CN108416882B - Portable fingerprint identification device - Google Patents
Portable fingerprint identification deviceDownload PDFInfo
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- CN108416882B CN108416882BCN201810272016.6ACN201810272016ACN108416882BCN 108416882 BCN108416882 BCN 108416882BCN 201810272016 ACN201810272016 ACN 201810272016ACN 108416882 BCN108416882 BCN 108416882B
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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
- G07C9/30—Individual registration on entry or exit not involving the use of a pass
- G07C9/32—Individual registration on entry or exit not involving the use of a pass in combination with an identity check
- G07C9/37—Individual registration on entry or exit not involving the use of a pass in combination with an identity check using biometric data, e.g. fingerprints, iris scans or voice recognition
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
- G06V40/12—Fingerprints or palmprints
- G06V40/13—Sensors therefor
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
- G06V40/12—Fingerprints or palmprints
- G06V40/1347—Preprocessing; Feature extraction
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Abstract
Description
Technical Field
The invention belongs to the technical field of security and image processing, and particularly relates to a portable fingerprint identification device.
Background
Biometric identification is a new identity authentication technique. In real life, everyone has a unique biometric characteristic that is different from others. With the development of computer technology, people can extract their own biological feature information, such as human face, fingerprint, finger vein, iris, voiceprint, etc. Such a technique of identification by means of physical characteristics of a person is called a biometric technique.
Recently, the importance of technologies for security authentication is increasing due to the development of smart phones and various mobile and wearable devices. Among such forms of technology, fingerprint recognition technology is widely used due to high convenience, security, and economic feasibility. In general fingerprint recognition, user authentication or verification may be performed by acquiring a fingerprint image of a user via a recognition sensor and comparing the acquired fingerprint image with a pre-registered fingerprint image. When elaborate dummy fingerprint patterns are input into the sensor, the fingerprint identification device may not be able to distinguish the dummy fingerprint patterns from the genuine fingerprint patterns, and thus may identify the dummy fingerprint patterns as a biometric fingerprint. For example, when a fingerprinted material (such as rubber, silicone, gelatin, epoxy, and latex) comes into contact with a sensor, the fingerprint printed on such material may be recognized as a human fingerprint. Therefore, identity identification is easy to forge and deceive only by using single biological characteristics (single-mode biological characteristics), for example, a single fingerprint picture is easy to forge and is easy to imitate and steal, and fingerprint identification is originally used in the field of crimes, so that some users have a conflict psychology, and the single fingerprint (vein and the like) characteristics of some users cannot collect effective and clear images, so that the single-mode biological characteristic system has certain limitation in practical application. And the multi-mode biological characteristic system improves the safety factor, reduces the risk of the identification system being broken, and has higher applicability.
Disclosure of Invention
In view of the above analysis, in order to improve the accuracy of identifying the real human body characteristic parameters and the safety of the identification of the entrance guard unit, the present invention provides a portable fingerprint identification device for fingerprint identification of the entrance guard unit having an identification sensor, comprising:
a first fingerprint image acquisition and storage unit for obtaining a first fingerprint image by means of an identification sensor, the first fingerprint image comprising a first portion and a second portion;
a first local analysis unit for performing a first local analysis on the first portion of the first fingerprint image to obtain a first local analysis result;
a first remote analysis unit for performing a first remote analysis on the second portion of the first fingerprint image to obtain a first remote analysis result;
a first judging unit used for obtaining a second fingerprint image by re-detecting the fingerprint after the temperature of the entrance guard unit is raised and simultaneously detecting the polar coordinate included angle theta between the finger to be identified and the identification plane of the identification sensor when the first local analysis result meets the condition that the first local analysis result is smaller than the first characteristic value and larger than the second characteristic valuemn∈[0,1]The second fingerprint image comprises a third part and a fourth part; otherwise, prompting that the second fingerprint image cannot be obtained without recognition;
the second local analysis unit is used for carrying out second local analysis on the third part of the second fingerprint image to obtain a second local analysis result;
the second remote analysis unit is used for carrying out second remote analysis on the fourth part of the second fingerprint image to obtain a second remote analysis result; and determining a fingerprint identification result of the access control unit according to the first local analysis result, the second local analysis result, the first remote analysis result and the second remote analysis result.
Further, the first local analysis unit includes:
the first neighborhood determining unit is used for taking the image geometric center of the first part as the center and the data in the neighborhood with the preset length as the radius as the data of the first part of the image to be processed;
the first preprocessing unit is used for carrying out binarization and noise reduction on the first partial image data to be processed to obtain a data set O;
the encryption unit is used for symmetrically encrypting the data set O to obtain a data set O';
a first feature value obtaining unit, configured to perform the following processing on the data set O' and the preset reference fingerprint data M: carrying out binarization processing on preset reference fingerprint data M to obtain M'; calculating to obtain a diagonal matrix of the data set O'; according to the order of the diagonal matrix, intercepting a middle matrix P with the same order from a first value at the upper left corner of the data set M'; the eigenvalues K1 of the matrix cross-multiplied by the intermediate matrix P with the data set O' are calculated.
Further, the first remote analysis unit includes:
a first transmission unit for transmitting the second portion of the first fingerprint image to a remote server;
the first Hash value determining unit is used for carrying out Hash operation on the received data of the second part at the remote server to obtain a first Hash value corresponding to the second part;
the second preprocessing unit is used for multiplying the matrix data K corresponding to the second part by a matrix S corresponding to preset reference fingerprint data M, wherein the smaller matrix of the two matrixes is supplemented by a diagonal matrix, and a matrix K' is obtained after multiplication;
the third preprocessing unit is used for obtaining an image data matrix L of the second part by taking the gray centroid of the image of the second part as the center and the preset length as the radius, projecting the matrix L to obtain a matrix L ', and performing cross multiplication on the matrix L ' and the matrix K ', wherein the smaller one of the two matrixes is completed by a diagonal matrix, and the matrix Q is obtained after the cross multiplication;
and the second characteristic value acquisition unit is used for calculating the characteristic value F of the matrix Q.
Further, the second local analysis unit includes:
a second neighborhood determining unit, configured to use data in a neighborhood with a geometric center of the image of the third portion as a center and a preset length as a radius as third partial image data to be processed;
the third preprocessing unit is used for carrying out binarization and noise reduction on third partial image data to be processed to obtain a data set R;
the second encryption unit is used for symmetrically encrypting the data set R by taking the average value of the data set O as a key to obtain a data set R';
a third feature value obtaining unit, configured to perform the following processing on the data set R' and the preset reference fingerprint data M: carrying out binarization processing on preset reference fingerprint data M to obtain M'; calculating to obtain a diagonal matrix of the data set R'; according to the order of the diagonal matrix, intercepting a middle matrix T with the same order from a first value at the upper left corner of the data set M'; the eigenvalues K2 of the matrix cross-multiplied by the intermediate matrix T with the data set R' are calculated.
Further, the second remote analysis unit includes:
a second transmission unit, configured to transmit the fourth portion of the second fingerprint image to a remote server;
a fourth characteristic value obtaining unit for setting
Wherein k ismnRepresenting a grey value of an image pixel (m, n) of the fourth part;
carrying out gray level conversion Tr () on the image of the fourth part to obtain theta'mn：
wherein
Wherein theta iscThe threshold value for boundary identification is determined by the empirical value of fingerprint boundary identification, and then the following calculation is carried out:
transform coefficient k'mn＝(K-1)θmn
Extracting the image boundary, wherein the extracted image boundary matrix is
Edges＝[k′mn]
Calculating a characteristic value E of the image boundary matrix;
the second Hash value determining unit is used for carrying out Hash operation on the received data of the fourth part at the remote server to obtain a second Hash value corresponding to the fourth part;
and the third Hash value determining unit is used for carrying out Hash operation on the preset reference fingerprint data to obtain a third Hash value.
Further, the second remote analysis unit further includes a recognition result determination unit for determining a fingerprint recognition result of the access control unit, including:
the similarity calculation unit is used for adding the first Hash value and the second Hash value and carrying out consistent Hash operation, and calculating the similarity a of the operation result and the third Hash value by using a MinHash algorithm;
a recognition result determination unit for determining
And whether the identification is smaller than a preset identification threshold value or not is judged, if so, the successful identification is prompted, and otherwise, the failed identification is prompted.
The technical scheme of the invention has the following advantages:
the portable fingerprint identification device can respectively calculate the identification factors based on remote and local, the influence of the temperature rise on the null shift generated by the identification sensor of the entrance guard unit in the temperature rise process is not eliminated in the identification process, but is actively considered, and the comparison of the one-time calculation mode of square root calculation is carried out in the calculation of two detection results, so that the identification accuracy of the false object to be identified is improved by about 43 percent through the experiment by neglecting in the analysis and calculation (namely, eliminating in the square root calculation when v is calculated).
Drawings
Fig. 1 shows a block diagram of the components of the device according to the invention.
Detailed Description
As shown in fig. 1, a portable fingerprint recognition device according to a preferred embodiment of the present invention, for fingerprint recognition of an entrance guard unit having a recognition sensor, includes:
a first fingerprint image acquisition and storage unit for obtaining a first fingerprint image by means of an identification sensor, the first fingerprint image comprising a first portion and a second portion;
a first local analysis unit for performing a first local analysis on the first portion of the first fingerprint image to obtain a first local analysis result;
a first remote analysis unit for performing a first remote analysis on the second portion of the first fingerprint image to obtain a first remote analysis result;
a first judging unit used for obtaining a second fingerprint image by re-detecting the fingerprint after the temperature of the entrance guard unit is raised and simultaneously detecting the polar coordinate included angle theta between the finger to be identified and the identification plane of the identification sensor when the first local analysis result meets the condition that the first local analysis result is smaller than the first characteristic value and larger than the second characteristic valuemn∈[0,1]The second fingerprint image comprises a third part and a fourth part; otherwise, prompting that the second fingerprint image cannot be obtained without recognition;
the second local analysis unit is used for carrying out second local analysis on the third part of the second fingerprint image to obtain a second local analysis result;
the second remote analysis unit is used for carrying out second remote analysis on the fourth part of the second fingerprint image to obtain a second remote analysis result; and determining a fingerprint identification result of the access control unit according to the first local analysis result, the second local analysis result, the first remote analysis result and the second remote analysis result.
Further, the first local analysis unit includes:
the first neighborhood determining unit is used for taking the image geometric center of the first part as the center and the data in the neighborhood with the preset length as the radius as the data of the first part of the image to be processed;
the first preprocessing unit is used for carrying out binarization and noise reduction on the first partial image data to be processed to obtain a data set O;
the encryption unit is used for symmetrically encrypting the data set O to obtain a data set O';
a first feature value obtaining unit, configured to perform the following processing on the data set O' and the preset reference fingerprint data M: carrying out binarization processing on preset reference fingerprint data M to obtain M'; calculating to obtain a diagonal matrix of the data set O'; according to the order of the diagonal matrix, intercepting a middle matrix P with the same order from a first value at the upper left corner of the data set M'; the eigenvalues K1 of the matrix cross-multiplied by the intermediate matrix P with the data set O' are calculated.
Further, the first remote analysis unit includes:
a first transmission unit for transmitting the second portion of the first fingerprint image to a remote server;
the first Hash value determining unit is used for carrying out Hash operation on the received data of the second part at the remote server to obtain a first Hash value corresponding to the second part;
the second preprocessing unit is used for multiplying the matrix data K corresponding to the second part by a matrix S corresponding to preset reference fingerprint data M, wherein the smaller matrix of the two matrixes is supplemented by a diagonal matrix, and a matrix K' is obtained after multiplication;
the third preprocessing unit is used for obtaining an image data matrix L of the second part by taking the gray centroid of the image of the second part as the center and the preset length as the radius, projecting the matrix L to obtain a matrix L ', and performing cross multiplication on the matrix L ' and the matrix K ', wherein the smaller one of the two matrixes is completed by a diagonal matrix, and the matrix Q is obtained after the cross multiplication;
and the second characteristic value acquisition unit is used for calculating the characteristic value F of the matrix Q.
Further, the second local analysis unit includes:
a second neighborhood determining unit, configured to use data in a neighborhood with a geometric center of the image of the third portion as a center and a preset length as a radius as third partial image data to be processed;
the third preprocessing unit is used for carrying out binarization and noise reduction on third partial image data to be processed to obtain a data set R;
the second encryption unit is used for symmetrically encrypting the data set R by taking the average value of the data set O as a key to obtain a data set R';
a third feature value obtaining unit, configured to perform the following processing on the data set R' and the preset reference fingerprint data M: carrying out binarization processing on preset reference fingerprint data M to obtain M'; calculating to obtain a diagonal matrix of the data set R'; according to the order of the diagonal matrix, intercepting a middle matrix T with the same order from a first value at the upper left corner of the data set M'; the eigenvalues K2 of the matrix cross-multiplied by the intermediate matrix T with the data set R' are calculated.
Further, the second remote analysis unit includes:
a second transmission unit, configured to transmit the fourth portion of the second fingerprint image to a remote server;
a fourth characteristic value obtaining unit for setting
Wherein k ismnRepresenting a grey value of an image pixel (m, n) of the fourth part;
carrying out gray level conversion Tr () on the image of the fourth part to obtain theta'mn：
wherein
Wherein theta iscThe threshold value for boundary identification is determined by the empirical value of fingerprint boundary identification, and then the following calculation is carried out:
transform coefficient k'mn＝(K-1)θmn
Extracting the image boundary, wherein the extracted image boundary matrix is
Edges＝[k′mn]
Calculating a characteristic value E of the image boundary matrix;
the second Hash value determining unit is used for carrying out Hash operation on the received data of the fourth part at the remote server to obtain a second Hash value corresponding to the fourth part;
and the third Hash value determining unit is used for carrying out Hash operation on the preset reference fingerprint data to obtain a third Hash value.
Further, the second remote analysis unit further includes a recognition result determination unit for determining a fingerprint recognition result of the access control unit, including:
the similarity calculation unit is used for adding the first Hash value and the second Hash value and carrying out consistent Hash operation, and calculating the similarity a of the operation result and the third Hash value by using a MinHash algorithm;
a recognition result determination unit for determining
And whether the identification is smaller than a preset identification threshold value or not is judged, if so, the successful identification is prompted, and otherwise, the failed identification is prompted.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (1)
1. A portable fingerprint recognition device for fingerprint recognition of an access control unit having a recognition sensor, comprising:
a first fingerprint image acquisition and storage unit for obtaining a first fingerprint image by means of an identification sensor, the first fingerprint image comprising a first portion and a second portion;
a first local analysis unit for performing a first local analysis on the first portion of the first fingerprint image to obtain a first local analysis result;
a first remote analysis unit for performing a first remote analysis on the second portion of the first fingerprint image to obtain a first remote analysis result;
the first judging unit is used for re-detecting the fingerprint after the temperature of the entrance guard unit is raised to obtain a second fingerprint image and simultaneously detecting a polar coordinate included angle theta between the finger to be identified and the identification plane of the identification sensor when the first local analysis result meets the condition that the first local analysis result is smaller than a first threshold and larger than a second thresholdmn∈[0,1]The second fingerprint image comprises a third part and a fourth part; otherwise, prompting that the second fingerprint image cannot be obtained without recognition;
the second local analysis unit is used for carrying out second local analysis on the third part of the second fingerprint image to obtain a second local analysis result;
the second remote analysis unit is used for carrying out second remote analysis on the fourth part of the second fingerprint image to obtain a second remote analysis result; determining a fingerprint identification result of the access control unit according to the first local analysis result, the second local analysis result, the first remote analysis result and the second remote analysis result;
the first local analysis unit includes:
the first neighborhood determining unit is used for taking the image geometric center of the first part as the center and the data in the neighborhood with the preset length as the radius as the data of the first part of the image to be processed;
the first preprocessing unit is used for carrying out binarization and noise reduction on the first partial image data to be processed to obtain a data set O;
the encryption unit is used for symmetrically encrypting the data set O to obtain a data set O';
a first feature value obtaining unit, configured to perform the following processing on the data set O' and the preset reference fingerprint data M: carrying out binarization processing on preset reference fingerprint data M to obtain M'; calculating to obtain a diagonal matrix of the data set O'; according to the order of the diagonal matrix, intercepting a middle matrix P with the same order from a first value at the upper left corner of the data set M'; calculating a characteristic value K1 of a matrix obtained by cross multiplication of the intermediate matrix P and the data set O';
the first remote analysis unit includes:
a first transmission unit for transmitting the second portion of the first fingerprint image to a remote server;
the first Hash value determining unit is used for carrying out Hash operation on the received data of the second part at the remote server to obtain a first Hash value corresponding to the second part;
the second preprocessing unit is used for multiplying the matrix data K corresponding to the second part by a matrix S corresponding to preset reference fingerprint data M, wherein the smaller matrix of the two matrixes is supplemented by a diagonal matrix, and a matrix K' is obtained after multiplication;
the third preprocessing unit is used for obtaining an image data matrix L of the second part by taking the gray centroid of the image of the second part as the center and the preset length as the radius, projecting the matrix L to obtain a matrix L ', and performing cross multiplication on the matrix L ' and the matrix K ', wherein the smaller one of the two matrixes is completed by a diagonal matrix, and the matrix Q is obtained after the cross multiplication;
a second eigenvalue acquisition unit for calculating an eigenvalue F of the matrix Q;
the second local analysis unit includes:
a second neighborhood determining unit, configured to use data in a neighborhood with a geometric center of the image of the third portion as a center and a preset length as a radius as third partial image data to be processed;
the third preprocessing unit is used for carrying out binarization and noise reduction on third partial image data to be processed to obtain a data set R;
the second encryption unit is used for symmetrically encrypting the data set R by taking the average value of the data set O as a key to obtain a data set R';
a third feature value obtaining unit, configured to perform the following processing on the data set R' and the preset reference fingerprint data M: carrying out binarization processing on preset reference fingerprint data M to obtain M'; calculating to obtain a diagonal matrix of the data set R'; according to the order of the diagonal matrix, intercepting a middle matrix T with the same order from a first value at the upper left corner of the data set M'; calculating a characteristic value K2 of a matrix obtained by cross multiplication of the intermediate matrix T and the data set R';
the second remote analysis unit includes:
a second transmission unit, configured to transmit the fourth portion of the second fingerprint image to a remote server;
a fourth characteristic value obtaining unit for setting
Wherein k ismnRepresenting a grey value of an image pixel (m, n) of the fourth part;
carrying out gray level conversion Tr () on the image of the fourth part to obtain theta'mn：
wherein
Wherein theta iscThe threshold value for boundary identification is determined by the empirical value of fingerprint boundary identification, and then the following calculation is carried out:
transform coefficient k'mn＝(K-1)θmn
Extracting the image boundary, wherein the extracted image boundary matrix is
Edges＝[k′mn]
Calculating a characteristic value E of the image boundary matrix;
the second Hash value determining unit is used for carrying out Hash operation on the received data of the fourth part at the remote server to obtain a second Hash value corresponding to the fourth part;
the third Hash value determining unit is used for carrying out Hash operation on the preset reference fingerprint data to obtain a third Hash value;
the second remote analysis unit further comprises a recognition result determination unit for determining a fingerprint recognition result of the access control unit, and the second remote analysis unit comprises:
the similarity calculation unit is used for adding the first Hash value and the second Hash value and carrying out consistent Hash operation, and calculating the similarity a of the operation result and the third Hash value by using a MinHash algorithm;
a recognition result determination unit for determining
And whether the identification is smaller than a preset identification threshold value or not is judged, if so, the successful identification is prompted, and otherwise, the failed identification is prompted.
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| CN109376721B (en)* | 2018-12-19 | 2020-01-24 | 江苏恒宝智能系统技术有限公司 | Fingerprint feature extraction method, fingerprint registration method, fingerprint identification method and device |
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