CN111696228A - Intelligent palm print and palm vein lock based on compressed sensing method - Google Patents
Intelligent palm print and palm vein lock based on compressed sensing method Download PDFInfo
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- CN111696228A CN111696228A CN202010324488.9A CN202010324488A CN111696228A CN 111696228 A CN111696228 A CN 111696228A CN 202010324488 A CN202010324488 A CN 202010324488A CN 111696228 A CN111696228 A CN 111696228A
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- 210000003462 vein Anatomy 0.000 title claims abstract description 77
- 238000000034 method Methods 0.000 title claims abstract description 40
- 238000005070 sampling Methods 0.000 claims abstract description 13
- 238000012545 processing Methods 0.000 claims abstract description 6
- 230000006835 compression Effects 0.000 claims abstract description 5
- 238000007906 compression Methods 0.000 claims abstract description 5
- 239000011159 matrix material Substances 0.000 claims description 30
- 238000005259 measurement Methods 0.000 claims description 17
- 230000009466 transformation Effects 0.000 claims description 9
- 238000000605 extraction Methods 0.000 claims description 8
- 238000007781 pre-processing Methods 0.000 claims description 7
- 230000008569 process Effects 0.000 claims description 7
- 238000005457 optimization Methods 0.000 claims description 5
- 238000001914 filtration Methods 0.000 claims description 2
- 230000005540 biological transmission Effects 0.000 abstract description 8
- 230000008901 benefit Effects 0.000 abstract description 6
- 238000005516 engineering process Methods 0.000 description 3
- 238000011084 recovery Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 210000004204 blood vessel Anatomy 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/00174—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys
- G07C9/00563—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys using personal physical data of the operator, e.g. finger prints, retinal images, voicepatterns
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- E—FIXED CONSTRUCTIONS
- E05—LOCKS; KEYS; WINDOW OR DOOR FITTINGS; SAFES
- E05B—LOCKS; ACCESSORIES THEREFOR; HANDCUFFS
- E05B15/00—Other details of locks; Parts for engagement by bolts of fastening devices
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/70—Multimodal biometrics, e.g. combining information from different biometric modalities
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- 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
- G06V40/14—Vascular patterns
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- General Physics & Mathematics (AREA)
- Human Computer Interaction (AREA)
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- Theoretical Computer Science (AREA)
- Collating Specific Patterns (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
The invention provides a palm print palm vein intelligent lock based on a compression sensing method, which comprises a palm print palm vein intelligent lock device, wherein the palm print palm vein intelligent lock device comprises a lock body, a lock handle, a key hole and a palm print palm vein authentication device, and the key and the palm print palm vein authentication device have an unlocking function at the same time. The palm print and palm vein recognition method based on compressed sensing can improve the performance of the intelligent lock, and is mainly realized by processing images by adopting a compressed sensing algorithm. The method has the advantages that the sampling rate of the algorithm is low, the requirements of storage resources and transmission broadband can be reduced, the anti-noise capability is high, and the safety is high in the image transmission process. Therefore, the accuracy of the identity authentication can be improved, and the equipment cost can be reduced.
Description
Technical Field
The invention relates to a palm print and palm vein recognition intelligent lock.
Background
In the information society of today, the need for identity verification is more and more urgent, and informatization systems face a difficult challenge on how to identify one's identity. At present, the technology of fingerprint identification, face identification and the like widely applied in China is gradually developed and has obvious advantages. The palm print and palm vein is an identity recognition technology which is not easy to replace by others, is imitated, is convenient, effective and safe, but in the identity recognition process of the intelligent lock, the basic requirements of people on the intelligent lock are high in accuracy and low in equipment cost. Therefore, the processing method of the collected palm print and palm vein image is particularly important.
The image processing based on the compressed sensing has the advantage of incomparable ratio compared with the traditional image processing by utilizing the characteristic that compressed sampling of a compressed sensing theory is synchronously performed. The method has the advantages that the algorithm is low in sampling rate, requirements for storage resources and transmission broadband can be reduced, the anti-noise capability is high, and the safety is high in the image transmission process.
Disclosure of Invention
Aiming at the existing palm print palm vein recognition process, the invention aims to provide a palm print palm vein recognition method based on compressed sensing to improve the performance of an intelligent lock, improve the accuracy of identity verification by adopting a compressed sensing algorithm and reduce the equipment cost.
The technical scheme for realizing the purpose of the invention is as follows:
a palm print palm vein intelligent lock based on a compression sensing method comprises a palm print palm vein intelligent lock device, wherein the palm print palm vein intelligent lock device comprises a lock body, a lock handle, a key hole and a palm print palm vein authentication device;
the palm print and palm vein authentication equipment is installed on the lock body, and a palm print and palm vein collection module arranged in the palm print and palm vein authentication equipment is used for integrating two biological identifications of a palm print and a palm vein, so that the accuracy of the palm print and palm vein authentication equipment is improved.
The built-in central processing unit of lock body includes palm print palm vein image preprocessing unit, palm print palm vein characteristic extraction unit and palm print palm vein discernment judgement unit, wherein:
the palm print and palm vein image preprocessing unit adopts a compressed sensing method to preprocess the acquired palm original image. The process comprises four implementation steps: the method comprises the following steps of obtaining image information, measuring matrix transformation, obtaining a reconstructed original signal and recovering an image, wherein the characteristics of each step are as follows:
s1, the image information is obtained by the following steps: acquiring partial information of an image through image compression sampling;
s2, the measurement matrix transformation is characterized in that: designing a measurement matrix meeting the conditions, ensuring irrelevance between the measurement matrix and signal sparseness, and under the condition of determining sparsity, performing linear transformation of multiplication on a sampling signal and an inverse matrix of the measurement matrix to obtain a sparse signal of an original signal;
s3, acquiring the reconstructed original signal is characterized in that: solving an optimization problem, and approximately solving a 0 norm problem by using a greedy algorithm under the condition of not changing an objective function;
s4, the restored image is characterized in that: after the reconstructed original signal, the entire image is restored.
The specific implementation of the method for solving the sparsity is as follows:
m1: replacing the accurate sparsity in the original algorithm with the estimated sparsity;
m2: automatically searching towards two sides by taking the estimated sparsity as a center to obtain a group of sparsity values;
m3: respectively calculating residual errors of respective signals under a group of sparse values, wherein the minimum residual error is the optimal sparsity of the group;
m4: repeating M2 and M3 by taking the sparsity selected by M3 as a center, and recording the optimal sparsity value of each group;
m5: and circularly executing M4, and if the frequency of the occurrence of the optimal sparsity in a certain group is large, terminating the algorithm, wherein the sparsity is the last optimal sparsity.
The method breaks through the limitation of sparsity in the compressed sensing algorithm, and greatly enhances the practicability of the compressed sensing algorithm; and moreover, algorithm stopping conditions are set from the aspect of probability statistics, and the recovery time is effectively shortened.
The palm print and palm vein feature extraction unit adopts a self-adaptive Gabor filtering method to extract palm vein features, determines a main direction in each divided sub-region, calculates a standard variance for each sub-region and determines a central frequency;
the palm print and palm vein recognition and judgment unit is used for comparing the features of the image after feature extraction.
The key hole is used for unlocking by a key and has an unlocking function with the palm print palm vein authentication equipment.
The principle of the palm print and palm vein intelligent lock based on the compressed sensing method is as follows: the intelligent lock can be unlocked by adopting two modes of a key and palm print palm vein identification. When a user selects a key to unlock the lock, the key is directly inserted into the key hole and is rotated to open the lock; when a user selects a palm print and palm vein recognition mode to unlock, firstly, a palm is placed at a palm print and palm vein acquisition device, the device can acquire a palm print and palm vein image of the user, then, the image is preprocessed through a compressed sensing algorithm, after the processed image is obtained, the image is subjected to feature extraction, and finally, matching decision is carried out on data to be compared and data stored in the device. If the matching is successful, the lock is automatically opened, otherwise, no matching item is displayed.
The palm print and palm vein intelligent lock based on the compressed sensing method has the following advantages by adopting vein recognition: stability; uniqueness: the characteristics of blood vessels of any hand have unique biological characteristics and cannot be repeated; long-term effective recognition rate: any damage, scratch, pollution and surrounding environment change of the collection surface can not affect the identification effect; ultra-precise safety measures: the method has uniqueness, non-replicability and incapability of being stolen, and prevents the leakage, the counterfeiting, the stealing and the data loss of personal information of a user.
The invention has the beneficial effects that:
(1) and (3) reconstructing the image at the receiving end by using a compressed sensing theory, wherein the reconstructed image is obtained by solving a constrained optimization algorithm based on the measured values of the sampling values of which the number is far less than that of the Nyquist sampling theorem. The resource requirements for image acquisition and storage can be reduced to a great extent, and the requirements for image acquisition equipment are reduced.
(2) The image reconstruction of the compressed sensing is to recover according to the data volume which is far smaller than the original image, so that the underdetermined ill-conditioned problem from low dimension to high dimension is solved, and a solution is provided for a plurality of troublesome problems in the field of image processing application; during transmission, only the measured values need to be compressed, which also significantly reduces the transmission bandwidth requirements.
(3) The compressed sensing can realize safe transmission, in order to meet the RIP condition which is the condition of accurately reconstructing the image, a random matrix is usually adopted as a measuring matrix, and the random measuring matrix which is only known at the receiving end and the transmitting end has strong safety and is extremely difficult to be broken, so that the compressed sensing has strong safety in the process from compressed sampling at the encoding end to reconstruction recovery at the decoding end, and can be used as the theoretical basis of image safe transmission.
(4) The method for calculating the sparsity has the advantages that: the accurate sparsity does not need to be input, but is replaced by an estimated sparsity, so that the practicability of the algorithm is enhanced; the optimal sparsity is automatically searched by the algorithm without manual intervention; measuring the quality of sparsity by using a residual value; gradually achieving the optimal value through continuous loop iteration; from the angle of probability statistics, an algorithm termination condition is set, and the recovery time of the image is effectively shortened.
(5) Compared with the fingerprint identification which is widely used at present, the palm print and palm vein biometric authentication method is a non-contact identification method and has higher accuracy.
Description of the drawings:
FIG. 1 is a schematic structural diagram of an embodiment of the present invention;
FIG. 2 is a flowchart illustrating the operation of the palm print and palm vein authentication module according to an embodiment of the present invention;
FIG. 3 is a compressed sensing block diagram;
fig. 4 is a compressed sensing matrix model.
FIG. 5 is a detailed flow chart of compressed sensing according to an embodiment of the present invention;
Detailed Description
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the present embodiment provides a palm print palm vein intelligent lock based on a compressed sensing method, including a palm print palm vein intelligent lock device, where the palm print palm vein intelligent lock device includes a lock body, a lock handle, a key hole, and a palm print palm vein authentication device. The palm print palm vein intelligent lock can be unlocked by adopting two modes of a key and palm print palm vein identification.
As shown in fig. 2, the conventional biometric methods such as palm print/palm vein recognition, fingerprint recognition, iris recognition, face recognition, etc. are similar in workflow, and all include four processes of original information, image preprocessing, feature information extraction, and pattern matching. Firstly, establishing a palm print palm vein feature database, and associating vein feature templates and unique identity identification information by different users through information acquisition equipment and storing the vein feature templates and the unique identity identification information into the database; secondly, the identification system compares the extracted vein image to be compared with the existing characteristics in the database by using a specific and complex algorithm; and finally, outputting the comparison result.
As shown in fig. 3, the palm print and palm vein image preprocessing unit preprocesses the acquired palm original image by using a compressed sensing method, firstly, the signal is represented by a sparse basis Ψ, α is a coefficient vector of a signal x under the linear projection of a sparse basis matrix, and then, a measurement matrix Φ is usedM×NAnd measuring the signal x, projecting the original signal to a dimension lower than the signal length for observation and research, obtaining an M-dimensional vector by sampling, namely a measurement signal y, and finally recovering the signal by adopting a CS (circuit switched) optimization reconstruction algorithm.
As shown in fig. 4, the visualization is represented in the form of a matrix of colored squares, where colored sub-blocks represent non-zero values and white positions represent element values of 0. Using measurement matrix phiM×NProjecting the compressible signal from N-dimension to M-dimension space, and storing the information of interest of the original signal in the processyIn order to simplify the representation, the measurement matrix Φ isM×NAnd sparse basis matrix ΨN×NtLinear multiplication is carried out, and the obtained matrix is called a sensing matrix thetaM×NtPhi psi. Based on this, the measurement signal y and the sparse coefficient vector S can be considered equivalent, which is essentially S in the transform domain ΘyIs used in the sparse representation of (1).
As shown in fig. 5, the compressed sensing algorithm process includes four implementation steps: the method comprises the following steps of obtaining image information, measuring matrix transformation, obtaining a reconstructed original signal and recovering an image, wherein the characteristics of each step are as follows:
s1, the image information is obtained by the following steps: acquiring partial information of an image through image compression sampling;
s2, the measurement matrix transformation is characterized in that: designing a measurement matrix meeting the conditions, ensuring irrelevance between the measurement matrix and signal sparseness, and under the condition of determining sparsity, performing linear transformation of multiplication on a sampling signal and an inverse matrix of the measurement matrix to obtain a sparse signal of an original signal;
s3, acquiring the reconstructed original signal is characterized in that: solving an optimization problem, and approximately solving a 0 norm problem by using a greedy algorithm under the condition of not changing an objective function;
s4, the restored image is characterized in that: after the reconstructed original signal, the entire image is restored.
The technical scheme of the invention is sufficient, the palm print palm vein recognition technology is well applied to the field of intelligent locks, and the collected palm print palm vein images are processed by adopting a compressed sensing algorithm. Therefore, the accuracy of the identity authentication is improved, and the equipment cost is reduced.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (5)
1. A palm print palm vein intelligent lock based on a compressed sensing method is characterized in that: the palm print palm vein intelligent lock comprises palm print palm vein intelligent lock equipment, wherein the palm print palm vein intelligent lock equipment comprises a lock body, a lock handle, a key hole and palm print palm vein authentication equipment, and the key and the palm print palm vein authentication equipment have an unlocking function simultaneously.
2. The palm print and palm vein intelligent lock based on the compressed sensing method as claimed in claim 1, wherein: the palm print and palm vein authentication equipment is installed on the lock body, and a palm print and palm vein collection module arranged in the palm print and palm vein authentication equipment is used for integrating two biological identifications of a palm print and a palm vein, so that the accuracy of the palm print and palm vein authentication equipment is improved.
3. The palm print and palm vein intelligent lock based on the compressed sensing method as claimed in claim 1, wherein: the built-in central processing unit of lock body includes palm print palm vein image preprocessing unit, palm print palm vein characteristic extraction unit and palm print palm vein discernment judgement unit, wherein:
the palm print and palm vein image preprocessing unit adopts a compressed sensing method to preprocess the acquired palm original image.
The palm print and palm vein feature extraction unit adopts a self-adaptive Gabor filtering method to extract palm vein features, determines a main direction in each divided sub-region, calculates a standard variance for each sub-region and determines a central frequency;
the palm print and palm vein recognition and judgment unit is used for comparing the features of the image after feature extraction.
4. The palm print and palm vein intelligent lock based on the compressed sensing method as claimed in claim 3, wherein: the palm print and palm vein image preprocessing unit adopts a compressed sensing method to preprocess the acquired palm original image. The process comprises four implementation steps: the method comprises the following steps of obtaining image information, measuring matrix transformation, obtaining a reconstructed original signal and recovering an image, wherein the characteristics of each step are as follows:
s1, the image information is obtained by the following steps: acquiring partial information of an image through image compression sampling;
s2, the measurement matrix transformation is characterized in that: designing a measurement matrix meeting the conditions, ensuring irrelevance between the measurement matrix and signal sparseness, and under the condition of determining sparsity, performing linear transformation of multiplication on a sampling signal and an inverse matrix of the measurement matrix to obtain a sparse signal of an original signal;
s3, acquiring the reconstructed original signal is characterized in that: solving an optimization problem, and approximately solving a 0 norm problem by using a greedy algorithm under the condition of not changing an objective function;
s4, the restored image is characterized in that: after the reconstructed original signal, the entire image is restored.
5. The palm print and palm vein intelligent lock based on the compressed sensing method as claimed in claim 1, wherein: the key hole is used for unlocking by a key and has an unlocking function with the palm print palm vein authentication equipment.
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Cited By (1)
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| CN113034741A (en) * | 2021-03-02 | 2021-06-25 | 桂林电子科技大学 | Palm vein intelligent lock based on DWT-DCT (discrete wavelet transform-discrete cosine transform) transform encryption algorithm |
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