CN210691315U - Photoacoustic intensity anti-counterfeiting recognition device based on linear array type mini LED - Google Patents
Photoacoustic intensity anti-counterfeiting recognition device based on linear array type mini LED Download PDFInfo
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Abstract
The utility model provides a photoacoustic intensity anti-counterfeiting recognition device based on linear array type mini LEDs, which is characterized in that a light source linear array module and a linear array ultrasonic sensing module are positioned under a quartz plate; the heat dissipation fixing plate is provided with an M6 threaded hole for mounting the light source linear array module and the linear array ultrasonic sensing module, is connected with the mechanical displacement device through threads, and is controlled by the mechanical displacement device to perform displacement; the light source linear array module is arranged at the position of the fixing plate for radiating the heat at the left side and the right side of the linear array sensing module; the linear array ultrasonic sensing module is connected with the preposed signal amplifying unit, the utility model effectively improves the anti-counterfeiting performance and the accuracy of the identification; through linear array ultrasonic sensing module and DOE device, turn into the dual overlapping structure of linear point focus with light, on the basis of guaranteeing linear scanning area, improved the speed of scanning, improved the light intensity on the scanning face for the degree of depth that the detection ultrasonic wave can arrive is bigger, and the information of acquireing is more.
Description
Technical Field
The utility model relates to a blood vessel intensity anti-fake recognition device especially relates to an optoacoustic formation of image, subcutaneous blood vessel are anti-fake and biological recognition device.
Background
The photoacoustic vascular technology is characterized in that a measured object is used for absorbing light energy to generate photoacoustic effect, photoacoustic signals, namely ultrasonic imaging, are excited, the photoacoustic vascular technology has the characteristics of high contrast and high resolution, and the Young modulus can be used for distinguishing vascular photoacoustic signals of different people from vascular and non-vascular substances of the same person; and a blood vessel topological structure contrast image can be constructed according to the intensity of the photoacoustic signal.
Compared with the traditional identity authentication technology, the biological identification carries the secret key at any time, is not easy to lose, forget or steal, has stronger anti-counterfeiting performance, and is widely applied to the fields of national security, information security, network security, security authentication, electronic authentication and the like; the biological identification comprises the following technologies:
(1) fingerprint identification
Among all biometric techniques, fingerprint recognition is currently the most widely used one, and many methods are available for fingerprint recognition: comparing the local minutiae of the fingerprints; performing correlation identification through all the characteristics; identification of the edges of the fingerprint's undulations, etc. The product has relatively low price and small volume. However, after the finger print appears, the technique is easily forged.
(2) Palm geometry recognition
The method is to measure the physical characteristics of the palm and fingers of the user for identification, and advanced products can also identify three-dimensional images. The biological identification method is easy to crack by using a silica gel mold.
(3) Retinal identification
Retinal recognition uses a low intensity light source emitted by an optical device to scan a unique pattern on the retina and to process and recognize the pattern. This requires a high precision retina scanning device, while the user has to look at a point during the scanning process. Also, cosmetic pupils and the like have appeared, making this technique easy to counterfeit.
(4) Iris recognition
Iris recognition is to image the human eye using a CCD and then perform image processing and recognition on the iris, and since the size of the pupil of a living body is normal, this technology is considered to be one of the safest technologies, and is one of the most popular technologies at present, and there are products integrated into mobile devices such as mobile phones, tablets, and the like. Also, the appearance of cosmetic pupils and the like makes this technique easy to counterfeit.
(5) Face recognition
Face recognition is a technology second to fingerprint recognition in market share and one of the most studied technologies for recognition algorithms. Currently, new imaging methods are emerging, such as: 3D face imaging and infrared face imaging techniques, etc. These methods are all based on the surface imaging of the organism and are easily broken by the silica gel mold.
The group member of the project researches the face thermal infrared imaging technology, mainly reads the face thermal distribution by a thermal imager, reversely calculates the blood vessel distribution of the face according to a thermal gradient propagation formula, and then identifies the face thermal infrared imaging technology. However, the core technology of infrared and thermal infrared CCD is mostly abroad, and the product involves military industry, mass purchasing is difficult in China, and the price is high, so the development of the technology is not optimistic.
(6) Vein recognition
The vein recognition uses near infrared light (generally 910nm) to illuminate parts such as a palm or a finger, images veins, and then carries out filtering, denoising, thinning and feature extraction recognition. The method is used for imaging blood vessels and is one of the highest safety technologies at present; the core patent of the technology is concentrated on Japan company, and because of the need of infrared CCD, the price of the whole machine is very high, thus the technology is not easy to be popularized.
Fingerprint identification, iris identification, face identification, 3D face identification, retina identification, vein identification and other biological identification technologies are all image identification after CCD optical imaging, and along with the fact that products such as finger model beauty pupil masks are higher and higher in manufacturing level, the safety of the technologies is lower and lower; the currently internationally recognized biometric authentication technology which is most widely applied, lowest in price and extremely high in usability is still a fingerprint, and is configured in electronic products such as notebooks, mobile phones and the like, the face technology is called as the most natural and most intuitive biometric identification technology, and compared with other biometric identification modes such as fingerprints and the like, the face identification technology has the remarkable advantages that: intelligent interaction, high user acceptance; the intuition is outstanding, accord with the cognitive rule that people recognize people with appearance; the method has strong adaptability and good safety, and the market share of face recognition is expanded year by year. Iris recognition is a biological recognition technology which combines the best convenience and accuracy at present, in 2005, the national focus laboratory of the department of automation of the Chinese academy of sciences, because of the outstanding score obtained in the aspects of iris image acquisition and recognition technology, the technology of obtaining the national technical utility model, second class rewarding vein recognition, mainly carries out imaging recognition on blood vessels in vivo, because it is very difficult to copy vein patterns of a specific individual, the vein recognition technology has very high safety performance, and is one of the technologies which are considered to be the most promising at present.
The photoacoustic blood vessel strength anti-counterfeiting identification technology combines the photoacoustic material characteristics and realizes the identification of the multi-modal biological characteristics through imaging data analysis. The blood vessel topological structure chart can be formed by using different ultrasonic intensities excited by blood to identify and distinguish the truth of the blood vessel.
SUMMERY OF THE UTILITY MODEL
For overcoming the anti-counterfeiting deficiency of the existing vein recognition technology, the utility model provides a photo-acoustic intensity anti-counterfeiting recognition device based on linear array type mini LED, which avoids the defects of unclear collected images of the traditional vein recognition and false identification of forged blood vessels and false pictures, but adopts the photo-acoustic signal threshold value anti-counterfeiting recognition technology of the blood vessels in the region to be detected, thereby not only realizing the imaging of the blood vessel topological structure, but also realizing the accurate recognition of the biological recognition technology by fusing the anti-counterfeiting mode of the photo-acoustic threshold value image; the Diffraction Optical Element (DOE) adopted by the system is hereinafter referred to as a DOE device, the Mini LED light shaping is converted into a linear point overlapping focusing structure, on the basis of ensuring the scanning line area, the linear scanning speed and accuracy are improved, the light intensity on the linear focusing point is improved, the intensity of the detected ultrasonic wave is higher, and the acquired photoacoustic signal threshold information is more accurate. The system can receive the ultrasonic signals of the area to be detected, comprehensively process the photoacoustic signal information flow, and greatly improve the anti-counterfeiting accuracy and the recognition accuracy.
In order to achieve the above purpose, the utility model adopts the following technical scheme:
a photoacoustic intensity anti-counterfeiting recognition device based on a linear array type mini LED comprises a quartz plate, a light source linear array module, a linear array ultrasonic sensing module, a heat dissipation fixing plate, a preposed signal amplification unit, a mechanical displacement device and an anti-counterfeiting recognition unit; the light source linear array module and the linear array ultrasonic sensing module are positioned under the quartz plate; the heat dissipation fixing plate is provided with an M6 threaded hole for mounting the light source linear array module and the linear array ultrasonic sensing module, is connected with the mechanical displacement device through threads, and is controlled by the mechanical displacement device to perform displacement; the light source linear array module is arranged at the fixed plate part for radiating the heat at the left side and the right side of the linear array sensing module; the linear array ultrasonic sensing module is connected with the preposed signal amplifying unit, and the preposed signal amplifying unit is connected with the anti-counterfeiting identification unit through a BNG data line.
The light source linear array module and the linear array ultrasonic sensing module form an angle of 45 degrees, and a Mini LED light source, a collimating mirror and a DOE device are sequentially arranged from bottom to top; the collimator lens is used for collimating the light beam; the DOE device is positioned at the top of the light source linear array module, converts parallel light into focused light and focuses the focused light on a quartz plate; the light beam focusing points of the Mini LEDs on the two sides of the linear array ultrasonic sensing module are overlapped with each other.
Furthermore, the quartz plate is T-shaped, is made of silicon dioxide, has the thickness of 0.5mm, and is attached to the linear array ultrasonic sensing module on the bottom surface for ultrasonic coupling.
Furthermore, the linear array ultrasonic sensing module has the specification of 32 array elements and the size of about 4mm multiplied by 10.35 mm.
Furthermore, the DOE device of the light source linear array module is used for focusing parallel light, so that light rays emitted by the Mini LED are overlapped and focused on the top quartz plate right above the linear array ultrasonic sensing module, the uniformity of the final light rays is better than 85%, the diameter of a focusing light spot is about 0.05mm, and the distance between the light spots is about 0.005 mm.
Furthermore, an ultrasonic array sensor in the linear array ultrasonic sensing module is connected with a preposed signal amplification unit, and the amplified signal is transmitted to the anti-counterfeiting identification unit.
Further, the heat dissipation fixing plate drives the light source linear array module and the linear array ultrasonic sensing module to perform linear displacement while dissipating heat of the Mini LED light source.
Furthermore, the mechanical displacement device adopts a conventional two-dimensional mechanical displacement platform to perform linear displacement along an x-y axis, so as to drive the heat dissipation fixing plate to perform displacement and control the whole system to perform C-scanning.
Furthermore, the anti-counterfeiting identification unit processes the received ultrasonic signals and performs blood vessel imaging and anti-counterfeiting identification. And the mechanical displacement device controls the heat dissipation fixing plate to scan.
Further, the utility model also provides a optoacoustic blood vessel anti-fake identification method based on mini LED of linear array, including following step:
s1: placing the part to be detected (finger or palm and the like) of the detected crowd on a quartz plate, starting a power supply, and exciting a Mini LED light source and a preposed signal amplifying unit to work;
s2: focusing beams with wavelength of 532 +/-5 nm generated by the Mini LED through a DOE device, and converting the beams into linear focusing structures on the surface of a region to be measured;
s3: the linear array ultrasonic sensing module transmits the received ultrasonic signals to the preposed signal amplifying unit for signal amplification;
s4: the amplified signals are transmitted to an anti-counterfeiting identification unit for signal processing, and the intensity of the photoacoustic signals is normalized according to the difference of the received ultrasonic intensities and the time interval in the processing process; reconstructing the blood vessel optical property distribution of the linear array position;
s5: the anti-counterfeiting identification unit controls the mechanical displacement device to displace to complete the scanning of the photoacoustic signal of the region to be detected;
s6: the anti-counterfeiting identification unit analyzes the characteristics of the tissues of the scanning points through the analysis of the normalized ultrasonic signal intensity threshold of the scanning points and extracts signal flow data of the blood vessel optical characteristic distribution at the position of the area array;
s7: performing anti-counterfeiting authentication according to signal stream data distributed by the optical characteristics of the blood vessels to distinguish counterfeit blood vessels;
s8: carrying out characteristic processing on signal flow data of the blood vessel;
s9: matching calculation is carried out on the characteristic quantity of the blood vessel;
s10: and obtaining a matching recognition result by using deep learning or SVM, a neural network and the like.
In the above method, the S6 and S7 specifically include: registering and warehousing the signal flow data of the blood vessel optical characteristic distribution and the blood vessel identification characteristic, and then forming an information matching group with the signal flow data of the blood vessel optical characteristic distribution and the blood vessel identification characteristic obtained in the step S4; by adopting a normalization method to confirm the signal flow intensity of the true blood vessel and the false blood vessel, the normalization process is expressed as follows:
wherein, F (r, t) represents the normalized photoacoustic signal data flow, a and b represent the threshold of a true blood vessel, the threshold of a blood vessel with weak signal and the threshold of a blood vessel with strong signal, respectively, and r represents the photoacoustic signal intensity.
Further, the anti-counterfeiting identification information matching group comprises the signal intensity of the blood vessel and the topological structure of the blood vessel.
Further, in S8, a data flow matching method, a template matching method, or a neural network algorithm is used to perform matching calculation on the blood vessel data flow characteristics and perform classification and identification on the topological structure characteristics of the blood vessels.
Further, in S10, a convolutional neural network is specially used for training the acquired data flow information of the region to be measured and the topology of the blood vessel.
Compared with the prior art, the beneficial effects of the utility model reside in that: the utility model integrates the optoacoustic vascular technology with the artificial intelligence identification technology, can perform optoacoustic vascular threshold vascular anti-counterfeiting and vascular topological structure imaging, and the integration of two technologies of optoacoustic anti-counterfeiting and vascular identification, effectively improves the anti-counterfeiting performance and the accuracy of identification; compared with the traditional method, the linear array ultrasonic sensing module and the DOE device are adopted to convert light rays into a linear point focusing double-overlapping structure, so that the scanning speed is increased and the light intensity on a scanning surface is increased on the basis of ensuring the linear scanning area, the reaching depth of the detected ultrasonic waves is larger, and more information is obtained; the photoacoustic signal data flow is used for anti-counterfeiting authentication and blood vessel topological structure imaging, so that the blood vessel imaging effect is clearer, the anti-counterfeiting performance is better, the accuracy of a biological anti-counterfeiting recognition algorithm is improved, and the method can be widely applied to the fields of biological recognition and the like.
Drawings
Fig. 1 is a schematic structural view of the present invention;
the system comprises a quartz plate 1, a light source linear array module 2, a linear array ultrasonic sensing module 3, a heat dissipation fixing plate 4, a mechanical displacement device 5, a preposed signal amplifying unit 6 and an anti-counterfeiting identification unit 7, wherein the quartz plate is a quartz plate;
FIG. 2 is a schematic structural diagram of a light source linear array module;
the device comprises a Mini LED light source group 201, a collimating mirror 202 and a DOE device 203.
Detailed Description
The following detailed description of the embodiments of the present invention is made with reference to the accompanying drawings:
as shown in fig. 1, a photoacoustic intensity anti-counterfeiting recognition device based on a linear array type mini LED comprises a quartz plate 1, a light source linear array module 2, a linear array ultrasonic sensing module 3, a heat dissipation fixing plate 4, a mechanical displacement device 5, a preposed signal amplification unit 6 and an anti-counterfeiting recognition unit 7; the light source linear array module 2 and the linear array ultrasonic sensing module 3 are positioned under the quartz plate 1; the heat dissipation fixing plate 4 is provided with an M6 threaded hole for mounting the light source linear array module 2 and the linear array ultrasonic sensing module 3, is connected with the mechanical displacement device 5 through threads, and is controlled by the mechanical displacement device 5 to perform displacement; the light source linear array module 2 is arranged at the position of the fixing plate for radiating heat at the left side and the right side of the linear array ultrasonic sensing module 3; the linear array ultrasonic sensing module 3 is connected with a preposed signal amplifying unit 6, and the preposed signal amplifying unit 6 is connected with an anti-counterfeiting identification unit 7 through a BNG data line (a data transmission line with a BNC Connector, a Bayonet Nut Connector snap-fit type Connector).
The light source linear array module 2 and the linear array ultrasonic sensing module 3 form an angle of 45 degrees, and a Mini LED light source group 201, a collimating mirror 202 and a DOE device 203 are sequentially arranged from bottom to top, as shown in fig. 2; the collimating lens 201 is used for collimating and converting light rays emitted by the Mini LED light source group 201 into parallel light rays; the DOE device 203 is located at the bottom of the light source linear array module 2, and focuses the parallel light rays passing through the collimating mirror 202, and the focal point is located right above the linear array ultrasonic sensing module 3.
The quartz plate 1 is T-shaped, is made of silicon dioxide, has the upper thickness of 0.5mm, and is attached to the linear array ultrasonic sensing module 3 at the bottom surface for ultrasonic coupling.
The array element number of the linear array ultrasonic sensing module 3 is not less than 32, and the overall size is about 4mm multiplied by 10.35 mm.
The DOE device 203 of the light source linear array module 2 is used for adjusting parallel light, so that light rays emitted by the left and right Mini LEDs of the linear array ultrasonic sensing module 3 are overlapped and focused on the top quartz plate 1 right above the linear array ultrasonic sensing module 3 and are converted into a focusing linear lattice, the uniformity of the adjusted light rays is better than 90%, the diameter of a focusing light spot is about 0.325mm, and the distance between the light spots is about 0.005 mm.
The ultrasonic transducer in the linear array ultrasonic sensing module 3 is connected with the preposed signal amplifying unit 6 through a BNG line and is connected with the anti-counterfeiting identification unit 7 through a communication transmission line.
The Mini LED light source group 201 can be respectively connected with light beams with the wavelength of 532 +/-5 nm and is used for exciting blood vessels to generate photoacoustic signals.
The heat dissipation fixing plate 4 drives the linear array ultrasonic sensing module 3 and the light source linear array module 2 to perform linear displacement while dissipating heat of the Mini LED light source group 201.
The mechanical displacement device adopts a conventional two-dimensional mechanical displacement platform to carry out linear displacement along an x-y axis, drives the heat dissipation fixing plate to carry out displacement, and controls the whole system to carry out C-scanning.
And the anti-counterfeiting identification unit 7 performs threshold anti-counterfeiting identification according to the acquired photoacoustic signal data stream. The anti-counterfeiting identification device is preferably a computer.
As shown in fig. 1, when the system is used for testing, the method comprises the following steps:
s1: placing the part to be detected (finger or palm and the like) of the crowd to be detected on the quartz plate 1, starting a power supply, and exciting the Mini LED light source group 201 and the preposed signal amplifying unit 6 to work;
s2: a beam with the wavelength of 532 +/-1 nm generated by a light source is shaped through the DOE device 203, and the focused light is converted into a linear focusing lattice type structure on the surface to be measured through the DOE device 203;
s3: the linear array ultrasonic sensing module 3 transmits the received ultrasonic signals to the preposed signal amplifying unit 6 for signal amplification;
s4: the amplified signals are transmitted to an anti-counterfeiting identification unit 7 for signal processing, and the intensity of the photoacoustic signals is normalized according to the difference of the received ultrasonic intensities and the time interval in the processing process. Reconstructing the blood vessel optical property distribution of the linear array position;
s5: the anti-counterfeiting identification unit 7 controls the mechanical displacement device 5 to move in one dimension to complete the scanning of the photoacoustic signal of the region to be detected.
S6: the anti-counterfeiting identification unit 7 analyzes the characteristics of the tissues of the scanning points through the normalized ultrasonic signal intensity threshold analysis of the scanning points, and extracts the signal flow data of the blood vessel optical characteristic distribution at the area array position. Registering and warehousing the signal flow data of the blood vessel optical characteristic distribution and the blood vessel identification characteristic, and then forming an information matching group with the signal flow data of the blood vessel optical characteristic distribution and the blood vessel identification characteristic obtained in the step S4; by taking a normalization approach to make sure the signal flow strength of the vessels and non-vessels, the normalization process is expressed as follows:
wherein, F (r, t) represents the photoacoustic signal data flow after normalization, a and b represent the thresholds of non-blood vessels and blood vessels, the weak blood vessels and the strong blood vessels, respectively, and r represents the photoacoustic signal intensity.
S7: and performing anti-counterfeiting authentication according to the signal stream data distributed by the optical characteristics of the blood vessels to distinguish the forged blood vessels. The anti-counterfeiting identification information matching group comprises the signal intensity of blood vessels and the topological structure of the blood vessels.
S8: and (3) carrying out feature processing on the signal flow data of the blood vessel, namely carrying out matching calculation on the features of the blood vessel data flow and carrying out classification and identification on the topological structure features of the blood vessel by adopting a data flow matching method, a template matching method or a neural network algorithm.
S9: matching calculation is carried out on the characteristic quantity of the blood vessel;
s10: and obtaining a matching identification result by using deep learning. And training the obtained data flow information and the topological structure of the blood vessel by using a convolutional neural network.
The photoacoustic intensity anti-counterfeiting identification device based on the linear array type mini LED according to the present invention is described above by way of example with reference to the accompanying drawings. However, it should be understood by those skilled in the art that various modifications can be made to the above-mentioned photoacoustic blood vessel anti-counterfeiting identification device based on linear array type ultrasonic sensing without departing from the scope of the present invention. Therefore, the scope of the present invention should be determined by the content of the appended claims.
Claims (6)
1. A photoacoustic intensity anti-counterfeiting recognition device based on a linear array type mini LED is characterized by comprising a quartz plate, a light source linear array module, a linear array ultrasonic sensing module, a heat dissipation fixing plate, a preposed signal amplification unit, a mechanical displacement device and an anti-counterfeiting recognition unit; the light source linear array module and the linear array ultrasonic sensing module are positioned under the quartz plate; the heat dissipation fixing plate is provided with an M6 threaded hole for mounting the light source linear array module and the linear array ultrasonic sensing module, is connected with the mechanical displacement device through threads, and is controlled by the mechanical displacement device to perform displacement; the light source linear array module is arranged at the fixed plate part for radiating the heat at the left side and the right side of the linear array sensing module; the linear array ultrasonic sensing module is connected with a preposed signal amplifying unit, and the preposed signal amplifying unit is connected with the anti-counterfeiting identification unit through a BNG data line; the light source linear array module and the linear array ultrasonic sensing module form an angle of 45 degrees, and a Mini LED light source, a collimating mirror and a DOE device are sequentially arranged from bottom to top; the collimator lens is used for collimating the light beam; the DOE device is positioned at the top of the light source linear array module, converts parallel light into focused light and focuses the focused light on a quartz plate; the light beam focusing points of the Mini LEDs on the two sides of the linear array ultrasonic sensing module are overlapped with each other.
2. The photoacoustic intensity anti-counterfeiting identification device based on the linear array type mini LED according to claim 1, wherein the quartz plate is T-shaped, is made of silicon dioxide, has a thickness of 0.5mm, and is attached to the linear array ultrasonic sensing module on the bottom surface for ultrasonic coupling.
3. The photoacoustic intensity anti-counterfeiting identification device based on the linear array type mini LED of claim 1, wherein the linear array type ultrasonic sensing module has a size of 32 array elements and is about 4mm x 10.35 mm.
4. The photoacoustic intensity anti-counterfeiting identification device based on the linear array type Mini LEDs as claimed in claim 1, wherein the DOE device of the light source linear array module is used for focusing parallel light, so that light emitted by the Mini LEDs is overlapped and focused on the top quartz plate right above the linear array ultrasonic sensing module, the uniformity of the final light is better than 85%, the diameter of a focused light spot is about 0.05mm, and the distance between light spots is about 0.005 mm.
5. The photoacoustic intensity anti-counterfeiting identification device based on the linear array type Mini LED according to claim 1 or 4, wherein the Mini LED light sources are in a linear array type, have a size of 32, have a single size of 0.2mm, and are connected into a light beam with a wavelength of 532 +/-5 nm to excite a blood vessel to generate photoacoustic signals.
6. The photoacoustic intensity anti-counterfeiting identification device based on the linear array type mini LED as claimed in claim 1, wherein the ultrasonic array sensor in the linear array ultrasonic sensing module is connected with a preposed signal amplifying unit, and the amplified signal is transmitted to the anti-counterfeiting identification unit.
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