CN114241535B - Rapid palm vein feature extraction method and system - Google Patents
Rapid palm vein feature extraction method and system Download PDFInfo
- Publication number
- CN114241535B CN114241535B CN202111452089.1A CN202111452089A CN114241535B CN 114241535 B CN114241535 B CN 114241535B CN 202111452089 A CN202111452089 A CN 202111452089A CN 114241535 B CN114241535 B CN 114241535B
- Authority
- CN
- China
- Prior art keywords
- matrix
- palm vein
- jset
- jpre
- jprt
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
Landscapes
- Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Artificial Intelligence (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
The utility model provides a quick palm vein feature extraction method and system, collect palm vein information with the sensor and process the palm vein information that gathers and obtain the palm vein feature and upload to the database, calculate the similarity between each palm vein feature as the isogenism between each palm vein feature to each palm vein feature in the database again, and then carry out the fragmentation storage according to the isogenism between each palm vein feature, realized the beneficial achievement of extracting palm vein data feature and carrying out the discernment of palm vein information fast with low computational cost from this.
Description
Technical Field
The disclosure belongs to the field of image recognition, and particularly relates to a rapid palm vein feature extraction method and system.
Background
The palm venation recognition technology is adopted, so that the limitation of the general face recognition technology is broken through, and the improvement and improvement of social comprehensive management are realized. The zero-contact safe and convenient intelligent identification technology is used, the standard construction and application management of the urban rail transit public safety precaution system are promoted and standardized, and a perfect public safety precaution system is formed. The palm vein recognition system disclosed in patent application No. CN201510767083.1 can calculate scalar products of high-frequency feature vectors of corresponding sample points of two images, add the scalar products to obtain high-frequency similarity, divide the number of corresponding components of the low-frequency feature vectors corresponding to the two images by the total dimension of the vectors to obtain low-frequency similarity, and add the high-frequency similarity and the low-frequency similarity according to a preset weight to obtain the total similarity, but the calculation cost is too high. In actual production life, a lighter and faster calculation method and system are needed for the technical application of palm print recognition.
Disclosure of Invention
The present invention is directed to a method and a system for fast extracting a palm vein feature, so as to solve one or more technical problems in the prior art and provide at least one useful choice or creation condition.
The palm venation recognition technology is adopted, so that the limitation of the general face recognition technology is broken through, but in actual production and life, a lighter and faster calculation method and a system are needed for the application of the palm print recognition technology.
The utility model provides a quick palm vein feature extraction method and system, install the sensor on the handrail of a plurality of different entrances and exits of building respectively, gather palm vein information with the sensor and process the palm vein information who gathers and obtain the palm vein feature and upload to the database in, again calculate the similarity between each palm vein feature as the homology between each palm vein feature to each palm vein feature in the database, and then carry out the fragmentation according to the homology between each palm vein feature.
In order to achieve the above object, according to an aspect of the present disclosure, there is provided a rapid palm vein feature extraction method, including the steps of:
s100, respectively installing sensors on handrails at a plurality of different entrances and exits of a building;
s200, collecting palm vein information by a sensor;
s300, processing the collected palm vein information to obtain palm vein characteristics and uploading the palm vein characteristics to a database;
s400, calculating the similarity between the palm vein features in the database to serve as the homology between the palm vein features;
and S500, carrying out fragment storage according to the homology among the characteristics of the palm veins.
Further, in S100, a method of installing sensors on handrails at a plurality of different entrances and exits of a building, respectively, includes: the method comprises the steps that sensors are respectively installed on handrails at a plurality of different entrances and exits of a building, the sensors comprise image sensors, typewriteable input equipment and infrared sensors, the sensors are used for collecting face image information of pedestrians at the entrances and exits, and the sensors are used for collecting character string information input by the pedestrians at the entrances and exits through the input equipment.
Further, in S200, the method for collecting the palm vein information by the sensor includes: the palm vein information of the pedestrian at the entrance and exit is collected by a sensor, the sensor irradiates a palm vein pattern reflected by a palm collected by the palm of the pedestrian with infrared rays of an infrared sensor, and an image matrix with uniform size is obtained by carrying out graying and binarization processing on the palm vein pattern and is used as the palm vein information.
Further, in S300, the method of processing the collected palm vein information to obtain the palm vein feature and uploading the palm vein feature to the database includes:
taking the palm vein information as an image matrix with the size of mxn, recording the image matrix as a matrix Jpre, wherein m is the number of rows of the matrix Jpre, the serial number of the rows in the matrix Jpre is j, the number of columns of the matrix Jpre is n, the serial number of the columns of the matrix Jpre is i, the element of the row with the serial number i in the matrix Jpre is Jpre (, i), the element of the row with the serial number j in the matrix Jpre is Jpre (j,), the element of the row with the serial number j in the matrix Jpre is j, the element of the column with the serial number i in the matrix Jpre is Jpre (j, i), i belongs to [1, n ], and j belongs to [1, m ];
setting an image matrix which has the same size as the preprocessing chart and is m multiplied by n as a matrix Jpro, wherein m is the number of rows of the matrix Jpro, the serial numbers of the rows in the matrix Jpro are j in the same way, the number of columns of the matrix Jpro is n, the serial numbers of the columns of the matrix Jpro are i, the element of the row with the serial number of i in the matrix Jpro is Jpro (, i), the element of the row with the serial number of j in the matrix Jpro is Jpro (j, i), and the element of the row with the serial number of j in the matrix Jpro and the serial number of i in the column is Jpro (j, i);
the calculation process of Jpro (j, i) in the matrix Jpro is as follows:
s301, acquiring an element Jpre (j, i) of a matrix Jpre, wherein the serial number of a row is j, and the serial number of a column is i;
s302 obtains 8 elements of Jpre (j, i) adjacent in position in the matrix Jpre, namely
8 elements of Jpre (j-1, i), Jpre (j, i-1), Jpre (j-1, i-1), Jpre (j +1, i), Jpre (j, i +1), Jpre (j +1, i-1), Jpre (j-1, i +1), wherein if Jpre (j, i) is located at the edge of the matrix Jpre or if there is no element in the 8 elements, 0 is substituted, the set of 8 elements is recorded as Vset (j, i), the element in the set Vset (j, i) is V (j, i), and V (j, i) belongs to Vset (j, i);
s303, a calculation formula for calculating the value of Jpro (j, i) according to Jpre (j, i) and the set Vset (j, i) is as follows:
wherein the function exp () is an exponential function with a natural constant e as a base;
thus, the numerical value of each element Jpro (j, i) in the matrix Jpro is obtained, the matrix Jpro can be expressed as Jpro ═ Jpro (j, i) | i ∈ [1, n ], j ∈ [1, m ] ], and the matrix Jpro is the palm vein feature.
Further, in S400, the method of calculating the similarity between the palm vein features in the database as the degree of homology between the palm vein features includes:
recording newly acquired palm vein features as a matrix Jprt or any one of the palm vein features as Jprt, recording a set of the palm vein features in a database as a set Jset, wherein the number of elements in the set Jset is k, the number of the elements in the set Jset is q, q belongs to [1, k ], and the elements with the number of q in the set Jset are recorded as a matrix Jset (q);
wherein m is the number of rows of the matrix Jset (q), the serial numbers of the rows in the matrix Jset (q) are j, the number of columns of the matrix Jset (q) is n, the serial numbers of the columns in the matrix Jset (q) are i, the element with the serial number of the columns in the matrix Jset (q) being I is Jset (q) (, i), the element with the serial number of the rows in the matrix Jset (q) being J is Jset (q) ((j,), the element with the serial number of the rows in the matrix Jset (q) being j, the element with the serial number of the columns being i is Jset (q) ((j, i), i belongs to [1, n ], j belongs to [1, m ];
wherein m is the number of rows of the matrix Jprt, the serial numbers of the rows in the matrix Jprt are also j, the number of columns of the matrix Jprt is n, the serial numbers of the columns of the matrix Jprt are i, the element of the row with the serial number of i in the matrix Jprt is Jprt (, i), the element of the row with the serial number of j in the matrix Jprt is Jprt (j,;), the element with the serial number of j in the row in the matrix Jprt and the element with the serial number of i in the column in the matrix Jprt is Jprt (j, i);
let a function of calculating the degree of homology between any palm vein feature and the palm vein features in the database be a function Wtr (), where Wtr (Jprt, jset (q)) represents the degree of homology between Jprt and jset (q) calculated by the function Wtr (), and the formula of Wtr (Jprt, jset (q)) is:
wherein add () is a summation function, add (Jset (q) (, i)) represents the sum of elements of columns with sequence number i in matrix Jset (q), add (Jset (q) ((j,)) represents the sum of elements of rows with sequence number j in matrix Jset (q), add (Jprt) (q) (, i)) represents the sum of elements of columns with sequence number i in matrix Jprt, add (Jprt (j,)) represents the sum of elements of rows with sequence number j in matrix Jprt, the numerical value of the calculation result of Wtr (Jprt, Jset (q)) can be represented as Wtr (q), Wtr (q) is a distance value obtained by calculating any vein feature and vein feature with sequence number q in the database, the set formed by the distance values obtained by calculating any vein feature and each vein feature in the database is represented as a set element in the set, and the element in the set corresponding to each other, the sequence numbers of elements in the set Wset are q, the number of the elements in the set Wset is k, the elements with the sequence numbers of q in the set Wset are wtr (q), the wtr (q) and Jset (q) correspond to each other, and the set Wset is the homology among all the palm vein features.
Further, in S500, according to the degree of homology between the palm vein features, the method for performing slice storage includes:
marking a function Avg () as a function for calculating the arithmetic mean of elements in a set, wherein a set formed by the degrees of homology among all the palm vein features is Wset, Avg (Wset) is the arithmetic mean of the elements in the Wset, the set of the palm vein features in a database is Jset, marking newly acquired palm vein features as a matrix Jprt or any one of the palm vein features as Jprt, acquiring a set formed by the serial numbers of the elements smaller than Avg (Wset) in the Wset as a homologous serial number set, taking the elements in the homologous serial number set as serial numbers, acquiring the element forming set with the corresponding serial numbers in the set Jset as the homologous palm vein feature set, slicing in the storage of the database to obtain a storage slice, storing the homologous vein feature set on the storage slice, and performing image recognition on the elements in the homologous palm vein feature set in the Jprt and the storage slice by using an image recognition algorithm, therefore, the rapid extraction and the rapid identification and search of the palm vein features are realized.
The present disclosure also provides a rapid palm vein feature extraction system, the rapid palm vein feature extraction system includes: the processor executes the computer program to implement the steps in the fast palm vein feature extraction method, the fast palm vein feature extraction system may be operated in a computing device such as a desktop computer, a notebook computer, a palm computer, a cloud data center, and the like, and the operable system may include, but is not limited to, a processor, a memory, and a server cluster, and the processor executes the computer program to operate in units of the following systems:
a sensor unit for mounting sensors on handrails at a plurality of different entrances and exits of a building, respectively;
the information acquisition unit is used for acquiring the palm vein information by using the sensor;
the data processing unit is used for processing the collected palm vein information to obtain palm vein characteristics and uploading the palm vein characteristics to the database;
the homology calculating unit is used for calculating the similarity between the palm vein features in the database as the homology between the palm vein features;
and the slice storage unit is used for carrying out slice storage according to the homology among the palm vein features.
The beneficial effect of this disclosure does: the utility model provides a quick palm vein feature extraction method and system, collect palm vein information with the sensor and process the palm vein information that gathers and obtain the palm vein feature and upload to the database, calculate the similarity between each palm vein feature as the isogenism between each palm vein feature to each palm vein feature in the database again, and then carry out the fragmentation storage according to the isogenism between each palm vein feature, realized the beneficial achievement of extracting palm vein data feature and carrying out the discernment of palm vein information fast with low computational cost from this.
Drawings
The foregoing and other features of the present disclosure will become more apparent from the detailed description of the embodiments shown in conjunction with the drawings in which like reference characters designate the same or similar elements throughout the several views, and it is apparent that the drawings in the following description are merely some examples of the present disclosure and that other drawings may be derived therefrom by those skilled in the art without the benefit of any inventive faculty, and in which:
FIG. 1 is a flow chart of a rapid palm vein feature extraction method;
fig. 2 is a system structure diagram of a rapid palm vein feature extraction system.
Detailed Description
The conception, specific structure and technical effects of the present disclosure will be clearly and completely described below in conjunction with the embodiments and the accompanying drawings to fully understand the objects, aspects and effects of the present disclosure. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
In the description of the present invention, the meaning of a plurality of means is one or more, the meaning of a plurality of means is two or more, and larger, smaller, larger, etc. are understood as excluding the number, and larger, smaller, inner, etc. are understood as including the number. If the first and second are described for the purpose of distinguishing technical features, they are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
Fig. 1 is a flowchart illustrating a method for rapidly extracting a palm vein feature according to the present invention, and a method and a system for rapidly extracting a palm vein feature according to an embodiment of the present invention are described below with reference to fig. 1.
The present disclosure provides a rapid palm vein feature extraction method, which specifically includes the following steps:
s100, respectively installing sensors on handrails at a plurality of different entrances and exits of a building;
s200, collecting palm vein information by a sensor;
s300, processing the collected palm vein information to obtain palm vein characteristics and uploading the palm vein characteristics to a database;
s400, calculating the similarity between the palm vein features in the database to serve as the similarity between the palm vein features;
and S500, carrying out fragment storage according to the homology among the characteristics of the palm veins.
Further, in S100, a method of installing sensors on handrails at a plurality of different entrances and exits of a building, respectively, includes: the method comprises the steps that sensors are respectively installed on handrails at a plurality of different entrances and exits of a building, the sensors comprise image sensors, typewriteable input equipment and infrared sensors, the sensors are used for collecting face image information of pedestrians at the entrances and exits, and the sensors are used for collecting character string information input by the pedestrians at the entrances and exits through the input equipment.
Further, in S200, the method for collecting the palm vein information by the sensor includes: the palm vein information of the pedestrian at the entrance and exit is collected by a sensor, the sensor irradiates a palm vein pattern collected by the palm of the pedestrian with infrared rays of an infrared sensor, and an image matrix with uniform size obtained by performing gray processing and binary processing on the palm vein pattern is used as the palm vein information.
Further, in S300, the method of processing the collected palm vein information to obtain the palm vein feature and uploading the palm vein feature to the database includes:
taking the palm vein information as an image matrix with the size of m multiplied by n as a matrix Jpre, wherein m is the number of rows of the matrix Jpre, the serial number of the rows in the matrix Jpre is j, the number of columns of the matrix Jpre is n, the serial number of the columns of the matrix Jpre is i, the element of the row with the serial number i in the matrix Jpre is Jpre (, i), the element of the row with the serial number j in the matrix Jpre is Jpre (j,) and the element of the row with the serial number j in the matrix Jpre is Jpre (j, i), i belongs to [1, n ], and j belongs to [1, m ];
setting an image matrix which has the same size as the preprocessed image and is mxn as a matrix Jpro, wherein m is the number of rows of the matrix Jpro, the serial numbers of the rows in the matrix Jpro are j, the number of columns of the matrix Jpro is n, the serial numbers of the columns of the matrix Jpro are i, the element of the row with the serial number i in the matrix Jpro is Jpro (, i), the element of the row with the serial number j in the matrix Jpro is Jpro (j,), the element of the row with the serial number j in the matrix Jpro is Jpro (j), and the element of the row with the serial number j in the matrix Jpro is Jpro (j, i);
the calculation process of Jpro (j, i) in the matrix Jpro is:
s301, acquiring an element Jpre (j, i) of a matrix Jpre, wherein the serial number of a row is j, and the serial number of a column is i;
s302 obtains 8 elements of Jpre (j, i) adjacent to each other in the position of matrix Jpre, namely
8 elements of Jpre (j-1, i), Jpre (j, i-1), Jpre (j-1, i-1), Jpre (j +1, i), Jpre (j, i +1), Jpre (j +1, i-1), Jpre (j-1, i +1), wherein if Jpre (j, i) is at an edge in the matrix Jpre or if there is no element in the 8 elements, 0 is used as a substitute, and the set of 8 elements is recorded as Vset (j, i), the elements in the set Vset (j, i) are V (j, i), V (j, i) epsilon Vset (j, i);
s303, a calculation formula for calculating the value of Jpro (j, i) according to Jpre (j, i) and the set Vset (j, i) is as follows:
wherein the function exp () is an exponential function with a natural constant e as a base;
thus, the numerical value of each element Jpro (j, i) in the matrix Jpro is obtained, the matrix Jpro can be expressed as Jpro ═ Jpro (j, i) | i ∈ [1, n ], j ∈ [1, m ] ], and the matrix Jpro is the palm vein feature.
Further, in S400, the method of calculating the similarity between the palm vein features in the database as the degree of homology between the palm vein features includes:
recording newly acquired palm vein features as a matrix Jprt or any one of the palm vein features as Jprt, recording a set of the palm vein features in a database as a set Jset, wherein the number of elements in the set Jset is k, the number of the elements in the set Jset is q, q belongs to [1, k ], and the elements with the number of q in the set Jset are recorded as a matrix Jset (q);
wherein m is the number of rows of the matrix Jset (q), the serial numbers of the rows in the matrix Jset (q) are j, the number of columns of the matrix Jset (q) is n, the serial numbers of the columns in the matrix Jset (q) are i, the element with the serial number of the columns in the matrix Jset (q) being I is Jset (q) (, i), the element with the serial number of the rows in the matrix Jset (q) being J is Jset (q) ((j,), the element with the serial number of the rows in the matrix Jset (q) being j, the element with the serial number of the columns being i is Jset (q) ((j, i), i belongs to [1, n ], j belongs to [1, m ];
wherein m is the number of rows of the matrix Jprt, the serial numbers of the rows in the matrix Jprt are also j, the number of columns of the matrix Jprt is n, the serial numbers of the columns of the matrix Jprt are i, the element of the row with the serial number of i in the matrix Jprt is Jprt (, i), the element of the row with the serial number of j in the matrix Jprt is Jprt (j,;), the element with the serial number of j in the row in the matrix Jprt and the element with the serial number of i in the column in the matrix Jprt is Jprt (j, i);
the function for calculating the homology of any palm vein feature and the palm vein features in the database is denoted as function Wtr (), where Wtr (Jprt, jset (q)) denotes the homology of Jprt and jset (q) calculated by function Wtr (), and the formula for calculating Wtr (Jprt, jset (q)) is:
wherein add () is a summation function, add (Jset (q) (, i)) represents the sum of elements of columns with sequence number i in matrix Jset (q), add (Jset (q) ((j,)) represents the sum of elements of rows with sequence number j in matrix Jset (q), add (Jprt) (q) (, i)) represents the sum of elements of columns with sequence number i in matrix Jprt, add (Jprt (j,)) represents the sum of elements of rows with sequence number j in matrix Jprt, the numerical value of the calculation result of Wtr (Jprt, Jset (q)) can be represented as Wtr (q), Wtr (q) is a distance value obtained by calculating any vein feature and vein feature with sequence number q in the database, the set formed by the distance values obtained by calculating any vein feature and each vein feature in the database is represented as a set element in the set, and the element in the set corresponding to each other, the sequence numbers of elements in the set Wset are q, the number of elements in the set Wset is k, the elements with the sequence numbers of q in the set Wset are wtr (q), the wtr (q) and Jset (q) correspond to each other, and the set Wset is the homology among all the palm vein features.
Further, in S500, according to the degree of homology between the palm vein features, the method for performing slice storage includes:
recording a function Avg () as a function for calculating an arithmetic mean of elements in a set, wherein a set formed by the degrees of homology among all the palm vein features is Wset, Avg (Wset) represents the arithmetic mean of the elements in the Wset, the set of the palm vein features in a database is Jset, recording a newly acquired palm vein feature as a matrix Jprt or any one of the palm vein features as Jprt, acquiring a set formed by the serial numbers of the elements smaller than Avg (Wset) in the Wset as a homologous serial number set, taking the elements in the homologous serial number set as the serial numbers, acquiring the element forming set with the corresponding serial numbers in the set Jset as the homologous palm vein feature set, segmenting in the storage of the database to obtain storage segments, storing the homologous palm vein feature set on the storage segments, and using an image recognition algorithm to recognize the elements in the Jprt and the palm vein feature set in the storage segments, therefore, the rapid extraction and the rapid identification and search of the palm vein features are realized.
The rapid palm vein feature extraction system comprises: the processor executes the computer program to implement the steps in the above embodiment of the rapid palm vein feature extraction method, the rapid palm vein feature extraction system may be operated in a desktop computer, a notebook computer, a palm computer, a cloud data center and other computing devices, and the operable system may include, but is not limited to, the processor, the memory, and a server cluster.
As shown in fig. 2, the rapid palm vein feature extraction system according to an embodiment of the present disclosure includes: a processor, a memory and a computer program stored in the memory and operable on the processor, the processor implementing the steps in the embodiment of the rapid palm vein feature extraction method described above when executing the computer program, the processor executing the computer program to run in the units of the following system:
a sensor unit for mounting sensors on handrails at a plurality of different entrances and exits of a building, respectively;
the information acquisition unit is used for acquiring the palm vein information by using the sensor;
the data processing unit is used for processing the collected palm vein information to obtain palm vein characteristics and uploading the palm vein characteristics to the database;
the homology calculating unit is used for calculating the similarity between the palm vein features in the database as the homology between the palm vein features;
and the fragment storage unit is used for carrying out fragment storage according to the homology among the palm vein features.
The rapid palm vein feature extraction system can be operated in computing equipment such as desktop computers, notebooks, palm computers and cloud data centers. The rapid palm vein feature extraction system comprises a processor and a memory. Those skilled in the art will appreciate that the example is only an example of a rapid palm vein feature extraction method and system, and does not constitute a limitation of the rapid palm vein feature extraction method and system, and may include more or less components than the above, or combine some components, or different components, for example, the rapid palm vein feature extraction system may further include an input and output device, a network access device, a bus, and the like.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete component Gate or transistor logic, discrete hardware components, etc. The general processor may be a microprocessor or the processor may be any conventional processor, and the processor is a control center of the rapid palm vein feature extraction system, and various interfaces and lines are used to connect various sub-regions of the entire rapid palm vein feature extraction system.
The memory can be used for storing the computer programs and/or modules, and the processor can realize various functions of the rapid palm vein feature extraction method and system by running or executing the computer programs and/or modules stored in the memory and calling data stored in the memory. The memory 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 required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, etc. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
The invention provides a rapid palm vein feature extraction method and system, wherein a sensor is used for collecting palm vein information, the collected palm vein information is processed to obtain palm vein features and is uploaded to a database, the similarity among the palm vein features in the database is calculated to serve as the homology among the palm vein features, and then the palm vein features are stored in a slicing mode according to the homology among the palm vein features, so that the palm vein data features are extracted with low calculation cost, and the palm vein information is rapidly identified.
Although the description of the present disclosure has been rather exhaustive and particularly described with respect to several illustrated embodiments, it is not intended to be limited to any such details or embodiments or any particular embodiments, so as to effectively encompass the intended scope of the present disclosure. Furthermore, the foregoing describes the disclosure in terms of embodiments foreseen by the inventor for which an enabling description was available, notwithstanding that insubstantial modifications of the disclosure, not presently foreseen, may nonetheless represent equivalent modifications thereto.
Claims (5)
1. A rapid palm vein feature extraction method is characterized by comprising the following steps:
s100, respectively installing sensors on handrails at a plurality of different entrances and exits of a building;
s200, collecting palm vein information by a sensor;
s300, processing the collected palm vein information to obtain palm vein characteristics and uploading the palm vein characteristics to a database;
s400, calculating the similarity between the palm vein features in the database to serve as the homology between the palm vein features;
s500, performing fragmentation storage according to the homology among the palm vein features;
in S300, the method of processing the collected palm vein information to obtain the palm vein feature and uploading the palm vein feature to the database includes:
taking the palm vein information as an image matrix with the size of mxn, recording the image matrix as a matrix Jpre, wherein m is the number of rows of the matrix Jpre, the serial number of the rows in the matrix Jpre is j, the number of columns of the matrix Jpre is n, the serial number of the columns of the matrix Jpre is i, the element of the row with the serial number i in the matrix Jpre is Jpre (, i), the element of the row with the serial number j in the matrix Jpre is Jpre (j,), the element of the row with the serial number j in the matrix Jpre is j, the element of the column with the serial number i in the matrix Jpre is Jpre (j, i), i belongs to [1, n ], and j belongs to [1, m ];
setting an image matrix which has the same size as the preprocessing chart and is m multiplied by n as a matrix Jpro, wherein m is the number of rows of the matrix Jpro, the serial numbers of the rows in the matrix Jpro are j in the same way, the number of columns of the matrix Jpro is n, the serial numbers of the columns of the matrix Jpro are i, the element of the row with the serial number of i in the matrix Jpro is Jpro (, i), the element of the row with the serial number of j in the matrix Jpro is Jpro (j, i), and the element of the row with the serial number of j in the matrix Jpro and the serial number of i in the column is Jpro (j, i);
the calculation process of Jpro (j, i) in the matrix Jpro is as follows:
s301, acquiring an element Jpre (j, i) of a matrix Jpre, wherein the serial number of a row is j, and the serial number of a column is i;
s302 obtains 8 elements of Jpre (j, i) adjacent in position in the matrix Jpre, namely
8 elements of Jpre (j-1, i), Jpre (j, i-1), Jpre (j-1, i-1), Jpre (j +1, i), Jpre (j, i +1), Jpre (j +1, i-1), Jpre (j-1, i +1), wherein if Jpre (j, i) is located at the edge of the matrix Jpre or if there is no element in the 8 elements, 0 is substituted, the set of 8 elements is recorded as Vset (j, i), the element in the set Vset (j, i) is V (j, i), and V (j, i) belongs to Vset (j, i);
s303, a calculation formula for calculating the value of Jpro (j, i) according to Jpre (j, i) and the set Vset (j, i) is as follows:
wherein the function exp () is an exponential function with a natural constant e as a base;
thus, the numerical value of each element Jpro (j, i) in the matrix Jpro is obtained, the matrix Jpro is represented as Jpro = [ Jpro (j, i) | i belongs to [1, n ], j belongs to [1, m ] ], and the matrix Jpro is the palm vein feature;
in S400, the method of calculating the similarity between the palm vein features in the database as the degree of homology between the palm vein features includes:
recording newly acquired palm vein features as a matrix Jprt or any one of the palm vein features as Jprt, recording a set of the palm vein features in a database as a set Jset, wherein the number of elements in the set Jset is k, the number of the elements in the set Jset is q, q belongs to [1, k ], and the elements with the number of q in the set Jset are recorded as a matrix Jset (q);
wherein m is the number of rows of a matrix Jset (q), the serial numbers of the rows in the matrix Jset (q) are j, the number of columns in the matrix Jset (q) is n, the serial numbers of the columns in the matrix Jset (q) are i, the element which takes the serial number of the column in the matrix Jset (q) as i is Jset (q) (, i), the element which takes the row with the serial number of j in the matrix Jset (q) as Jset (q) (j,), the element which takes the serial number of the row in the matrix Jset (q) as j, and the element which takes the serial number of the column as i as Jset (q) (j, i), i belongs to [1, n ], j belongs to [1, m ];
wherein m is the number of rows of the matrix Jprt, the serial numbers of the rows in the matrix Jprt are also j, the number of columns of the matrix Jprt is n, the serial numbers of the columns of the matrix Jprt are i, the element of the row with the serial number of i in the matrix Jprt is Jprt (, i), the element of the row with the serial number of j in the matrix Jprt is Jprt (j,;), the element with the serial number of j in the row in the matrix Jprt and the element with the serial number of i in the column in the matrix Jprt is Jprt (j, i);
the function for calculating the homology of any palm vein feature and the palm vein features in the database is denoted as function Wtr (), where Wtr (Jprt, jset (q)) denotes the homology of Jprt and jset (q) calculated by function Wtr (), and the formula for calculating Wtr (Jprt, jset (q)) is:
wherein add () is a function of summation, add (Jset (q) (, i)) represents a sum of elements of a column with a sequence number i in a matrix Jset (q), add (Jset (q) ((j,)) i)) represents a sum of elements of a row with a sequence number j in the matrix Jset (q), add (Jprt) (q) (, i)) represents a sum of elements of a column with a sequence number i in the matrix Jprt, add (Jprt (j,)) represents a sum of elements of a row with a sequence number j in the matrix Jprt, the numerical value of the calculation result of Wtr (Jprt, Jset (q)) is Wtr (q), Wtr (q) is a set of distance values obtained by calculating any palm vein feature and a vein feature with a sequence number q in a database, the set of distance values obtained by calculating any palm vein feature and each palm vein feature in the database is set corresponding to the elements in the set of Wtr and the set, the sequence numbers of elements in the set Wset are q, the number of elements in the set Wset is k, the elements with the sequence numbers of q in the set Wset are wtr (q), the wtr (q) and Jset (q) correspond to each other, and the set Wset is the homology among all the palm vein features.
2. The method for rapidly extracting the palm vein feature according to claim 1, wherein in S100, the method for respectively installing the sensors on the handrails at the plurality of different entrances and exits of the building comprises the following steps: the method comprises the steps that sensors are respectively installed on handrails at a plurality of different entrances and exits of a building, the sensors comprise image sensors, typewriteable input equipment and infrared sensors, the sensors are used for collecting face image information of pedestrians at the entrances and exits, and the sensors are used for collecting character string information input by the pedestrians at the entrances and exits through the input equipment.
3. The method for rapidly extracting the palm vein features according to claim 1, wherein in S200, the method for collecting the palm vein information by using the sensor comprises the following steps: the palm vein information of the pedestrian at the entrance and exit is collected by a sensor, the sensor irradiates a palm vein pattern reflected by a palm collected by the palm of the pedestrian with infrared rays of an infrared sensor, and an image matrix with uniform size is obtained by carrying out graying and binarization processing on the palm vein pattern and is used as the palm vein information.
4. The method for rapidly extracting the palm vein features according to claim 3, wherein in step S500, the method for performing slice storage according to the degree of homology among the palm vein features comprises:
marking a function Avg () as a function for calculating the arithmetic mean of elements in a set, wherein a set formed by the degrees of homology among all the palm vein features is Wset, Avg (Wset) is the arithmetic mean of the elements in the Wset, the set of the palm vein features in a database is Jset, marking newly acquired palm vein features as a matrix Jprt or any one of the palm vein features as Jprt, acquiring a set formed by the serial numbers of the elements smaller than Avg (Wset) in the Wset as a homologous serial number set, taking the elements in the homologous serial number set as serial numbers, acquiring the element forming set with the corresponding serial numbers in the set Jset as the homologous palm vein feature set, slicing in the storage of the database to obtain a storage slice, storing the homologous vein feature set on the storage slice, and performing image recognition on the elements in the homologous palm vein feature set in the Jprt and the storage slice by using an image recognition algorithm, therefore, the rapid extraction and the rapid identification and search of the palm vein features are realized.
5. A rapid palm vein feature extraction system, the rapid palm vein feature extraction system comprising: the processor, the memory and the computer program stored in the memory and operable on the processor, when executing the computer program, implement the steps in the fast palm vein feature extraction method in claim 1, wherein the fast palm vein feature extraction system is operated in a computing device of a desktop computer, a notebook computer, a palm computer and a cloud data center.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111452089.1A CN114241535B (en) | 2021-12-01 | 2021-12-01 | Rapid palm vein feature extraction method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111452089.1A CN114241535B (en) | 2021-12-01 | 2021-12-01 | Rapid palm vein feature extraction method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114241535A CN114241535A (en) | 2022-03-25 |
| CN114241535B true CN114241535B (en) | 2022-09-27 |
Family
ID=80752626
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111452089.1A Active CN114241535B (en) | 2021-12-01 | 2021-12-01 | Rapid palm vein feature extraction method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114241535B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101408938A (en) * | 2008-11-18 | 2009-04-15 | 华南理工大学 | Identification authentication apparatus based on finger biologic characteristics |
| CN102419752A (en) * | 2010-09-28 | 2012-04-18 | 上海可鲁***软件有限公司 | Industrial database message storage method |
| CN103392174A (en) * | 2012-11-29 | 2013-11-13 | 华为技术有限公司 | System based on flash storage, partitioning method and apparatus |
| CN105474234A (en) * | 2015-11-24 | 2016-04-06 | 厦门中控生物识别信息技术有限公司 | Method and apparatus for palm vein recognition |
| CN112052842A (en) * | 2020-10-14 | 2020-12-08 | 福建省海峡智汇科技有限公司 | Palm vein-based person identification method and device |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107273844A (en) * | 2017-06-12 | 2017-10-20 | 成都芯软科技股份公司 | Vena metacarpea recognizes matching process and device |
| CN108875629B (en) * | 2018-06-14 | 2021-06-04 | 电子科技大学 | Palm vein identification method based on multi-sample feature fusion |
| CN111104859A (en) * | 2019-11-19 | 2020-05-05 | 广州恒龙信息技术有限公司 | Authentication method and system based on multispectral identification |
| CN112540986A (en) * | 2020-12-07 | 2021-03-23 | 吴娟 | Dynamic indexing method and system for quick combined query of big electric power data |
| CN112613757A (en) * | 2020-12-25 | 2021-04-06 | 成都高乔科技有限公司 | Order resource management configuration system based on big data |
| CN113591134B (en) * | 2021-09-28 | 2021-12-14 | 广东机电职业技术学院 | Threat intelligence big data sharing method and system |
-
2021
- 2021-12-01 CN CN202111452089.1A patent/CN114241535B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101408938A (en) * | 2008-11-18 | 2009-04-15 | 华南理工大学 | Identification authentication apparatus based on finger biologic characteristics |
| CN102419752A (en) * | 2010-09-28 | 2012-04-18 | 上海可鲁***软件有限公司 | Industrial database message storage method |
| CN103392174A (en) * | 2012-11-29 | 2013-11-13 | 华为技术有限公司 | System based on flash storage, partitioning method and apparatus |
| CN105474234A (en) * | 2015-11-24 | 2016-04-06 | 厦门中控生物识别信息技术有限公司 | Method and apparatus for palm vein recognition |
| CN112052842A (en) * | 2020-10-14 | 2020-12-08 | 福建省海峡智汇科技有限公司 | Palm vein-based person identification method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114241535A (en) | 2022-03-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110532884B (en) | Pedestrian re-recognition method, device and computer readable storage medium | |
| CN111679949A (en) | Anomaly detection method based on equipment index data and related equipment | |
| CN112102221A (en) | 3D UNet network model construction method and device for detecting tumor and storage medium | |
| Xu et al. | A supervoxel approach to the segmentation of individual trees from LiDAR point clouds | |
| WO2021174789A1 (en) | Feature extraction-based image recognition method and image recognition device | |
| CN113963303A (en) | Image processing method, video recognition method, device, equipment and storage medium | |
| CN111325276A (en) | Image classification method and device, electronic equipment and computer-readable storage medium | |
| CN111444807A (en) | Target detection method, device, electronic equipment and computer readable medium | |
| CN115034315A (en) | Business processing method and device based on artificial intelligence, computer equipment and medium | |
| CN112966687B (en) | Image segmentation model training method and device and communication equipment | |
| CN114241535B (en) | Rapid palm vein feature extraction method and system | |
| CN111709346B (en) | Historical building identification and detection method based on deep learning and high-resolution images | |
| CN111179218B (en) | Conveyor belt material detection method and device, storage medium and terminal equipment | |
| CN116227573B (en) | Segmentation model training method, image segmentation device and related media | |
| CN115439938A (en) | Anti-splitting face archive data merging processing method and system | |
| CN114639143B (en) | Portrait archiving method, device and storage medium based on artificial intelligence | |
| CN115798004A (en) | Face card punching method and device based on local area, electronic equipment and medium | |
| CN115601684A (en) | Emergency early warning method and device, electronic equipment and storage medium | |
| CN108475339B (en) | Method and system for classifying objects in an image | |
| CN114549884A (en) | Abnormal image detection method, device, equipment and medium | |
| CN114219051A (en) | Image classification method, classification model training method and device and electronic equipment | |
| KR102242042B1 (en) | Method, apparatus and computer program for data labeling | |
| CN109614854B (en) | Video data processing method and device, computer device and readable storage medium | |
| CN110647858B (en) | Video occlusion judgment method and device and computer storage medium | |
| CN110276260B (en) | Commodity detection method based on depth camera |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |