Key feature matching method, processor, electronic lock and storage medium

Abstract

The invention relates to a key feature matching method, a processor, an electronic lock and a storage medium, and the key feature matching method comprises the steps: obtaining a currently collected target key feature under the condition of receiving an unlocking request; constructing a query key; determining a key feature index matched with the query key from a pre-constructed feature index database; the key feature index is associated with the unlocking frequency corresponding to each reference key feature in a preset feature information base; determining a candidate key feature sequence corresponding to the target key feature from a feature information base according to a key feature index matched by the query key; and sequentially comparing all candidate key features in the candidate key feature sequence with the target key feature to obtain a comparison result. Retrieval and comparison of key features can be realized based on the unlocking frequency, so that the searching and comparison frequency and time are reduced, and the key feature searching and matching efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of electronic locks, and in particular to a key feature matching method, a processor, an electronic lock and a storage medium. Background Art

[0002] With the development of science and technology and the improvement of people's demand for residential safety, electronic locks have been widely used in the field of home residences, providing families with a more convenient and safe way to enter and exit. Family members can unlock electronic locks through fingerprints, passwords, mobile phone apps and other methods without carrying traditional keys.

[0003] The electronic lock has an integrated sensor for biometric identification. When the user places a finger on the sensor, the sensor will collect the user's biometric features and compare them with the pre-stored biometric features. In the specific comparison process, it involves querying the features in the feature library. Currently, the commonly used query methods for electronic locks include linear search, binary search, Fibonacci search, and interpolation search.

[0004] The above search method has a high time complexity when there are a large number of key features, and requires a lot of time and computing resources to retrieve the key features, so the search and matching efficiency is low.

[0005] With regard to the problem of low efficiency in searching and matching key features for electronic locks in the related art, no effective solution has been proposed so far. Summary of the invention

[0006] In this embodiment, a key feature matching method, a processor, an electronic lock and a storage medium are provided to solve the problem of low efficiency of key feature search and matching in electronic locks in the related art.

[0007] In a first aspect, a key feature matching method is provided in this embodiment, comprising: When receiving an unlocking request, obtaining the currently collected target key features; Constructing a query key according to the current time information of the unlock request and the current unlock times; Determine a key feature index matching the query key from a pre-built feature index library; the key feature index is associated with the unlocking frequency corresponding to each reference key feature in a preset feature information library; the reference key feature with a higher unlocking frequency has a higher value of the corresponding key feature index; According to the key feature index matched by the query key, determining a candidate key feature sequence corresponding to the target key feature from the feature information library; the candidate key feature sequence is a sequence arranged from high to low based on the key feature index; All candidate key features in the candidate key feature sequence are sequentially compared with the target key feature to obtain a comparison result.

[0008] In some of the embodiments, constructing a query key according to the current time information of the unlock request and the current unlock times includes: Determining the pre-divided unlocking time period to which the unlocking request belongs according to the current time information of the unlocking request; A query key is constructed according to the unlocking time period and the current unlocking times of the unlocking request.

[0009] In some of the embodiments, determining a key feature index matching the query key from a pre-built feature index library includes: A key feature index whose associated unlocking frequency matches the unlocking times corresponding to the query key within the unlocking time period corresponding to the query key is determined from a pre-built feature index library.

[0010] In some embodiments, the method further comprises: In an unlocking time period within a statistical period, a corresponding time period identifier is assigned to a key feature whose unlocking frequency within the unlocking time period reaches a preset frequency threshold; According to the time period identifier, the identification information of the key feature corresponding to the key feature index is partitioned and stored, and the identification information is sorted in the corresponding partition based on the unlocking frequency within the unlocking time period.

[0011] In some embodiments, the method further comprises: In one of the unlocking time periods within one of the statistical cycles, key features whose unlocking frequency within the unlocking time period reaches a preset frequency threshold are pre-loaded into the cache to be preferentially used for feature matching query.

[0012] In some embodiments, the method further comprises: Determining whether the target key feature is matched successfully according to the comparison result; If yes, then output the unlocking instruction and calculate the cumulative number of unlocking times of the target key feature within a preset statistical period; The unlocking frequency of the target key feature in the statistical period is determined according to the accumulated unlocking times and the total unlocking times of all key features in the statistical period.

[0013] In some embodiments, the method further comprises: Identify the key features whose accumulated unlocking times satisfy the preset times decay condition within the statistical period as the key features to be processed; According to a preset attenuation rule, the key feature index of the key feature to be processed is attenuated.

[0014] In a second aspect, a processor is provided in this embodiment, including an acquisition module, a construction module, a query module, a sequence determination module, and a matching module; wherein: The acquisition module is used to acquire the currently collected target key features when receiving an unlocking request; The construction module is used to construct a query key according to the current time information of the unlocking request and the current unlocking times; The query module is used to determine the key feature index matching the query key from a pre-built feature index library; the key feature index is associated with the unlocking frequency corresponding to each reference key feature in the preset feature information library; the reference key feature with a higher unlocking frequency has a higher value of the corresponding key feature index; The sequence determination module is used to determine a candidate key feature sequence corresponding to the target key feature from the feature information library according to the key feature index matched by the query key; the candidate key feature sequence is a sequence arranged from high to low based on the key feature index; The matching module is used to sequentially compare all candidate key features in the candidate key feature sequence with the target key feature to obtain a comparison result.

[0015] In a third aspect, an electronic lock is provided in this embodiment, comprising: a biometric feature collection device, a lock switch driving device, and the processor described in the second aspect; wherein: The biometric feature collection device and the lock switch driving device are respectively connected to the processor.

[0016] In a fourth aspect, a storage medium is provided in this embodiment, on which a computer program is stored, and when the program is executed by a processor, the key feature matching method described in the first aspect is implemented.

[0017] Compared with the related art, the present embodiment provides a key feature matching method, a processor, an electronic lock and a storage medium. The key feature matching method, when receiving an unlocking request, obtains the currently collected target key feature; constructs a query key according to the current time information of the unlocking request and the current unlocking times; determines the key feature index matching the query key from the pre-constructed feature index library; the key feature index is associated with the unlocking frequency corresponding to each reference key feature in the preset feature information library; the higher the unlocking frequency of the reference key feature, the higher the value of the corresponding key feature index; according to the key feature index matched by the query key, determines the candidate key feature sequence corresponding to the target key feature from the feature information library; the candidate key feature sequence is a sequence arranged from high to low based on the key feature index; all the candidate key features in the candidate key feature sequence are sequentially compared with the target key feature to obtain the comparison result. It can realize the retrieval and comparison of key features based on the unlocking frequency, thereby reducing the number and time of search comparison and improving the efficiency of key feature search and matching.

[0018] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings: Figure 1 is a hardware structure block diagram of a terminal of the key feature matching method of this embodiment; Figure 2 is a flow chart of the key feature matching method of this embodiment; Figure 3 is a flow chart of a key feature matching method in some embodiments; Figure 4 is a structural block diagram of the processor of this embodiment; Figure 5 Schematic diagram of the structure of the electronic lock of this embodiment. DETAILED DESCRIPTION

[0020] In order to more clearly understand the purpose, technical solutions and advantages of the present application, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments.

[0021] Unless otherwise defined, the technical terms or scientific terms involved in this application shall have the general meaning understood by people with general skills in the technical field to which this application belongs. The words "one", "a", "the", "these" and the like in this application do not indicate a quantitative limitation, and they may be singular or plural. The terms "include", "comprise", "have" and any variants thereof involved in this application are intended to cover non-exclusive inclusions; for example, a process, method and system, product or device comprising a series of steps or modules (units) is not limited to the listed steps or modules (units), but may include unlisted steps or modules (units), or may include other steps or modules (units) inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" may mean: A exists alone, A and B exist at the same time, and B exists alone. Generally, the character " / " indicates that the objects associated with each other are in an "or" relationship. The terms "first", "second", "third", etc. in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0022] The method embodiment provided in this embodiment can be executed in a terminal, a computer or a similar computing device. For example, running on a terminal, Figure 1 FIG. 1 is a hardware structure diagram of a terminal of the key feature matching method of this embodiment. Figure 1 As shown, the terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 and a memory 104 for storing data, wherein the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA. The above terminal may also include a transmission device 106 and an input and output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0023] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the key feature matching method in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the terminal via a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0024] The transmission device 106 is used to receive or send data via a network. The above network includes a wireless network provided by a communication provider of the terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0025] In this embodiment, a key feature matching method is provided. Figure 2 is a flow chart of the key feature matching method of this embodiment. Figure 2 As shown, the process includes the following steps: Step S210, when receiving an unlocking request, obtaining the currently collected target key features.

[0026] Specifically, the reception of the unlock request can be confirmed when the user wakes up the electronic lock. For example, the user touches a specific area of ​​the electronic lock, places a finger on the fingerprint collection area of ​​the electronic lock, or presses a preset button. This embodiment does not specifically limit the specific operation form of the unlock request. The key features involved in this embodiment can specifically be biometric features used for unlock verification, including but not limited to fingerprint features, iris features, retinal features, and facial features. Among them, when the user wakes up the electronic lock to initiate an unlock request, the biometric feature collection device (such as a fingerprint collection module) of the electronic lock will collect the user's biometric features to obtain the above-mentioned target key features.

[0027] Optionally, the biometrics of the person with unlocking authority can be recorded in advance on the electronic lock. During the recording process, the extracted biometrics are converted into digital information for storage, and a unique identification (Identity document) corresponding to the biometric storage address is recorded, hereinafter referred to as the feature ID.

[0028] Step S220: construct a query key according to the current time information of the unlocking request and the current unlocking times.

[0029] Specifically, the query key can be constructed based on the time information corresponding to the current unlock request and the number of unlocks corresponding to the unlock request. The number of unlocks corresponding to the unlock request can be the number of unlocks initiated within a preset period of time. For example, if the current unlock request is the third unlock request initiated by the user between 8 and 9 in the morning, the query key can be constructed based on the time information from 8 to 9 in the morning and the number of unlocks of the third unlock. The specific construction form varies depending on the specific construction carrier used (for example, constructing the query key based on a hash table, constructing the query key based on a database). The query key is used to quickly determine the biometric features that need to be compared from the previously entered biometric features.

[0030] Step S230, determining a key feature index matching the query key from a pre-built feature index library; the key feature index is associated with the unlocking frequency corresponding to each reference key feature in a preset feature information library; the higher the unlocking frequency of the reference key feature, the higher the value of the corresponding key feature index.

[0031] The key feature index may specifically be an index value constructed according to the unlocking frequency corresponding to the key feature. The feature index library may be a library for storing each key feature index, for example, it may be implemented by a database or a hash table. When it is detected that a user initiates an unlocking request based on a key feature that has been previously entered, after the key feature is successfully verified, the associated unlocking frequency counter is used to update the unlocking frequency associated with the key feature, and then the key feature index is updated. The higher the unlocking frequency of a key feature, the higher the corresponding key feature index. The reference key feature is the key feature of a user who has completed information collection and entry in advance on the electronic lock and has the right to unlock.

[0032] A storage area may be allocated in a processor or server to store the key feature indexes associated with the key feature locks, and each key feature index may be associated with a feature ID of each key feature. In this way, the corresponding reference key feature may be directly located according to the key feature index that matches the query key.

[0033] The key feature index that matches the query key can be determined from the feature index library based on the content in the query key. Specifically, several key feature indexes whose unlocking frequency and unlocking time information match the query key can be searched. From the feature index library, determine the key feature index whose associated time period matches the time information corresponding to the unlocking request and whose unlocking frequency matches the current unlocking times of the unlocking request as the key feature index matched by the query key. For example, determine the matching unlocking frequency range based on the current unlocking times of the unlocking request, and then use the key feature index in the feature index library whose time period matches the current time information of the unlocking request and whose unlocking frequency falls within the unlocking frequency range as the key feature index that matches the query key.

[0034] In particular, the key feature index can also be associated with the time period, and the time period with a large number of key feature unlocking times can be associated with the key feature index. For example, the key feature index can be stored in time period partitions to match the corresponding key feature index from the corresponding time period.

[0035] Step S240, according to the key feature index matched by the query key, determine the candidate key feature sequence corresponding to the target key feature from the feature information library; the candidate key feature sequence is a sequence arranged from high to low based on the key feature index. Among them, the corresponding candidate key feature sequence can be determined according to the association relationship between the key feature index and the feature ID of the key feature. The candidate key feature sequence can be sorted from high to low according to the key feature index.

[0036] Step S250, sequentially comparing all candidate key features in the candidate key feature sequence with the target key feature to obtain a comparison result.

[0037] The currently collected target key features that need to be matched and verified are sequentially compared with all the candidate key features in the candidate key feature sequence, wherein the feature similarity can be calculated during the comparison process, and the specific feature comparison method is not limited in this embodiment. When the target key feature is determined to be one of the candidate key features based on the comparison result, it is confirmed that the target key feature verification is successful, and an unlocking instruction can be issued to unlock the door.

[0038] It can be understood that the candidate key feature sequence is the key feature sequence that is matched first. When all the candidate key features in the candidate key feature sequence are inconsistent with the target key feature, the other key features that have been entered previously but have not been compared can be read and compared with the target key feature. If all the key features that have been entered are inconsistent with the target key feature, it is confirmed that the current verification has failed.

[0039] In the related art, traditional indexing methods such as linear search are often used to compare the key features currently collected to be matched with the key features that have been recorded. When the amount of key feature data that has been recorded increases, the comparison time will increase and the comparison efficiency will decrease, which cannot quickly respond to user needs, resulting in users waiting too long for key feature verification, affecting user experience.

[0040] In this regard, this embodiment combines the key features with the unlocking frequency based on the above steps S210 to S250 to generate a corresponding index. Based on the key feature index associated with the unlocking frequency, the key features that meet the door opening frequency conditions can be quickly located, thereby reducing unnecessary search and comparison operations, and helping to quickly and accurately find records that meet specific conditions when processing large amounts of data, thereby improving the speed and accuracy of electronic lock response feature matching, improving comparison efficiency, and enhancing user experience.

[0041] Therefore, in the above steps S210 to S250, when receiving an unlocking request, the currently collected target key features are obtained; a query key is constructed according to the current time information of the unlocking request and the current unlocking times; a key feature index matching the query key is determined from a pre-constructed feature index library; the key feature index is associated with the unlocking frequency corresponding to each reference key feature in the preset feature information library; the higher the unlocking frequency of the reference key feature, the higher the value of the corresponding key feature index; according to the key feature index matched by the query key, a candidate key feature sequence corresponding to the target key feature is determined from the feature information library; the candidate key feature sequence is a sequence arranged from high to low based on the key feature index; all candidate key features in the candidate key feature sequence are sequentially compared with the target key feature to obtain a comparison result. It can realize the retrieval and comparison of key features based on the unlocking frequency, thereby reducing the number and time of search comparisons and improving the efficiency of key feature search and matching.

[0042] In one embodiment, based on the above step S220, according to the current time information of the unlocking request and the current unlocking times, constructing a query key may include: According to the current time information of the unlocking request, the pre-divided unlocking time period to which the unlocking request belongs is determined; according to the unlocking time period and the current unlocking times of the unlocking request, a query key is constructed.

[0043] In this embodiment, the segmentation can be performed in terms of time. For example, 24 hours a day can be divided into 24 unlocking time periods in units of hours. According to the time when the unlocking request is currently initiated, the unlocking time period to which the unlocking request belongs is determined. For example, if the current unlocking request is initiated at 8:30, the unlocking time period corresponding to the unlocking request can be determined as the time period from 8 to 9 o'clock. If the current unlocking request is initiated for the third time between 8 and 9 o'clock, the number of unlocking times corresponding to the unlocking request can be determined as 3. Thus, in the hash table, a query key consisting of a time period identifier and an unlocking number can be constructed in the form of "0800-0900_3". It can be understood that the composition of the query key is only an example, and can be adaptively set according to the needs of the actual application scenario. For example, in a database, the query key can be constructed in the form of a composite index containing two columns: a time period and an unlocking number.

[0044] This embodiment constructs a query key including a time period identifier and the number of unlocking times, which can facilitate subsequent searches for key features that meet the number of unlocking times condition within a specific time period.

[0045] Additionally, in one embodiment, based on the above step S230, determining the key feature index matching the query key from the pre-built feature index library may include: From the pre-built feature index library, a key feature index whose associated unlocking frequency matches the number of unlocking times corresponding to the query key within the unlocking time period corresponding to the query key is determined.

[0046] According to the time period identifier corresponding to the key feature index, the key feature index that satisfies the unlocking number condition (e.g., unlocking frequency range) determined based on the unlocking number of the query key within the unlocking time period corresponding to the query key is determined, and then the corresponding key feature is located according to the key feature index. Therefore, this embodiment can realize the rapid location of the key feature that meets the search condition, avoid unnecessary search and comparison, and thus can determine the candidate key feature from the reference key features with a large amount of data.

[0047] In one embodiment, the key feature matching method may further include: In an unlocking time period within a statistical period, a corresponding time period identifier is assigned to the key feature whose unlocking frequency within the unlocking time period reaches a preset frequency threshold; according to the time period identifier, the identification information of the key feature corresponding to the key feature index is partitioned and stored, and the identification information is sorted in the corresponding partition based on the unlocking frequency within the unlocking time period.

[0048] Among them, when it is detected that a certain key feature frequently unlocks the lock in a certain unlocking time period, a corresponding time period identifier can be assigned to the key feature. For example, if the unlocking frequency of key feature A in the time period from 10 to 11 o'clock every day for three consecutive days reaches the preset frequency threshold, the time period identifier of 10 to 11 o'clock is assigned to key feature A. Later, when the user initiates unlocking in the time period from 10 to 11 o'clock and needs to match the key feature, the key feature A can be located according to this time period identifier, so as to compare the key feature A with the collected biometric features of the user who needs to be verified.

[0049] In this embodiment, the feature IDs of all key features can also be partitioned and stored in the memory according to the associated time period identifiers. For example, the feature ID associated with the time period identifier from 10 o'clock to 11 o'clock is stored in one area, and the feature ID associated with the time period identifier from 11 o'clock to 12 o'clock is stored in another area. In each area, the keys are sorted from high to low according to the unlocking frequency.

[0050] Among them, an area can be set to store the feature ID, and a counter that records the number of unlocking times and a variable that identifies the assigned time period can be associated. For example, in C language, it can be implemented based on structures and linked lists. The key feature is associated with the feature ID, the unlocking times counter, and the time period identifier. Every time the user completes the unlocking action, the counter corresponding to the currently verified key feature will increase the count and record the corresponding door opening time period.

[0051] This embodiment can improve the efficiency of feature retrieval and matching by combining biometric features with time periods and unlocking times, so that when performing feature search, key features that meet the unlocking times condition in the corresponding time period can be quickly located, unnecessary search and comparison operations can be reduced, response speed and accuracy can be improved, and accurate positioning and screening can be achieved. In addition, feature IDs are partitioned and stored according to the associated time period identifiers, so that when an unlocking request is received in the corresponding time period, the feature ID can be directly read from the corresponding storage partition, thereby reducing the time for reading the memory.

[0052] In one embodiment, the key feature matching method may further include: In an unlocking time period within a statistical period, key features whose unlocking frequency within the unlocking time period reaches a preset frequency threshold are pre-loaded into the cache to be preferentially used for feature matching query.

[0053] For example, when the electronic lock is idle, all entered key features can be read at regular intervals, and the key features for frequent door openings in the current time period can be pre-loaded into the cache based on the unlocking frequency and time period identifiers corresponding to each key feature, so as to improve the read hit rate of the corresponding key features during subsequent feature comparisons, further speeding up frequent queries.

[0054] Additionally, in one embodiment, the key feature matching method may further include: Determine whether the target key feature matches successfully based on the comparison result; if so, output the unlocking instruction and calculate the cumulative number of unlockings of the target key feature within the preset statistical period; determine the unlocking frequency of the target key feature within the statistical period based on the cumulative number of unlockings and the total number of unlockings of all key features within the statistical period.

[0055] In calculating the unlocking frequency of the key feature, the present embodiment can increase the count based on the unlocking times counter after each successful unlocking verification, and then calculate the cumulative unlocking times of the key feature in a preset statistical period, such as a week. Then, the cumulative unlocking times of the key feature is divided by all unlocking times in the statistical period to obtain the unlocking frequency of the key feature. In this way, the present embodiment can achieve accurate statistics of the unlocking frequency of the key feature, thereby achieving detection of the unlocking feature distribution of the user.

[0056] Additionally, in one embodiment, the key feature matching method may further include: The key features whose accumulated unlocking times meet the preset times decay condition within the statistical period are identified as the key features to be processed; and the key feature index of the key features to be processed is decayed according to the preset decay rules.

[0057] For example, at the end of a statistical cycle, the number of unlocking times of each key feature is detected. If the number of unlocking times of a key feature decays and the decay condition reaches a preset number decay condition, for example, the number of unlocking times in the entire statistical cycle is 0, or the difference compared with the number of unlocking times in the previous statistical cycle reaches a preset difference threshold, then the key feature is identified as a key feature to be processed, and the key feature index of the key feature to be processed is decayed. Specifically, the key feature index can be exponentially decayed.

[0058] In this embodiment, by performing attenuation processing on the key feature index corresponding to the key feature that meets the frequency attenuation condition, the key feature index can be updated in a timely manner, thereby improving the accuracy and efficiency of retrieving suitable key features.

[0059] Figure 3 is a flow chart of a key feature matching method in some embodiments, such as Figure 3As shown, the process includes the following steps: Step S301, when it is detected that the user wakes up the electronic lock, extract the user's target key feature.

[0060] Step S302, based on the key feature index, read the candidate key feature sequence, perform feature comparison with the target key feature, and obtain a comparison result; the specific process of reading the candidate key feature sequence can refer to the above embodiment, and this step will not be repeated.

[0061] Step S303, based on the comparison result, determine whether the target key feature is successfully verified; if so, execute step S304; otherwise, execute step S305; wherein, when there is a candidate key feature that is consistent with the target key feature, it is confirmed that the target key feature is successfully verified; otherwise, the target key feature continues to be compared with other key features that have been entered but not compared. If there is no key feature that is consistent with the target key feature, it is confirmed that the target key feature verification has failed.

[0062] Step S304, recording the unlocking times and unlocking time period corresponding to the current unlocking.

[0063] Step S305, prompting the user that the unlocking verification has failed.

[0064] Step S306: re-sort the recorded key features in the corresponding storage area according to the unlocking frequency, wherein the key feature with a higher unlocking frequency is ranked higher and can obtain a higher key feature index value.

[0065] Step S307, partition and store different key features according to the time period identifier and re-order them. When receiving the unlock request next time, the key features with higher key feature index values ​​in the time period corresponding to the unlock request are read first to improve the efficiency of matching the correct key features.

[0066] Compared with traditional indexing methods, the above steps S301 to S307 can reduce the time and computing resources consumed in retrieving key features, especially for application scenarios with large amounts of data, and can improve retrieval efficiency, reduce the time users wait for unlocking verification, and improve user experience.

[0067] In this embodiment, a processor is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. The terms "module", "unit", "subunit" and the like used below can implement a combination of software and / or hardware of a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0068] Figure 4 is a structural block diagram of the processor 40 of this embodiment, such as Figure 4 As shown, the processor 40 includes: an acquisition module 41, a construction module 42, a query module 43, a sequence determination module 44 and a matching module 45; wherein: The acquisition module 41 is used to obtain the currently collected target key features when an unlocking request is received; the construction module 42 is used to construct a query key according to the current time information of the unlocking request and the current number of unlocking times; the query module 43 is used to determine the key feature index that matches the query key from a pre-constructed feature index library; the key feature index is associated with the unlocking frequency corresponding to each reference key feature in the preset feature information library; the higher the unlocking frequency of the reference key feature, the higher the value of the corresponding key feature index; the sequence determination module 44 is used to determine the candidate key feature sequence corresponding to the target key feature from the feature information library according to the key feature index matched to the query key; the candidate key feature sequence is a sequence arranged from high to low based on the key feature index; the matching module 45 is used to perform feature comparison of all candidate key features in the candidate key feature sequence with the target key feature in turn to obtain a comparison result.

[0069] In this embodiment, an electronic lock is also provided. Figure 5 is a schematic diagram of the structure of the electronic lock 50 of this embodiment, as shown in Figure 5 As shown, the electronic lock 50 includes: a biometric collection device 52, a lock switch driving device 54 and the processor 40 of the above embodiment; wherein: the biometric collection device 52 and the lock switch driving device 54 are respectively connected to the processor 40.

[0070] In this embodiment, an electronic device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0071] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0072] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program: S1, upon receiving an unlocking request, obtaining the currently collected target key features; S2, constructing a query key according to the current time information of the unlock request and the current unlock times; S3, determining a key feature index matching the query key from a pre-built feature index library; the key feature index is associated with the unlocking frequency corresponding to each reference key feature in the preset feature information library; the reference key feature with a higher unlocking frequency has a higher value of the corresponding key feature index; S4, determining a candidate key feature sequence corresponding to the target key feature from a feature information database according to the key feature index matched by the query key; the candidate key feature sequence is a sequence arranged from high to low based on the key feature index; S5, sequentially comparing all candidate key features in the candidate key feature sequence with the target key feature to obtain a comparison result.

[0073] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementation modes, and will not be repeated in this embodiment.

[0074] In addition, in combination with the key feature matching method provided in the above embodiments, a storage medium may be provided in this embodiment to implement the key feature matching method. The storage medium stores a computer program; when the computer program is executed by a processor, any key feature matching method in the above embodiments is implemented.

[0075] It should be understood that the specific embodiments described herein are only used to explain the application, rather than to limit it. Based on the embodiments provided in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the protection scope of this application.

[0076] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0077] Obviously, the drawings are only some examples or embodiments of the present application. For ordinary technicians in the field, the present application can also be applied to other similar situations based on these drawings without creative work. In addition, it is understandable that although the work done in this development process may be complicated and lengthy, for ordinary technicians in the field, certain changes in design, manufacturing or production based on the technical content disclosed in this application are only conventional technical means and should not be regarded as insufficient content disclosed in this application.

[0078] The term "embodiment" in this application refers to a specific feature, structure or characteristic described in conjunction with the embodiment that can be included in at least one embodiment of the present application. The appearance of this phrase in various locations in the specification does not necessarily mean the same embodiment, nor does it mean that it is mutually exclusive with other embodiments and is independent or optional. It is clearly or implicitly understood by those of ordinary skill in the art that the embodiments described in this application can be combined with other embodiments without conflict.

[0079] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of patent protection. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the scope of protection of the present application. Therefore, the scope of protection of the present application shall be subject to the attached claims.

Claims

1. A key feature matching method, characterized in that: include: When receiving an unlocking request, obtaining the currently collected target key features; Constructing a query key according to the current time information of the unlock request and the current unlock times; Determine a key feature index matching the query key from a pre-built feature index library; the key feature index is associated with the unlocking frequency corresponding to each reference key feature in a preset feature information library; the reference key feature with a higher unlocking frequency has a higher value of the corresponding key feature index; According to the key feature index matched by the query key, determining a candidate key feature sequence corresponding to the target key feature from the feature information library; the candidate key feature sequence is a sequence arranged from high to low based on the key feature index; All candidate key features in the candidate key feature sequence are sequentially compared with the target key feature to obtain a comparison result.

2. The key feature matching method according to claim 1, characterized in that: According to the current time information of the unlock request and the current unlock times, a query key is constructed, including: Determining the pre-divided unlocking time period to which the unlocking request belongs according to the current time information of the unlocking request; A query key is constructed according to the unlocking time period and the current unlocking times of the unlocking request.

3. The key feature matching method according to claim 2, characterized in that: Determining a key feature index matching the query key from a pre-built feature index library includes: A key feature index whose associated unlocking frequency matches the unlocking times corresponding to the query key within the unlocking time period corresponding to the query key is determined from a pre-built feature index library.

4. The key feature matching method according to claim 3, characterized in that: The method further comprises: In an unlocking time period within a statistical period, a corresponding time period identifier is assigned to a key feature whose unlocking frequency within the unlocking time period reaches a preset frequency threshold; According to the time period identifier, the identification information of the key feature corresponding to the key feature index is partitioned and stored, and the identification information is sorted in the corresponding partition based on the unlocking frequency within the unlocking time period.

5. The key feature matching method according to claim 4, characterized in that: The method further comprises: In one of the unlocking time periods within one of the statistical cycles, key features whose unlocking frequency within the unlocking time period reaches a preset frequency threshold are pre-loaded into the cache to be preferentially used for feature matching query.

6. The key feature matching method according to any one of claims 1 to 5, characterized in that: The method further comprises: Determining whether the target key feature is matched successfully according to the comparison result; If yes, then output the unlocking instruction and calculate the cumulative number of unlocking times of the target key feature within a preset statistical period; The unlocking frequency of the target key feature in the statistical period is determined according to the accumulated unlocking times and the total unlocking times of all key features in the statistical period.

7. The key feature matching method according to claim 6, characterized in that: The method further comprises: Identify the key features whose accumulated unlocking times satisfy the preset times decay condition within the statistical period as the key features to be processed; According to a preset attenuation rule, the key feature index of the key feature to be processed is attenuated.

8. A processor, characterized in that: It includes an acquisition module, a construction module, a query module, a sequence determination module and a matching module; wherein: The acquisition module is used to acquire the currently collected target key features when receiving an unlocking request; The construction module is used to construct a query key according to the current time information of the unlocking request and the current unlocking times; The query module is used to determine the key feature index matching the query key from a pre-built feature index library; the key feature index is associated with the unlocking frequency corresponding to each reference key feature in the preset feature information library; the reference key feature with a higher unlocking frequency has a higher value of the corresponding key feature index; The sequence determination module is used to determine a candidate key feature sequence corresponding to the target key feature from the feature information library according to the key feature index matched by the query key; the candidate key feature sequence is a sequence arranged from high to low based on the key feature index; The matching module is used to sequentially compare all candidate key features in the candidate key feature sequence with the target key feature to obtain a comparison result.

9. An electronic lock, characterized in that: include: A biometric feature collection device, a lock switch driving device, and a processor as claimed in claim 8; wherein: The biometric feature collection device and the lock switch driving device are respectively connected to the processor.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the key feature matching method according to any one of claims 1 to 7 are implemented.

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