device is successfully unlocked using the first fingerprint information within a preset time period, the first fingerprint information can be used as the fingerprint to be trained, and the training fingerprint can be updated using the first fingerprint information to increase the sample size of the training fingerprint.

[0119] In the embodiments of this application, if the similarity between the first fingerprint information and the pre-stored second fingerprint information of the user is less than a first threshold and greater than a third threshold, and the electronic device is successfully unlocked using the first fingerprint information within a preset time period, the training fingerprint can be updated based on the first fingerprint information. This can increase the sample size of the training fingerprint to improve the accuracy and speed of fingerprint unlocking.

[0120] The process of generating training fingerprints has been introduced above. To better understand the above process of generating training fingerprints, the following section will use the third fingerprint information, including fingerprint information 31, fingerprint information 32, ..., fingerprint information 3n, as an example to introduce the process of generating training fingerprints.

[0121] Figure 5 This is a schematic flowchart illustrating a fingerprint generation process provided in an embodiment of this application, as shown below. Figure 5 As shown, the training fingerprint generation process provided in this application embodiment may include steps 511-517.

[0122] Step 511: Determine whether the similarity between the feature pixel set corresponding to fingerprint information 31 and the second feature pixel set corresponding to the second fingerprint information is greater than the third threshold. If yes, proceed to step 512; otherwise, proceed to step 513.

[0123] Step 512, erase fingerprint information 31.

[0124] Step 513: Use fingerprint information 31 as a pre-trained fingerprint.

[0125] Step 514: Determine whether the electronic device can be successfully unlocked using the pre-trained fingerprint within a preset time period. If not, proceed to step 515; if yes, proceed to step 516.

[0126] Step 515: Erase the pre-trained fingerprint.

[0127] Step 516: Use the pre-trained fingerprint as the fingerprint to be trained.

[0128] In this process, fingerprint information 32, ..., fingerprint information 3n are processed according to the fingerprint information 31 above, and steps 511-516 are executed respectively to obtain multiple fingerprints to be trained.

[0129] Step 517: Determine the training fingerprint based on multiple fingerprints to be trained.

[0130] The specific implementation process of step 517 can be referred to the above embodiments, and will not be repeated here.

[0131] The fingerprint unlocking method provided in this application can be executed by a fingerprint unlocking device. This application uses an example of a fingerprint unlocking device executing an information processing method to illustrate the fingerprint unlocking device provided in this application.

[0132] Figure 6 This is a schematic diagram illustrating the structure of a fingerprint unlocking device according to an exemplary embodiment. Figure 6 As shown, the fingerprint unlocking device 600 may include:

[0133] The first acquisition module 610 is used to acquire the user's first fingerprint information;

[0134] The first determining module 620 is used to determine the similarity between the first fingerprint information and the second fingerprint information, wherein the second fingerprint information is pre-stored user fingerprint information.

[0135] The first comparison module 630 is used to compare the first fingerprint information with a training fingerprint when the similarity between the first fingerprint information and the pre-stored second fingerprint information of the user is less than a first threshold. The training fingerprint is determined based on multiple fingerprint information of the user that meet preset conditions previously obtained from the first fingerprint information.

[0136] The unlocking module 640 is used to unlock the electronic device when it is determined that the similarity between the first fingerprint information and the training fingerprint is greater than a second threshold.

[0137] In this embodiment of the application, when using fingerprint unlocking, if the similarity between the user's first fingerprint information and the pre-stored second fingerprint information of the user is less than a first threshold, that is, when fingerprint unlocking cannot be used using the traditional method, the first fingerprint information can be compared with the training fingerprint. Since the training fingerprint is determined based on multiple previously acquired fingerprint information of the user that meet preset conditions, the solution of this embodiment of the application introduces the training fingerprint to perform fingerprint verification on the first fingerprint information on the basis of the traditional fingerprint unlocking solution, thereby improving the accuracy of fingerprint unlocking.

[0138] In some embodiments of this application, the apparatus described above may further include:

[0139] The second acquisition module is used to acquire multiple third fingerprint information of the user before acquiring the user's first fingerprint information;

[0140] The second comparison module is used to compare each of the third fingerprint information with the second fingerprint information respectively;

[0141] The second determining module is used to use the third fingerprint information as a pre-training fingerprint when the similarity between the third fingerprint information and the second fingerprint information is less than the first threshold and greater than the third threshold.

[0142] The third determining module is used to determine the third fingerprint information as a fingerprint to be trained if the electronic device is successfully unlocked using the pre-trained fingerprint within a preset time period.

[0143] The fourth determining module is used to determine the training fingerprint based on multiple fingerprints to be trained.

[0144] In some embodiments of this application, the fourth determining module includes:

[0145] The first acquisition unit is used to acquire the first feature pixel set corresponding to each fingerprint to be trained, and the second feature pixel set corresponding to the second fingerprint information.

[0146] The first determining unit is configured to determine the training fingerprint based on the first feature pixel set corresponding to each fingerprint to be trained and the second feature pixel set.

[0147] In some embodiments of this application, the first determining unit is specifically used for:

[0148] Obtain the first feature pixel set corresponding to each fingerprint to be trained, and the feature pixels that exist in both the second feature pixel set, to obtain the third feature pixel set;

[0149] Obtain the feature pixels that exist in the second feature pixel set and whose occurrence frequency in the first feature pixel set corresponding to each fingerprint to be trained is greater than or equal to the fourth threshold, and obtain the fourth feature pixel set.

[0150] The training fingerprint is obtained based on the third feature pixel set and the fourth feature pixel set.

[0151] In some embodiments of this application, when it is determined that the similarity between the first fingerprint information and the second fingerprint information is less than a first threshold, the aforementioned apparatus may further include:

[0152] An update module is used to update the training fingerprint based on the first fingerprint information when it is determined that the similarity between the first fingerprint information and the second fingerprint information is greater than the third threshold, and the electronic device is successfully unlocked using the first fingerprint information within the preset time period.

[0153] In some embodiments of this application, the first determining module 620 is specifically used for:

[0154] The fifth feature pixel set corresponding to the first fingerprint information is compared with the second feature pixel set corresponding to the second fingerprint information;

[0155] The similarity between the first fingerprint information and the second fingerprint information is determined based on the number of identical feature pixels between the fifth feature pixel set and the second feature pixel set.

[0156] The fingerprint unlocking device in this application embodiment can be an electronic device or a component within an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. It can also be a server, network attached storage (NAS), personal computer (PC), television (TV), ATM, or self-service machine, etc. This application embodiment does not specifically limit the device.

[0157] The fingerprint unlocking device in this application embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit the specific operating system used.

[0158] The fingerprint unlocking device provided in this application embodiment can achieve... Figure 1 The various processes implemented in the method implementation examples will not be described again here to avoid repetition.

[0159] Optionally, such as Figure 7 As shown, this application embodiment also provides an electronic device 700, including a processor 701 and a memory 702. The memory 702 stores a program or instructions that can run on the processor 701. When the program or instructions are executed by the processor 701, they implement the various steps of the above-described fingerprint unlocking method embodiment and can achieve the same technical effect. To avoid repetition, they will not be described again here.

[0160] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0161] Figure 8 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of this application.

[0162] The electronic device 800 includes, but is not limited to, components such as: radio frequency unit 801, network module 802, audio output unit 803, input unit 804, sensor 805, display unit 806, user input unit 807, interface unit 808, memory 809, and processor 810.

[0163] Those skilled in the art will understand that the electronic device 800 may also include a power supply (such as a battery) for supplying power to various components. The power supply may be logically connected to the processor 810 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. Figure 8 The electronic device structure shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0164] The processor 810 is configured to: acquire a user's first fingerprint information; determine the similarity between the first fingerprint information and second fingerprint information, wherein the second fingerprint information is pre-stored user fingerprint information; if the similarity between the first fingerprint information and the second fingerprint information is less than a first threshold, compare the first fingerprint information with a training fingerprint, wherein the training fingerprint is determined based on multiple fingerprints of the user that meet preset conditions previously acquired from the first fingerprint information; and unlock the electronic device if the similarity between the first fingerprint information and the training fingerprint is determined to be greater than a second threshold.

[0165] Thus, when using fingerprint unlocking, if the similarity between the user's first fingerprint information and the pre-stored second fingerprint information is less than a first threshold, that is, if fingerprint unlocking cannot be used using the traditional method, the first fingerprint information can be compared with the training fingerprint. Since the training fingerprint is determined based on multiple previously acquired fingerprint information of the user that meet preset conditions, the solution of this application embodiment introduces a training fingerprint to verify the first fingerprint information on the basis of the traditional fingerprint unlocking solution, thereby improving the accuracy of fingerprint unlocking.

[0166] Optionally, the processor 810 is configured to acquire multiple third fingerprint information of the user before acquiring the user's first fingerprint information; compare each of the third fingerprint information with the second fingerprint information respectively; if the similarity between the third fingerprint information and the second fingerprint information is less than the first threshold and greater than the third threshold, use the third fingerprint information as a pre-training fingerprint; if the electronic device is successfully unlocked using the pre-training fingerprint within a preset time period, determine the third fingerprint information as a fingerprint to be trained; and determine the training fingerprint based on the multiple fingerprints to be trained.

[0167] In this way, by acquiring multiple third fingerprint information in advance, although these third fingerprint information cannot successfully unlock electronic devices, they can be used as potential training samples to generate training fingerprints. Thus, in the case where the randomness of the folds generated by the "water ripple reaction" causes fingerprint unlocking to fail, the first fingerprint information can be verified based on the training fingerprints to improve the accuracy of fingerprint unlocking.

[0168] Optionally, the processor 810 is configured to acquire a first feature pixel set corresponding to each fingerprint to be trained, and a second feature pixel set corresponding to the second fingerprint information; and determine the training fingerprint based on the first feature pixel set corresponding to each fingerprint to be trained and the second feature pixel set.

[0169] Thus, by determining the training fingerprint based on the first feature pixel set corresponding to each fingerprint to be trained and the second feature pixel set corresponding to the second fingerprint information, the accuracy of training fingerprint determination is improved.

[0170] Optionally, the processor 810 is configured to obtain a first set of feature pixels corresponding to each fingerprint to be trained, and feature pixels that exist in both the second set of feature pixels, to obtain a third set of feature pixels; obtain feature pixels that exist in the second set of feature pixels and whose occurrence frequency in the first set of feature pixels corresponding to each fingerprint to be trained is greater than or equal to a fourth threshold, to obtain a fourth set of feature pixels; and obtain the training fingerprint based on the third set of feature pixels and the fourth set of feature pixels.

[0171] Thus, by acquiring the first feature pixel set corresponding to each fingerprint to be trained and the feature pixels that exist in both the first and second feature pixel sets, a third feature pixel set is obtained; and by acquiring the feature pixels that exist in the second feature pixel set and whose occurrence frequency in the first feature pixel set corresponding to each fingerprint to be trained is greater than or equal to a fourth threshold, a fourth feature pixel set is obtained; then, based on the third and fourth feature pixel sets, the training fingerprint can be accurately obtained.

[0172] Optionally, the processor 810 is configured to update the training fingerprint based on the first fingerprint information when it is determined that the similarity between the first fingerprint information and the second fingerprint information is less than a first threshold, and when it is determined that the similarity between the first fingerprint information and the second fingerprint information is greater than the third threshold, and the electronic device is successfully unlocked using the first fingerprint information within the preset time period.

[0173] Thus, if the similarity between the first fingerprint information and the pre-stored second fingerprint information of the user is less than the first threshold and greater than the third threshold, and the electronic device is successfully unlocked using the first fingerprint information within a preset time period, the training fingerprint can be updated based on the first fingerprint information. This can increase the sample size of the training fingerprint to improve the accuracy and speed of fingerprint unlocking.

[0174] Optionally, the processor 810 is configured to compare the fifth feature pixel set corresponding to the first fingerprint information with the second feature pixel set corresponding to the second fingerprint information; and determine the similarity between the first fingerprint information and the second fingerprint information based on the number of identical feature pixels between the fifth feature pixel set and the second feature pixel set.

[0175] Thus, by comparing the fifth feature pixel set corresponding to the first fingerprint information with the second feature pixel set corresponding to the second fingerprint information, and then accurately determining the similarity between the first fingerprint information and the pre-stored second fingerprint information of the user based on the number of identical feature pixels between the fifth feature pixel set and the second feature pixel set, the accuracy of determining the similarity between the first fingerprint information and the pre-stored second fingerprint information of the user is improved.

[0176] It should be understood that, in this embodiment, the input unit 804 may include a graphics processing unit (GPU) 8041 and a microphone 8042. The GPU 8041 processes image data of still images or videos obtained by an image capture device (such as a color camera) in video capture mode or image capture mode. The display unit 806 may include a display panel 8061, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, or the like. The user input unit 807 includes at least one of a touch panel 8071 and other input devices 8072. The touch panel 8071 is also called a touch screen. The touch panel 8071 may include a touch detection device and a touch controller. Other input devices 8072 may include, but are not limited to, physical keyboards, function keys (such as volume control buttons, power buttons, etc.), trackballs, mice, and joysticks, which will not be described in detail here.

[0177] The memory 809 can be used to store software programs and various data. The memory 809 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback, image playback, etc.). Furthermore, the memory 809 may include volatile memory or non-volatile memory, or both. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 809 in the embodiments of this application includes, but is not limited to, these and any other suitable types of memory.

[0178] Processor 810 may include one or more processing units; optionally, processor 810 integrates an application processor and a modem processor, wherein the application processor mainly handles operations involving the operating system, user interface, and applications, and the modem processor mainly handles wireless communication signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into processor 810.

[0179] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the fingerprint unlocking method embodiments described above and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0180] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0181] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above fingerprint unlocking method embodiments and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0182] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0183] This application provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the fingerprint unlocking method embodiments described above, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0184] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0185] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0186] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A fingerprint unlocking method, characterized in that, The method includes: Obtain the user's first fingerprint information; Determine the similarity between the first fingerprint information and the second fingerprint information, wherein the second fingerprint information is pre-stored user fingerprint information; If the similarity between the first fingerprint information and the second fingerprint information is less than a first threshold, the first fingerprint information is compared with the training fingerprint, which is determined based on multiple fingerprint information of the user that meet preset conditions previously obtained from the first fingerprint information. If the similarity between the first fingerprint information and the training fingerprint is determined to be greater than a second threshold, the electronic device is unlocked; Prior to obtaining the user's first fingerprint information, the method further includes: Obtain multiple third-party fingerprint information of the user; Each of the third fingerprint information is compared with the second fingerprint information; If the similarity between the third fingerprint information and the second fingerprint information is less than the first threshold and greater than the third threshold, the third fingerprint information is used as a pre-trained fingerprint. If the electronic device is successfully unlocked using the pre-trained fingerprint within a preset time period, the third fingerprint information is determined to be the fingerprint to be trained. Obtain the first feature pixel set corresponding to each fingerprint to be trained, and the feature pixels that exist in the second feature pixel set corresponding to the second fingerprint information, to obtain the third feature pixel set; Obtain the feature pixels that exist in the second feature pixel set and whose occurrence frequency in the first feature pixel set corresponding to each fingerprint to be trained is greater than or equal to the fourth threshold, and obtain the fourth feature pixel set. The training fingerprint is obtained based on the third feature pixel set and the fourth feature pixel set.

2. The method according to claim 1, characterized in that, If the similarity between the first fingerprint information and the second fingerprint information is determined to be less than a first threshold, the method further includes: If the similarity between the first fingerprint information and the second fingerprint information is greater than the third threshold, and the electronic device is successfully unlocked using the first fingerprint information within the preset time period, the training fingerprint is updated based on the first fingerprint information.

3. The method according to claim 1, characterized in that, Determining the similarity between the first fingerprint information and the second fingerprint information includes: The fifth feature pixel set corresponding to the first fingerprint information is compared with the second feature pixel set corresponding to the second fingerprint information; The similarity between the first fingerprint information and the second fingerprint information is determined based on the number of identical feature pixels between the fifth feature pixel set and the second feature pixel set.

4. A fingerprint unlocking device, characterized in that, The device includes: The first acquisition module is used to acquire the user's first fingerprint information; A first determining module is used to determine the similarity between the first fingerprint information and the second fingerprint information, wherein the second fingerprint information is pre-stored user fingerprint information; The first comparison module is used to compare the first fingerprint information with the training fingerprint when the similarity between the first fingerprint information and the second fingerprint information is less than a first threshold. The training fingerprint is determined based on multiple fingerprint information of the user that meet preset conditions previously obtained from the first fingerprint information. The unlocking module is used to unlock the electronic device when it is determined that the similarity between the first fingerprint information and the training fingerprint is greater than a second threshold. The device further includes: The second acquisition module is used to acquire multiple third fingerprint information of the user before acquiring the user's first fingerprint information; The second comparison module is used to compare each of the third fingerprint information with the second fingerprint information respectively; The second determining module is used to use the third fingerprint information as a pre-training fingerprint when the similarity between the third fingerprint information and the second fingerprint information is less than the first threshold and greater than the third threshold. The third determining module is used to determine the third fingerprint information as a fingerprint to be trained if the electronic device is successfully unlocked using the pre-trained fingerprint within a preset time period. The fourth determining module is used to obtain feature pixels that exist in both the first feature pixel set corresponding to each fingerprint to be trained and the second feature pixel set corresponding to the second fingerprint information, to obtain a third feature pixel set; obtain feature pixels that exist in the second feature pixel set and whose occurrence frequency in the first feature pixel set corresponding to each fingerprint to be trained is greater than or equal to a fourth threshold, to obtain a fourth feature pixel set; and obtain the training fingerprint based on the third feature pixel set and the fourth feature pixel set.

5. The apparatus according to claim 4, characterized in that, If the similarity between the first fingerprint information and the second fingerprint information is determined to be less than a first threshold, the device further includes: An update module is used to update the training fingerprint based on the first fingerprint information when it is determined that the similarity between the first fingerprint information and the second fingerprint information is greater than the third threshold, and the electronic device is successfully unlocked using the first fingerprint information within the preset time period.

6. The apparatus according to claim 4, characterized in that, The first determining module is specifically used for: The fifth feature pixel set corresponding to the first fingerprint information is compared with the second feature pixel set corresponding to the second fingerprint information; The similarity between the first fingerprint information and the second fingerprint information is determined based on the number of identical feature pixels between the fifth feature pixel set and the second feature pixel set.

7. An electronic device, characterized in that, It includes a processor and a memory, the memory storing a program or instructions that can run on the processor, the program or instructions being executed by the processor to implement the steps of the fingerprint unlocking method as described in any one of claims 1-3.

8. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the fingerprint unlocking method as described in any one of claims 1-3.

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