CN111783058B - Biological feature recognition device and biological feature recognition method - Google Patents
Biological feature recognition device and biological feature recognition method Download PDFInfo
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- CN111783058B CN111783058B CN202010703249.4A CN202010703249A CN111783058B CN 111783058 B CN111783058 B CN 111783058B CN 202010703249 A CN202010703249 A CN 202010703249A CN 111783058 B CN111783058 B CN 111783058B
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/31—User authentication
- G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
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- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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Abstract
The application relates to the field of Internet of things and smart home, and provides biological feature recognition equipment and a biological feature recognition method. The method comprises the following steps: when the collected biological characteristics are compared with the prestored target biological characteristics according to the characteristic comparison parameters and the comparison result shows that the identification is successful, the identification type is determined according to the comparison times, and the identification success rate corresponding to part or all of the identification types is updated; if the identification success rate corresponding to the updated identification type meets the adjustment condition, adjusting the characteristic comparison parameter corresponding to the target biological characteristic; and after the new biological characteristics are collected, determining a comparison result between the new biological characteristics and the pre-stored target biological characteristics according to the adjusted characteristic comparison parameters. The biological characteristic identification method can dynamically adjust the characteristic comparison parameters of biological characteristic identification according to the individual condition of the biological characteristics of the user, optimize and adjust the rejection rate, and obtain good balance of use convenience and safety.
Description
Technical Field
The application relates to the field of Internet of things and smart home, in particular to a biological feature recognition device and a biological feature recognition method.
Background
In smart home applications, more and more devices use biometric identification technology to verify the identity of a user. Such as intelligent terminal equipment or intelligent door locks. Some intelligent terminal devices solve the problem that a user must control the intelligent terminal device by means of a remote controller by adopting a biological characteristic identification technology. The intelligent door lock adopts the biological characteristic identification technology, so that a user can open the door lock without carrying mechanical tools such as keys, cards and the like.
However, the biometric identification technology such as fingerprint has natural defects compared with keys, cards, remote controllers and the like, and firstly, the biometric characteristics are easy to change along with the change of the environment or the physiological characteristics of people, such as skin abrasion and injury, finger peeling, over-dry fingers or sweating and dampness; secondly, the biological characteristics of different people are different in definition, for example, compared with people with obvious biological characteristics, the fingerprints of heavy physical workers are worn to cause shallow lines, the fingerprints of old people have more folds and cracks, and the like. The above problems may cause some users to frequently reject biometric identification using fingerprints and the like because the biometric features are unclear, thereby limiting further popularization of biometric identification technology.
Disclosure of Invention
The embodiment of the application provides biological feature recognition equipment and a biological feature recognition method, which can dynamically adjust the rejection rate according to the individual condition of the biological feature of a user by dynamically adjusting the feature comparison parameters of biological feature recognition, and improve the use convenience.
In a first aspect, an embodiment of the present application provides a biometric apparatus, including:
the biological characteristic collector is used for collecting biological characteristics and target biological characteristics;
the memory is used for storing the target biological characteristics acquired by the biological characteristic acquisition unit, the characteristic comparison parameters corresponding to the target biological characteristics and data used for adjusting the characteristic comparison parameters;
a processor to: if the collected biological characteristics are compared with the prestored target biological characteristics according to the characteristic comparison parameters, and the comparison result is successful in identification, the identification type is determined according to the comparison times, and the identification success rate corresponding to part or all of the identification types is updated; if the identification success rate corresponding to the updated identification type meets the adjustment condition, adjusting the characteristic comparison parameter corresponding to the target biological characteristic; and after the new biological characteristics are collected, determining a comparison result between the new biological characteristics and the pre-stored target biological characteristics according to the adjusted characteristic comparison parameters.
The biological feature recognition equipment provided by the embodiment of the application can dynamically adjust the feature comparison parameters of biological feature recognition, when the acquired biological features are compared with the prestored target biological features according to the feature comparison parameters and the comparison result shows that the identification is successful, the identification types are determined according to the comparison times, and the identification success rate corresponding to part or all of the identification types is updated; if the identification success rate corresponding to the updated identification type meets the adjustment condition, adjusting the characteristic comparison parameter corresponding to the target biological characteristic; and after the new biological characteristics are collected, determining a comparison result between the new biological characteristics and the pre-stored target biological characteristics according to the adjusted characteristic comparison parameters. The biological feature recognition equipment can dynamically adjust the feature comparison parameters of biological feature recognition according to the individual biological feature condition of a user, optimize and adjust the rejection rate, and obtain good balance of use convenience and safety.
In one possible implementation, the processor is specifically configured to:
if the comparison times are one time, the determined identification type is successful in one-time identification; or if the comparison times are more than one time, the determined identification type is that the multiple identification is successful; the comparison times are determined by the following method:
if the comparison result of the last comparison adjacent to the comparison is successful in identification, or the time interval between the comparison and the last comparison adjacent to the comparison is greater than a set time interval value, determining that the comparison times are once; alternatively, the first and second electrodes may be,
if the comparison result of the last comparison adjacent to the comparison is identification failure and the time interval between the comparison and the last comparison adjacent to the comparison is less than or equal to a set time interval value, determining the comparison times according to the total comparison times from the first comparison to the comparison;
the first comparison refers to comparison that when the last comparison is traversed forward from the comparison, the first comparison result which is found is identification failure, and the comparison result of the adjacent previous comparison is identification success or the time interval between the adjacent previous comparison and the previous comparison is larger than a set time interval value.
In the biometric identification device provided in this embodiment, when the acquired biometric is compared with the pre-stored target biometric according to the feature comparison parameter and the comparison result is that identification is successful, if the comparison is performed once, the determined identification type is that the identification is successful; or if the comparison times are more than one time, the determined identification type is that the multiple identification is successful. If the comparison result of the last comparison adjacent to the comparison is identification failure and the time interval between the comparison and the last comparison adjacent to the comparison is less than or equal to a set time interval value, determining the comparison times according to the total comparison times from the first comparison to the comparison; otherwise, determining the comparison times as one time. The device can reduce the operation amount of the biological feature recognition device and save the computing resource of the biological feature recognition device.
In one possible implementation, the processor is specifically configured to:
if the comparison times are one time, updating the total identification times of one-time successful identification according to the comparison times, or if the comparison times are more than one time, updating the total identification times of multiple-time successful identification according to the comparison times;
and determining the one-time identification success rate corresponding to the one-time identification success according to the total identification times of the one-time identification success and the total identification times of the multiple-time identification success.
In the biometric device provided in this embodiment, when the collected biometric characteristic is compared with the pre-stored target biometric characteristic according to the characteristic comparison parameter and the comparison result indicates that the identification is successful, the total identification frequency for which the one-time identification is successful or the total identification frequency for which the multiple-time identification is successful is selectively updated according to the comparison frequency, so that the one-time identification success rate corresponding to the one-time identification success is determined. The device selectively updates the total identification times of successful one-time identification or the total identification times of successful multiple-time identification according to the comparison times only when the identification is successful, and further updates the one-time identification success rate corresponding to the successful one-time identification, so that the operation amount of the biological feature identification device can be reduced, and the calculation resources of the biological feature identification device can be saved.
In one possible implementation, the processor is specifically configured to:
determining the total effective identification times corresponding to the target biological characteristics, wherein the total effective identification times are the sum of the total identification times of successful identification of one time and the total identification times of successful identification of multiple times;
and taking the ratio of the total identification times of the one-time successful identification to the total effective identification times as the one-time successful identification success rate corresponding to the one-time successful identification.
The biometric feature recognition device provided in this embodiment determines a total number of valid recognition times corresponding to the target biometric feature, where the total number of valid recognition times is a sum of the total number of successful recognition times for the first time and the total number of successful recognition times for the multiple times; and taking the ratio of the total identification times of successful primary identification to the total effective identification times as the primary identification success rate corresponding to the successful primary identification. When the equipment calculates the primary recognition success rate, the attention point is placed in the range of the total effective recognition times, so that the primary recognition success rate can reflect the use convenience of the biological feature recognition equipment more truly, the unreasonable influence of the artificial malicious attempt on the primary recognition success rate by biological feature recognition is avoided, and the use safety is ensured.
In a possible implementation manner, the feature comparison parameter includes a similarity threshold between the acquired biological feature and a pre-stored target biological feature; the processor is specifically configured to:
if the primary identification success rate is greater than or equal to a preset maximum threshold, increasing the similarity threshold;
and if the primary identification success rate is less than or equal to a preset minimum threshold, reducing the similarity threshold.
In the biometric device provided in this embodiment, the feature comparison parameter includes a similarity threshold between the acquired biometric feature and a pre-stored target biometric feature; if the primary identification success rate is greater than or equal to a preset maximum threshold, increasing the similarity threshold; and if the primary identification success rate is less than or equal to the preset minimum threshold, reducing the similarity threshold. When the similarity threshold is increased, the device improves the comparison threshold of the characteristic value, enables the success rate of primary recognition to be downlink, improves the probability of occurrence of the false recognition, improves the false recognition rate and improves the use safety; on the contrary, when the similarity threshold is reduced, the characteristic value comparison threshold is reduced, so that the one-time identification success rate is increased, the probability of the occurrence of the false rejection is reduced, the false rejection rate is reduced, and the use convenience is improved. After the new biological characteristics are collected, the comparison result of the new biological characteristics and the pre-stored target biological characteristics is determined according to the adjusted similarity threshold, and the use convenience is improved and the use safety is ensured by dynamically adjusting the similarity threshold.
In one possible implementation, the feature comparison parameters include the number of compared feature points; the processor is specifically configured to:
if the one-time identification success rate is larger than or equal to a preset maximum threshold value, increasing the number of the compared feature points;
and if the one-time identification success rate is less than or equal to a preset minimum threshold, reducing the number of the compared feature points.
In the biometric device provided in this embodiment, the feature comparison parameter includes the number of feature points of comparison between the acquired biometric feature and the pre-stored target biometric feature; if the one-time identification success rate is greater than or equal to a preset maximum threshold value, increasing the number of the compared feature points; and if the one-time identification success rate is less than or equal to the preset minimum threshold, reducing the number of the compared feature points. When the number of the compared characteristic points is increased, the equipment improves the comparison threshold of the characteristic values, enables the success rate of primary identification to be downlink, improves the probability of occurrence of false positives, improves the false negatives rate and improves the use safety; on the contrary, when the number of the compared feature points is reduced, the feature value comparison threshold is reduced, so that the one-time identification success rate is increased, the probability of the occurrence of the false rejection is reduced, the false rejection rate is reduced, and the use convenience is improved. After the new biological characteristics are collected, the comparison result of the new biological characteristics and the pre-stored target biological characteristics is determined according to the number of the adjusted compared characteristic points, and the number of the compared characteristic points is dynamically adjusted, so that the use convenience is improved, and the use safety is further ensured.
In a second aspect, an embodiment of the present application provides a biometric identification method, including:
if the collected biological characteristics are compared with the prestored target biological characteristics according to the characteristic comparison parameters and the comparison result is successful in identification, determining identification types according to the comparison times and updating the identification success rate corresponding to part or all of the identification types;
if the identification success rate corresponding to the updated identification type meets the adjustment condition, adjusting the characteristic comparison parameter corresponding to the target biological characteristic;
and after the new biological characteristics are collected, determining a comparison result between the new biological characteristics and the pre-stored target biological characteristics according to the adjusted characteristic comparison parameters.
In one possible implementation, the identification type includes one-time identification success and multiple-time identification success; the determining the identification type according to the comparison times comprises the following steps:
if the comparison times are one time, the determined identification type is successful in one-time identification; or if the comparison times are more than one time, the determined identification type is that the multiple identification is successful; the comparison times are determined by the following method:
if the comparison result of the last comparison adjacent to the comparison is successful in identification, or the time interval between the comparison and the last comparison adjacent to the comparison is greater than a set time interval value, determining that the comparison times are once; alternatively, the first and second electrodes may be,
if the comparison result of the last comparison adjacent to the comparison is identification failure and the time interval between the comparison and the last comparison adjacent to the comparison is less than or equal to a set time interval value, determining the comparison times according to the total comparison times from the first comparison to the comparison;
the first comparison refers to comparison that when the last comparison is traversed forward from the comparison, the first comparison result which is found is identification failure, and the comparison result of the adjacent previous comparison is identification success or the time interval between the adjacent previous comparison and the previous comparison is larger than a set time interval value.
In a possible implementation manner, the updating the recognition success rate corresponding to part or all of the recognition types includes:
if the comparison times are one time, updating the total identification times of one-time successful identification according to the comparison times, or if the comparison times are more than one time, updating the total identification times of multiple-time successful identification according to the comparison times;
and determining the one-time identification success rate corresponding to the one-time identification success according to the total identification times of the one-time identification success and the total identification times of the multiple-time identification success.
In a possible implementation manner, the determining, according to the total number of successful identifications of the first identification and the total number of successful identifications of the multiple identifications, a first identification success rate corresponding to the first identification success includes:
determining the total effective identification times corresponding to the target biological characteristics, wherein the total effective identification times are the sum of the total identification times of successful identification of one time and the total identification times of successful identification of multiple times;
and taking the ratio of the total identification times of the one-time successful identification to the total effective identification times as the one-time successful identification success rate corresponding to the one-time successful identification.
The technical effect brought by any implementation manner of the second aspect may be referred to the technical effect brought by the implementation manner of the first aspect, and is not described herein again.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is an external view schematic diagram of an intelligent lock according to an embodiment of the present application;
fig. 2 is a block diagram of an intelligent lock according to an embodiment of the present disclosure;
FIG. 3 illustrates an ROC curve for biometric identification provided by an embodiment of the present application;
fig. 4 is an external schematic view of a terminal device according to an embodiment of the present application;
fig. 5 is a block diagram of a terminal device according to an embodiment of the present disclosure;
fig. 6 is a schematic flowchart of a biometric identification method according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be described in further detail with reference to the accompanying drawings, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In the application process of the existing biometric identification technology, some users often have recognition refusal due to unclear biometric features and use of biometric identification such as fingerprints, and the existing biometric identification technology cannot be used, so that the further popularization of the biometric identification technology is limited. Based on this, the embodiment of the application provides a biological feature recognition device and a biological feature recognition method. When the comparison result is that the identification is successful, the identification type is determined according to the comparison times, and the identification success rate corresponding to part or all of the identification types is updated; if the identification success rate corresponding to the updated identification type meets the adjustment condition, adjusting the characteristic comparison parameter corresponding to the target biological characteristic; and after the new biological characteristics are collected, determining a comparison result between the new biological characteristics and the pre-stored target biological characteristics according to the adjusted characteristic comparison parameters. The biological feature recognition equipment can dynamically adjust the feature comparison parameters of biological feature recognition according to the individual biological feature condition of a user, optimize and adjust the rejection rate, and obtain good balance of use convenience and safety.
The biometric device in the embodiment of the present application refers to a terminal device that has various biometric application programs installed, including biometric application of the terminal device itself and third-party biometric application. In some embodiments, the terminal device is further capable of displaying an object provided in the installed biometric application. The terminal device may be mobile or stationary. For example, a mobile phone, a tablet computer, a vehicle-mounted device, a Personal Digital Assistant (PDA), a Point Of Sales (POS), a smart lock, or other terminal devices capable Of implementing the above functions.
In order to make the objects, technical solutions and advantages of the embodiments of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings, and it is to be understood that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that, in the embodiment of the present application, the biometric device may be a portable device such as a smart phone or a tablet computer; it can also be an intelligent lock, such as a fingerprint electronic lock. The following embodiments of the present application take a biometric device as an example of a fingerprint electronic lock. The fingerprint electronic lock is taken as an example to illustrate the technical solution of the embodiment of the present application more clearly, and does not limit the technical solution provided by the embodiment of the present application, and it can be known by those skilled in the art that the technical solution provided by the embodiment of the present application is also applicable to similar technical problems with the occurrence of new application scenarios.
In one embodiment, the biometric device is an intelligent lock, the biometric collector of the intelligent lock is a fingerprint collector, and the biometric identified by the intelligent lock is a fingerprint. Fig. 1 shows an appearance diagram of an intelligent lock according to an embodiment of the present application, and as can be seen from the appearance diagram shown in fig. 1, the intelligent lock includes a biometric collector, which may be a fingerprint collector 106. The fingerprint collector 106 is used for collecting fingerprints and target fingerprints. In the using process of the household, the intelligent lock collects fingerprints through the fingerprint collector and compares the fingerprints with stored target fingerprints, and when the comparison result is that the identification is successful, the intelligent lock is opened; otherwise, the door lock cannot be opened.
Fig. 2 shows a block diagram of an intelligent lock according to an embodiment of the present application, and referring to fig. 2, the intelligent lock 100 according to the embodiment of the present application includes: a processor 101, a fingerprint sampler 102, a memory 103, and a bus 104; the processor 101, the memory 103 and the fingerprint acquirer 102 are all connected through a bus 104, and the bus 104 is used for transmitting data among the processor 101, the memory 103 and the fingerprint acquirer 102.
The memory 103 may be configured to store software programs and modules, such as program instructions/modules corresponding to the biometric identification method in the embodiment of the present application, and the processor 101 executes various functional applications and data processing of the smart lock 100, such as the biometric identification method provided in the embodiment of the present application, by running the software programs and modules stored in the memory 103. The memory 103 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program of at least one application, and the like; the storage data area may store data created according to the usage of the smart lock 100 (such as the target biological characteristics collected by the fingerprint collector 102, the characteristic comparison parameters corresponding to the target biological characteristics, and data for adjusting the use of the characteristic comparison parameters), and the like. Further, the memory 103 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.
The processor 101 is the control center of the intelligent lock 100, connects the various parts of the entire intelligent lock 100 using the bus 104 and various interfaces and lines, and performs various functions of the intelligent lock 100 and processes data by running or executing software programs and/or modules stored in the memory 103 and calling up data stored in the memory 103. Alternatively, processor 101 may include one or more processing units, such as a CPU, GPU, digital processing unit, etc.
The fingerprint acquirer 102 is mainly used to obtain the target biometric characteristic and the biometric characteristic of the user. In some embodiments, the smart lock 100 further includes other structural elements, such as possibly a display, a communication module, and the like. The processor 101 may present the biometric associated information via a display. The processor 101 may also be connected to a network via a communication module to obtain a target biometric characteristic, etc. The present application is not particularly limited in contrast.
In an alternative embodiment, the smart lock 100 includes:
a fingerprint collector 102 for collecting biological characteristics and target biological characteristics;
the memory 103 is used for storing the target fingerprint acquired by the intelligent lock 100, the feature comparison parameter corresponding to the target fingerprint and data used for adjusting the feature comparison parameter;
a processor 101 for: if the acquired fingerprint is compared with the prestored target fingerprint according to the characteristic comparison parameter, and the comparison result is successful in identification, determining the identification type according to the comparison times, and updating the identification success rate corresponding to part or all of the identification types; if the identification success rate corresponding to the updated identification type meets the adjustment condition, adjusting the characteristic comparison parameter corresponding to the target fingerprint; and after a new fingerprint is acquired, determining a comparison result of the new fingerprint and a prestored target fingerprint according to the adjusted characteristic comparison parameter.
Illustratively, the biometric captured by the smart lock is a fingerprint. The intelligent lock can dynamically adjust the feature comparison parameters of fingerprint identification, the feature comparison parameters can be fingerprint comparison similarity threshold values and also can be fingerprint comparison sampling numbers, and the probability of rejection occurrence can be reduced by loosening the fingerprint comparison similarity threshold values or reducing the fingerprint comparison sampling numbers. When the acquired fingerprint is compared with a prestored target fingerprint according to the characteristic comparison parameter and the comparison result is successful in identification, determining an identification type according to the comparison times and updating the identification success rate corresponding to part or all of the identification types; if the identification success rate corresponding to the updated identification type meets the adjustment condition, adjusting the characteristic comparison parameter; and after the new fingerprint is acquired, determining a comparison result of the new fingerprint and the pre-stored target fingerprint according to the adjusted characteristic comparison parameter. The intelligent lock can dynamically adjust the characteristic comparison parameters of biological characteristic identification according to the individual biological characteristic conditions of a user, optimize and adjust the rejection rate, and obtain good balance of use convenience and safety.
In some embodiments, the identification type includes one identification success and multiple identification successes.
In some embodiments, the processor 101 adjusts the recognition success rate for a successful recognition pair, and in other embodiments, the processor 101 may also adjust the recognition success rate for a successful recognition pair and the recognition success rate for multiple recognition pairs at the same time. In the following embodiments of the present application, the technical solutions are described by taking an example of an identification success rate for the processor 101 to adjust a pair of successful identification.
In an alternative embodiment, the identification type includes one identification success and a plurality of identification successes; the processor 101 is specifically configured to:
if the comparison times is one time, the determined identification type is successful in one-time identification; or if the comparison times are more than one time, the determined identification type is that the multiple identification is successful;
the number of alignments was determined by the following method:
if the comparison result of the last comparison adjacent to the comparison is successful in identification, or the time interval between the comparison and the last comparison adjacent to the comparison is greater than a set time interval value, determining the comparison times as one time; alternatively, the first and second electrodes may be,
if the comparison result of the last comparison adjacent to the comparison is identification failure and the time interval between the comparison and the last comparison adjacent to the comparison is less than or equal to the set time interval value, determining the comparison times according to the total comparison times from the first comparison to the comparison;
the first comparison refers to the comparison that when the previous comparison is started to be traversed forward one by one from the previous comparison, the found first matching result is identification failure, and the comparison result of the adjacent previous comparison is identification success or the time interval between the adjacent previous comparison and the previous comparison is larger than a set time interval value.
Illustratively, the smart lock 100 is preset with a set time interval value as the timeout time, for example, the set time interval value is 5 minutes. When a fingerprint with the sequence number of Nth time is input (N is more than or equal to 2), if the comparison result is successful in identification, if the comparison result of the last N-1 comparison adjacent to the Nth comparison is successful in identification, or the time interval between the Nth comparison and the last N-1 comparison adjacent to the Nth comparison is more than a set time interval value for 5 minutes, determining the comparison time Q as one time; when a fingerprint with the Nth time serial number is input, if the comparison result is unsuccessful and the comparison result of the previous (N-1) comparison adjacent to the Nth fingerprint is successful in identification or the time interval between the Nth and the previous (N-1) comparison adjacent to the Nth fingerprint is more than 5 minutes, the fingerprint comparison with the comparison result which is unsuccessful in inputting again within 5 minutes from the Nth comparison is regarded as the same fingerprint identification until the fingerprint comparison with the Mth time serial number with the first comparison result which is successful in identification occurs (M & gtN). The Nth comparison is the first comparison of the fingerprint identification. The fingerprint comparison times from Nth time to Mth time are all counted into the comparison time Q of the fingerprint identification time. The comparison times Q are determined according to the following formula:
Q＝M-N+ 1
when the collected fingerprint is compared with a prestored target fingerprint according to the characteristic comparison parameter and the comparison result is successful, determining the identification type according to the comparison times: if the comparison times is 1 time, determining that the identification type is successful in one-time identification; or if the comparison times are more than 1, determining that the identification type is successful in multiple identification.
For the determination of the successful first comparison for multiple identifications, the Nth fingerprint comparison is determined as the first comparison in a mode of continuously monitoring the comparison result of each fingerprint comparison from front to back and the time interval of the comparison with the previous fingerprint in some embodiments; in some other embodiments, the determination is made by traversing from the current mth comparison onward when the comparison result of the fingerprint comparison is detected as identifying a successful mth comparison: and when the previous comparison is traversed from the Mth comparison pair forward one by one, the found first comparison result meeting the identification failure is the comparison of the Nth time, and the comparison result of the adjacent previous comparison is the identification success or the comparison of the Nth time with the sequence number of which the time interval between the adjacent previous comparison and the previous comparison is larger than the set time interval value is carried out.
In some embodiments, when the number of input fingerprint recognition errors exceeds the error number limit (e.g., 5) within the timeout period, the fingerprint recognition input of the smart lock 100 is locked for a certain time (e.g., 5 minutes), and the locking period is inoperable to prevent malicious attempts to unlock the lock.
In some embodiments, if no input is continuously performed within 5 minutes from the nth fingerprint comparison or no input of a fingerprint with a successful identification result is detected, the comparison time Q is cleared.
In an alternative embodiment, the processor 101 is specifically configured to:
if the comparison times are one, updating the total identification times of one-time successful identification according to the comparison times, or if the comparison times are more than one, updating the total identification times of multiple-time successful identification according to the comparison times;
and determining the one-time identification success rate corresponding to the one-time identification success according to the total identification times of the one-time identification success and the total identification times of the multiple-time identification success.
Illustratively, T1 is the total number of identifications that were successful for one identification, and T2 is the total number of identifications that were successful for multiple identifications. And if the acquired fingerprint is compared with the prestored target fingerprint according to the characteristic comparison parameter and the comparison result is successful in identification, updating the value of T1 or T2 according to the determined comparison times Q, and then determining the one-time identification success rate corresponding to the one-time successful identification according to the total identification times T1 of the one-time successful identification and the total identification times T2 of the multiple-time successful identification.
For example, when a fingerprint of a person is recorded, the person opens the door once, the fingerprint identification is successfully input for the first time, the door lock is opened, and the T1 times are increased by 1 time. Opening the door for another time, continuously inputting for 3 times, failing in the previous 2 times, and not opening the door lock; successful 3 rd time, door lock opened, at which time T2 times was added 3 times. And the door is opened once, the input is continuously performed for 5 times by using the input finger, the identification is wrong, the door lock is not opened, and the counts of T1 and T2 are not changed at the moment.
In an alternative embodiment, the processor 101 is specifically configured to:
determining the total effective identification times corresponding to the target fingerprint, wherein the total effective identification times are the sum of the total identification times of successful primary identification and the total identification times of successful secondary identification;
and taking the ratio of the total identification times of successful primary identification to the total effective identification times as the primary identification success rate corresponding to the successful primary identification.
Defining the success rate of one-time identification as R, and defining the total number of valid identifications corresponding to the target fingerprint as the sum of the total identification number T1 of one-time successful identification and the total identification number T2 of multiple successful identifications. The value of R can be determined according to the following formula:
wherein: r is the success rate of primary identification;
t1 is the total number of successful identifications for one identification;
t2 is the total number of successful identifications of multiple identifications.
In some embodiments, the smart lock 100 may calculate the success rate of one-time recognition of each of the plurality of users, and the determination that the value is the smallest among the success rates of one-time recognition of each user is the success rate of one-time recognition of the plurality of users.
In an alternative embodiment, the feature comparison parameter includes a similarity threshold between the collected fingerprint and a pre-stored target fingerprint; the processor 101 is specifically configured to:
if the primary identification success rate is greater than or equal to a preset maximum threshold, increasing a similarity threshold;
and if the primary recognition success rate is less than or equal to the preset minimum threshold, reducing the similarity threshold.
Fig. 3 is a Receiver Operator Characteristic (ROC) Curve of biometric identification used in some embodiments of the present application, from which a relationship between a rejection rate and a false recognition rate can be seen, and when a value of any one of an FRR (false rejection rate) or a FAR (false acceptance rate) is determined, a value of another parameter can be obtained according to the ROC Curve. The higher rejection rate can seriously affect the use experience of the user, and the characteristic comparison parameter has close relation with the rejection rate. The rejection rate can be reduced by relaxing the characteristic comparison parameters, so that the user experience is improved, but the reduction of the rejection rate can lead to the improvement of the false recognition rate, the false recognition rate is high, the safety of products can be influenced, and fingerprints which should not be matched are taken as matched fingerprints.
The maximum threshold RH of the primary recognition success rate corresponds to the lower limit value of the characteristic comparison parameter and corresponds to the lower limit value of the rejection rate FRR of the intelligent lock, and the false recognition rate FAR is at a high level at the moment; the minimum threshold RL of the primary identification success rate corresponds to the upper limit value of the characteristic comparison parameter and corresponds to the upper limit value of the rejection rate FRR of the intelligent lock, and the false identification rate FAR is at a low level at the moment. According to the ROC curve, the minimum rejection rate FRRL corresponds to the maximum allowable error rate of the product, namely FARH, which is generally determined according to the industry standard or the product standard, for example, the error rate is required to be less than or equal to 0.001% in GA701-2007 general technical conditions for fingerprint lock anti-theft locks, that is, the error rate is required to be less than or equal to 0.001%. The minimum rejection rate FRRL which can be tolerated by the product can be determined through an ROC curve according to the numerical value of FARH, and the minimum rejection rate FRRL which can be tolerated by the intelligent lock is related to the minimum similarity which can be tolerated by the intelligent lock. If the primary recognition success rate R is greater than or equal to the preset maximum threshold RH, the safety is low, and the purpose of reducing the primary recognition success rate R and improving the safety is achieved by increasing the similarity threshold; if the primary identification success rate R is smaller than or equal to the preset minimum threshold RL, the use convenience is low, and the purposes of improving the primary identification success rate R and improving the use convenience are achieved by reducing the similarity threshold. Through the dynamic adjustment of the similarity threshold, the good combination of use convenience and safety is achieved.
Optionally, the increasing or decreasing of the similarity threshold is performed according to a preset similarity step value. In some embodiments, the initial value of the similarity is a similarity value determined according to the ROC curve when the initial rejection rate FRR0 of the smart lock is 1%. In some embodiments, the similarity step value is set to 10% of the initial value of similarity; in other embodiments, the similarity step value is set to 10% of the real-time similarity before adjustment.
In some embodiments, the processor 101 is further configured to: and if the similarity threshold is lower than the minimum similarity which can be tolerated by the intelligent lock, adjusting the similarity threshold to the minimum similarity which can be tolerated by the intelligent lock.
In an alternative embodiment, the feature alignment parameters include the number of aligned feature points; the processor 101 is specifically configured to:
if the one-time identification success rate is greater than or equal to a preset maximum threshold value, increasing the number of the compared feature points;
and if the one-time identification success rate is less than or equal to the preset minimum threshold, reducing the number of the compared feature points.
The success rate of one-time recognition is adjusted by dynamically adjusting the number of the feature points, the concept of the technical scheme is similar to that of the similarity value through dynamic adjustment, and the process is not repeated herein.
In some other embodiments, the biometric device of the present application is a terminal device. For example, to facilitate understanding, fig. 4 shows an appearance schematic diagram of a terminal device provided in the embodiment of the present application, and as shown in fig. 4, the terminal device has a biometric characteristic collector 255, and the biometric characteristic collector 255 included may be a touch screen. For convenience of explanation, only the parts related to the embodiments of the present application are shown, and specific technical details are not disclosed, so that reference may be made to the parts of the embodiments of the smart lock of the present application. The terminal equipment can be any terminal equipment including a tablet computer, a vehicle-mounted computer, a PC and the like.
Fig. 5 is a block diagram schematically showing the structure of the terminal device 200 in the embodiment. As shown in fig. 5, the terminal device 200 includes: communication component 210, memory 220, display unit 230, camera 240, sensor 250, biometric acquisition 255, audio circuitry 260, bluetooth module 270, processor 280, and power supply 290.
The communication component 210 may include, but is not limited to, an antenna, at least one amplifier, a transmitter, a receiver, a signal listener, which may be one of the receivers, a coupler, a low noise amplifier, a duplexer, and the like.
In some embodiments, the communication component 210 may include RF (radio frequency) circuitry for receiving and transmitting signals during the transmission and reception of information or calls, and the like.
In other embodiments, the communication component 210 may further include a WiFi (Wireless Fidelity) module, the WiFi module belongs to short-distance Wireless transmission technology, and the terminal device 200 may help the user to send and receive information, browse web pages, view free-viewpoint video, access streaming media, and the like through the WiFi module, which provides the user with Wireless broadband internet access. It is understood that the WiFi module is not an essential component of the communication component 210 and may be omitted entirely as needed within the scope of not changing the nature of the application.
In one aspect, the display unit 230 may be used to receive input numeric or character information, generate signal inputs related to user settings and function control of the terminal device 200; on the other hand, the display unit 230 may also be used to display a Graphical User Interface (GUI) of information input by the User or information provided to the User and various menus of the terminal apparatus 200. Specifically, the display unit 230 may include a display screen 232 disposed on the front surface of the terminal device 200. The display screen 232 may be configured in the form of a liquid crystal display, a light emitting diode, or the like. The display unit 230 may be used to display the associated information of biometric identification in the present application.
The touch panel 231 may be covered on the display screen 232, or the touch panel 231 and the display screen 232 may be integrated to implement the input and output functions of the terminal device 200, and after the integration, the touch panel may be referred to as a touch display screen for short.
The camera 240 may be used to capture still images or video. The number of the cameras 240 may be one or plural. The object generates an optical image through the lens and projects the optical image to the photosensitive element. The photosensitive element may be a Charge Coupled Device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The light sensing elements convert the light signals into electrical signals which are then passed to a processor 280 for conversion into digital image signals.
The terminal device 200 may further comprise at least one sensor 250, such as an acceleration sensor 251, a distance sensor 252, a fingerprint sensor 253, a temperature sensor 254. The terminal device 200 may also be configured with other sensors such as a gyroscope, barometer, hygrometer, thermometer, infrared sensor, light sensor, motion sensor, and the like. The biometric collector 255 is used to collect target biometrics and biometrics monitored during use.
The audio circuitry 260, speaker 261, and microphone 262 may provide an audio interface between the user and the terminal device 200. The audio circuit 260 may transmit the electrical signal converted from the received audio data to the speaker 261, and convert the electrical signal into a sound signal by the speaker 261 and output the sound signal. The terminal device 200 may be further provided with a volume button for adjusting the volume of the sound signal. On the other hand, the microphone 262 converts the collected sound signals into electrical signals, which are received by the audio circuit 260 and converted into audio data, which are then output to the communication component 210 for transmission to, for example, another terminal device, or to the memory 220 for further processing.
The bluetooth module 270 is used for information interaction with other bluetooth devices having bluetooth modules through a bluetooth protocol. For example, the terminal device 200 may establish a bluetooth connection with a wearable electronic device (e.g., a smart watch) also equipped with a bluetooth module through the bluetooth module 270, so as to perform data interaction.
The processor 280 is a control center of the terminal device 200, connects various parts of the entire terminal device using various interfaces and lines, and performs various functions of the terminal device 200 and processes data by running or executing software programs stored in the memory 220 and calling data stored in the memory 220. In some embodiments, processor 280 may include one or more processing units; the processor 280 may also integrate an application processor, which primarily handles operating systems, user interfaces, applications, etc., and a baseband processor, which primarily handles wireless communications. It will be appreciated that the baseband processor described above may not be integrated into the processor 280. The processor 280 may run an operating system, an application program, a user interface display, a touch response, and the biometric identification method of the embodiments of the present application. Further, the processor 280 is coupled with the display unit 230.
Based on the same inventive concept as the biometric identification device provided in the above embodiment, the embodiment of the present application further provides a biometric identification method, and fig. 6 is a schematic flow chart of the method. As shown in fig. 6, the biometric method includes:
and S601, monitoring and collecting the biological characteristics.
Step S602, comparing the collected biological characteristics with the pre-stored target biological characteristics according to the characteristic comparison parameters.
Step S603, determining whether the comparison result is successful. If yes, sequentially executing step S604 and step S605; if not, the process returns to step S601.
And step S604, determining the identification type according to the comparison times.
Step S605, the recognition success rate corresponding to part or all of the recognition types is updated.
Step S606, determining that the identification success rate corresponding to the updated identification type satisfies the adjustment condition. If yes, go to step S607; if not, the process returns to step S601.
Step S607, adjusting the feature comparison parameter corresponding to the target biological feature.
Step S608, after acquiring the new biological feature, determining a comparison result between the new biological feature and the pre-stored target biological feature according to the adjusted feature comparison parameter.
Illustratively, the method comprises: if the acquired fingerprint is compared with the prestored target fingerprint according to the characteristic comparison parameter, and the comparison result is successful in identification, determining the identification type according to the comparison times, and updating the identification success rate corresponding to part or all of the identification types; if the identification success rate corresponding to the updated identification type meets the adjustment condition, adjusting the characteristic comparison parameter corresponding to the target fingerprint; and after a new fingerprint is acquired, determining a comparison result of the new fingerprint and a prestored target fingerprint according to the adjusted characteristic comparison parameter.
In an alternative embodiment, the identification type includes one identification success and a plurality of identification successes; step S604, determining the identification type according to the comparison times, including:
if the comparison times is one time, the determined identification type is successful in one-time identification; or if the comparison times are more than one time, the determined identification type is that the multiple identification is successful.
The number of alignments was determined by the following method:
if the comparison result of the last comparison adjacent to the comparison is successful in identification, or the time interval between the comparison and the last comparison adjacent to the comparison is greater than the set time interval value, determining the comparison times as one time; or, if the comparison result of the last comparison adjacent to the comparison is identification failure and the time interval between the comparison and the last comparison adjacent to the comparison is less than or equal to the set time interval value, determining the comparison times according to the total comparison times from the first comparison to the comparison.
Wherein, the first comparison means that when the previous comparison is traversed forward one by one from the comparison of this time, the first one found satisfies: the comparison result is identification failure, and the comparison result of the adjacent previous comparison is identification success or comparison with the time interval between the adjacent previous comparison larger than a set time interval value.
In an alternative embodiment, in step S605, updating the recognition success rate corresponding to part or all of the recognition types includes: the method comprises the following steps:
step S6051, if the comparison times is one time, updating the total identification times of one-time successful identification according to the comparison times, or if the comparison times is more than one time, updating the total identification times of multiple-time successful identification according to the comparison times;
step S6052, determining a primary identification success rate corresponding to the primary identification success according to the total identification times of the primary identification success and the total identification times of the multiple identification successes.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (8)
1. A biometric identification device, comprising:
the biological characteristic collector is used for collecting biological characteristics and target biological characteristics;
the memory is used for storing the target biological characteristics acquired by the biological characteristic acquisition unit, the characteristic comparison parameters corresponding to the target biological characteristics and data used for adjusting the characteristic comparison parameters;
a processor to: if the collected biological characteristics are compared with the prestored target biological characteristics according to the characteristic comparison parameters, and the comparison result is successful in identification, the identification type is determined according to the comparison times, and the identification success rate corresponding to part or all of the identification types is updated; if the identification success rate corresponding to the updated identification type meets the adjustment condition, adjusting the characteristic comparison parameter corresponding to the target biological characteristic; after acquiring a new biological characteristic, determining a comparison result of the new biological characteristic and a prestored target biological characteristic according to the adjusted characteristic comparison parameter;
the identification type comprises one-time identification success and multiple-time identification success; the processor is specifically configured to:
if the comparison times are one time, the determined identification type is successful in one-time identification; or if the comparison times are more than one time, the determined identification type is that the multiple identification is successful; the comparison times are determined by the following method:
if the comparison result of the last comparison adjacent to the comparison is successful in identification, or the time interval between the comparison and the last comparison adjacent to the comparison is greater than a set time interval value, determining that the comparison times are once; alternatively, the first and second electrodes may be,
if the comparison result of the last comparison adjacent to the comparison is identification failure and the time interval between the comparison and the last comparison adjacent to the comparison is less than or equal to a set time interval value, determining the comparison times according to the total comparison times from the first comparison to the comparison;
the first comparison refers to comparison that when the last comparison is traversed forward from the comparison, the first comparison result which is found is identification failure, and the comparison result of the adjacent previous comparison is identification success or the time interval between the adjacent previous comparison and the previous comparison is larger than a set time interval value.
2. The biometric identification device of claim 1, wherein the processor is specifically configured to:
if the comparison times are one time, updating the total identification times of one-time successful identification according to the comparison times, or if the comparison times are more than one time, updating the total identification times of multiple-time successful identification according to the comparison times;
and determining the one-time identification success rate corresponding to the one-time identification success according to the total identification times of the one-time identification success and the total identification times of the multiple-time identification success.
3. The biometric identification device of claim 2, wherein the processor is specifically configured to:
determining the total effective identification times corresponding to the target biological characteristics, wherein the total effective identification times are the sum of the total identification times of successful identification of one time and the total identification times of successful identification of multiple times;
and taking the ratio of the total identification times of the one-time successful identification to the total effective identification times as the one-time successful identification success rate corresponding to the one-time successful identification.
4. The biometric identification device according to claim 2, wherein the feature comparison parameter comprises a similarity threshold of the collected biometric feature and a pre-stored target biometric feature; the processor is specifically configured to:
if the primary identification success rate is greater than or equal to a preset maximum threshold, increasing the similarity threshold;
and if the primary identification success rate is less than or equal to a preset minimum threshold, reducing the similarity threshold.
5. The biometric apparatus according to claim 2, wherein the feature matching parameter includes the number of matched feature points; the processor is specifically configured to:
if the one-time identification success rate is larger than or equal to a preset maximum threshold value, increasing the number of the compared feature points;
and if the one-time identification success rate is less than or equal to a preset minimum threshold, reducing the number of the compared feature points.
6. A biometric identification method, comprising:
if the collected biological characteristics are compared with the prestored target biological characteristics according to the characteristic comparison parameters and the comparison result is successful in identification, determining identification types according to the comparison times and updating the identification success rate corresponding to part or all of the identification types;
if the identification success rate corresponding to the updated identification type meets the adjustment condition, adjusting the characteristic comparison parameter corresponding to the target biological characteristic;
after acquiring a new biological characteristic, determining a comparison result of the new biological characteristic and a prestored target biological characteristic according to the adjusted characteristic comparison parameter;
the identification type comprises one-time identification success and multiple-time identification success; the determining the identification type according to the comparison times comprises the following steps:
if the comparison times are one time, the determined identification type is successful in one-time identification; or if the comparison times are more than one time, the determined identification type is that the multiple identification is successful; the comparison times are determined by the following method:
if the comparison result of the last comparison adjacent to the comparison is successful in identification, or the time interval between the comparison and the last comparison adjacent to the comparison is greater than a set time interval value, determining that the comparison times are once; alternatively, the first and second electrodes may be,
if the comparison result of the last comparison adjacent to the comparison is identification failure and the time interval between the comparison and the last comparison adjacent to the comparison is less than or equal to a set time interval value, determining the comparison times according to the total comparison times from the first comparison to the comparison;
the first comparison refers to comparison that when the last comparison is traversed forward from the comparison, the first comparison result which is found is identification failure, and the comparison result of the adjacent previous comparison is identification success or the time interval between the adjacent previous comparison and the previous comparison is larger than a set time interval value.
7. The method according to claim 6, wherein the updating the recognition success rate corresponding to part or all of the recognition types comprises:
if the comparison times are one time, updating the total identification times of one-time successful identification according to the comparison times, or if the comparison times are more than one time, updating the total identification times of multiple-time successful identification according to the comparison times;
and determining the one-time identification success rate corresponding to the one-time identification success according to the total identification times of the one-time identification success and the total identification times of the multiple-time identification success.
8. The method according to claim 7, wherein the determining a primary recognition success rate corresponding to a primary recognition success according to the total recognition times of the primary recognition success and the total recognition times of the multiple recognition successes comprises:
determining the total effective identification times corresponding to the target biological characteristics, wherein the total effective identification times are the sum of the total identification times of successful identification of one time and the total identification times of successful identification of multiple times;
and taking the ratio of the total identification times of the one-time successful identification to the total effective identification times as the one-time successful identification success rate corresponding to the one-time successful identification.
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| CN205486117U (en) * | 2015-12-28 | 2016-08-17 | 深圳市亚略特生物识别科技有限公司 | Intelligent Mobile Terminal based on biological identification |
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