CN108171900B - ATM cash withdrawal system - Google Patents
ATM cash withdrawal system Download PDFInfo
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- CN108171900B CN108171900B CN201711485238.8A CN201711485238A CN108171900B CN 108171900 B CN108171900 B CN 108171900B CN 201711485238 A CN201711485238 A CN 201711485238A CN 108171900 B CN108171900 B CN 108171900B
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- cash
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07F—COIN-FREED OR LIKE APPARATUS
- G07F19/00—Complete banking systems; Coded card-freed arrangements adapted for dispensing or receiving monies or the like and posting such transactions to existing accounts, e.g. automatic teller machines
- G07F19/20—Automatic teller machines [ATMs]
- G07F19/203—Dispensing operations within ATMs
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07F—COIN-FREED OR LIKE APPARATUS
- G07F19/00—Complete banking systems; Coded card-freed arrangements adapted for dispensing or receiving monies or the like and posting such transactions to existing accounts, e.g. automatic teller machines
- G07F19/20—Automatic teller machines [ATMs]
- G07F19/211—Software architecture within ATMs or in relation to the ATM network
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Abstract
The invention provides an ATM cash withdrawal system, which comprises an ATM and a background server, wherein the ATM is connected with the background server; the ATM is provided with a fingerprint collector and a fingerprint processor; the fingerprint collector is used for collecting fingerprint images of the cash-taking users; the fingerprint processor processes the fingerprint image and transmits the obtained fingerprint characteristic parameters to the background server; the background server identifies the identity of the cash-withdrawing user according to the received fingerprint characteristic parameters, then calls bank card information bound with the cash-withdrawing user in advance according to the identity of the cash-withdrawing user and feeds the information back to the ATM, the computer in the ATM judges whether the cash-withdrawing bank card information is consistent with the bank card information bound with the cash-withdrawing user in advance, if so, cash-withdrawing operation is allowed, otherwise, cash-withdrawing operation is refused. The invention applies the fingerprint identification to the ATM cash-getting system, when the cash-getting is carried out, the cash-getting user can carry out cash-getting operation only by one fingerprint without remembering a plurality of passwords, and the cash-getting system is convenient, rapid and safe.
Description
Technical Field
The invention relates to the technical field of cash withdrawal systems, in particular to an ATM cash withdrawal system.
Background
For a long time, when the ATM withdraws money, a bank card is firstly inserted into the ATM, then a password is input, and the ATM withdraws money after confirmation in a bank background. The problem is that the bank cards held by young people are many at present, different bank cards are provided, so that users need to get cash to remember the passwords of the bank cards, the use is troublesome and inconvenient, the users forget the passwords of the bank cards sometimes, the users need to go to a bank business office to handle the bank cards and then re-handle the bank cards, the economic expenditure is increased for the users, and the workload is increased for banks.
Disclosure of Invention
In view of the above problems, the present invention provides an ATM cash withdrawal system.
The purpose of the invention is realized by adopting the following technical scheme:
an ATM cash withdrawal system comprises an ATM machine and a background server; the ATM is connected with the background server through a network. The ATM is provided with a fingerprint collector and a fingerprint processor; the fingerprint collector is used for collecting fingerprint images of the cash-taking users; the fingerprint processor is used for processing the fingerprint image and transmitting the obtained fingerprint characteristic parameters to the background server.
The background server is used for identifying the identity of the cash-withdrawing user according to the received fingerprint characteristic parameters, calling bank card information bound with the cash-withdrawing user in advance according to the identity of the cash-withdrawing user and feeding back the bank card information to the ATM, the computer in the ATM judges whether the cash-withdrawing bank card information is consistent with the bank card information bound with the cash-withdrawing user in advance, if so, cash-withdrawing operation is allowed, otherwise, cash-withdrawing operation is refused.
The invention has the beneficial effects that:
1. the cash-withdrawing user can carry out cash-withdrawing operation only by one fingerprint without remembering a plurality of passwords, and the cash-withdrawing system is convenient, quick and safe;
2. the cash-withdrawing user can not go to the bank business hall to handle the hang-up due to forgetting the password, the economic expenditure and the precious time of the cash-withdrawing user are saved, and a large amount of workload is reduced for bank staff.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
FIG. 1 is a block diagram of the present invention;
FIG. 2 is a block diagram of the fingerprint collector and fingerprint processor of the ATM of the present invention;
FIG. 3 is a block diagram of the architecture of the preprocessing module of the present invention.
Reference numerals:
an ATM machine 1; a background server 2; a fingerprint collector 3; a fingerprint processor 4; a pre-processing module 41; a feature extraction module 42; an enhancement unit 411; a denoising unit 412; and a dividing unit 413.
Detailed Description
The invention is further described with reference to the following examples.
Referring to fig. 1 and 2, an ATM cash-withdrawing system includes an ATM machine 1 and a background server 2; the ATM 1 is connected with the background server 2 through a network. The ATM 1 is provided with a fingerprint collector 3 and a fingerprint processor 4; the fingerprint collector 3 is used for collecting fingerprint images of the users who are presented; the fingerprint processor 4 is configured to process the fingerprint image and transmit the obtained fingerprint characteristic parameters to the background server 2.
The background server 2 is used for identifying the identity of the cash-withdrawing user according to the received fingerprint characteristic parameters, calling bank card information bound with the cash-withdrawing user in advance according to the identity of the cash-withdrawing user, and feeding back the information to the ATM 1, wherein a computer in the ATM 1 judges whether the cash-withdrawing bank card information is consistent with the bank card information bound with the cash-withdrawing user in advance, if so, cash-withdrawing operation is allowed, otherwise, cash-withdrawing operation is refused.
In one embodiment, referring to fig. 2, the fingerprint processor 4 comprises a pre-processing module 41 and a feature extraction module 42; the preprocessing module 41 is used for preprocessing the fingerprint image of the presenting user; the feature extraction module 42 is configured to extract a fingerprint feature parameter from the preprocessed fingerprint image.
In one embodiment, referring to fig. 2 and 3, the pre-processing module 41 includes an enhancement unit 411, a denoising unit 412, and a segmentation unit 413; the enhancement unit 411 is used for performing enhancement processing on the fingerprint image of the user; the denoising unit 412 is configured to remove random noise in the fingerprint image after the enhancement processing; the segmenting unit 413 is configured to segment the denoised fingerprint image.
In one embodiment, the enhancement processing on the fingerprint image of the user refers to the nonlinear transformation on the fingerprint image of the presenting user according to the following formula:
in the formula, Q (a, b) is the gray value of the pixel point (a, b) in the fingerprint image, H (a, b) is the gray value of the pixel point (a, b) in the enhanced fingerprint image, epsilon1And ε2Is a correction factor greater than zero, d1And d2Is the adjustment factor for the adjustment of the position of the object,
is the mean gray value, Q, of the fingerprint imagethIs a set threshold.
Has the advantages that: in the embodiment, the fingerprint image of the user who presents is subjected to nonlinear transformation by adopting the above formula, each pixel point in the collected fingerprint image can be transformed one by one according to different nonlinear transformation formulas, the algorithm can improve the brightness of the pixel point with the lower gray value, and meanwhile, the pixel point with the higher gray value is expanded, so that the lines in the fingerprint image subjected to nonlinear transformation are clearer, and a foundation is laid for the subsequent fingerprint feature extraction.
In one embodiment, the removing random noise in the fingerprint image after the enhancement processing specifically includes:
(1) performing N-layer wavelet decomposition on the fingerprint image after the enhancement processing to obtain a group of wavelet coefficients;
(2) carrying out threshold denoising on a high-frequency wavelet coefficient z in the wavelet coefficients by using the following threshold function to obtain an estimated value of a denoised wavelet coefficient high-frequency component:
in the formula (I), the compound is shown in the specification,
z is a high-frequency wavelet coefficient of the wavelet coefficients, and z is { z ═ z1,z2,…,znN is the number of the high-frequency wavelet coefficients in the wavelet coefficients, TthSetting a threshold value, wherein eta and r are adjustment factors, and N is the number of decomposition layers;
(3) and performing wavelet reconstruction on the estimated value of the high-frequency wavelet coefficient obtained through threshold processing and the low-frequency wavelet coefficient in the wavelet coefficient to obtain the de-noised fingerprint image.
Has the advantages that: in the embodiment, the threshold function is adopted to perform denoising processing on the enhanced fingerprint image, so that random noise in the enhanced fingerprint image can be effectively removed, the threshold function is continuous at the threshold, additional oscillation generated by the denoised fingerprint image is avoided, and the threshold function has a better smooth transition zone near the threshold, so that the denoised fingerprint image is closer to a real image, and the accuracy of subsequently extracting the fingerprint characteristic value is improved.
In one embodiment, segmenting the denoised fingerprint image includes:
(1) dividing the denoised fingerprint image into sub image blocks with the same size;
(2) calculating local division thresholds of all sub image blocks by adopting an OSTU algorithm, and dividing the sub image blocks at different positions by using different thresholds, wherein the threshold calculation formula of the sub image blocks is as follows:
when P is presenti,j(x,y)≥α′i,jThen, the pixel point is a foreground pixel point; otherwise, the pixel is a background pixel.
Wherein, alpha'i,jThe optimal threshold value is the optimal threshold value of the sub image block in the ith row and the jth column; alpha is a global segmentation threshold; alpha is alphai,jA local division threshold value of the ith row and the jth column sub image block; gamma is the gray variance of the de-noised fingerprint image; gamma rayi,jThe gray-scale variance of the sub-image in the ith row and the jth column; u. ofi,jThe mean value of the gray levels of the sub image blocks in the ith row and the jth column is u, and the mean value of the gray levels of the de-noised fingerprint image is u; pi,j(x, y) is the gray value of the pixel point (x, y) in the sub image block of the ith row and the jth column, k1And k2As a weighting factor, { ρi,j(x, y) } represents a set of gray values of all pixel points in the sub-image blocks at the ith row and the jth column;
(3) and acquiring all foreground pixel points, wherein the acquired foreground pixel points are the preprocessed fingerprint images.
Has the advantages that: the denoised fingerprint image is divided into a plurality of sub image blocks with the same size, different thresholds are selected to carry out division processing on the different sub image blocks, and the algorithm is more flexible and can self-adaptively adjust the thresholds. The threshold is determined by the gray level mean value of each sub-image block, the median of the gray level values of the pixel points in each sub-image block and the global gray level mean value, the interference of external conditions such as deflection and dirt of the fingerprint image can be avoided, the image segmentation accuracy is improved, meanwhile, the denoised fingerprint image is segmented, so that when the fingerprint image of a user is identified subsequently, only the detail features in the preprocessed fingerprint image need to be analyzed, the difficulty of extracting the subsequent fingerprint features is reduced, and the identification efficiency is improved.
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 (2)
1. An ATM cash withdrawal system is characterized by comprising an ATM machine and a background server; the ATM is connected with the background server through a network;
the ATM is provided with a fingerprint collector and a fingerprint processor; the fingerprint collector is used for collecting fingerprint images of the cash-taking users; the fingerprint processor is used for processing the fingerprint image and transmitting the obtained fingerprint characteristic parameters to the background server;
the background server is used for identifying the identity of the cash-withdrawing user according to the received fingerprint characteristic parameters, calling bank card information bound with the cash-withdrawing user in advance according to the identity of the cash-withdrawing user and feeding back the bank card information to the ATM, and the computer in the ATM judges whether the cash-withdrawing bank card information is consistent with the bank card information bound with the cash-withdrawing user in advance or not, if so, cash-withdrawing operation is allowed to be carried out, otherwise, cash-withdrawing operation is refused;
the fingerprint processor comprises a preprocessing module and a feature extraction module; the preprocessing module is used for preprocessing the acquired fingerprint image; the feature extraction module is used for extracting fingerprint feature parameters from the preprocessed fingerprint image;
the preprocessing module comprises an enhancing unit, a denoising unit and a segmentation unit; the enhancement unit is used for enhancing the fingerprint image of the user; the denoising unit is used for removing random noise in the fingerprint image after enhancement processing; the segmentation unit is used for carrying out segmentation processing on the denoised fingerprint image;
the removing of the random noise in the fingerprint image after the enhancement processing specifically includes:
(1) performing N-layer wavelet decomposition on the fingerprint image after the enhancement processing to obtain a group of wavelet coefficients;
(2) carrying out threshold denoising on a high-frequency wavelet coefficient z in the wavelet coefficients by using the following threshold function to obtain an estimated value of a denoised wavelet coefficient high-frequency component:
in the formula (I), the compound is shown in the specification,
z is a high-frequency wavelet coefficient of the wavelet coefficients, and z is { z ═ z1,z2,…,znN is the number of the high-frequency wavelet coefficients in the wavelet coefficients, TthSetting a threshold value, wherein eta and r are adjustment factors, and N is the number of decomposition layers;
(3) and performing wavelet reconstruction on the estimated value of the high-frequency wavelet coefficient obtained through threshold processing and the low-frequency wavelet coefficient in the wavelet coefficient to obtain the de-noised fingerprint image.
2. An ATM cash-out system according to claim 1, wherein said enhancement of the user's fingerprint image is a non-linear transformation of the user's fingerprint image according to the following equation:
in the formula, Q (a, b) is the gray value of the pixel point (a, b) in the fingerprint image, H (a, b) is the gray value of the pixel point (a, b) in the enhanced fingerprint image, epsilon1And ε2Is a correction factor greater than zero, d1And d2Is the adjustment factor for the adjustment of the position of the object,
is the mean gray value, Q, of the fingerprint imagethIs a set threshold.
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| CN109870461B (en) * | 2019-03-29 | 2020-04-24 | 泗阳恒润电子有限公司 | Electronic components quality detection system |
| CN111370124A (en) * | 2020-03-05 | 2020-07-03 | 湖南城市学院 | Health analysis system and method based on facial recognition and big data |
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Effective date of registration: 20211215 Address after: 252000 No. 2, Huixin South Road, Gaotang Economic Development Zone, Liaocheng City, Shandong Province (Development Zone Management Committee) Patentee after: GAOTANG Rongzhi Rongzhi Technology Service Co.,Ltd. Address before: 234000 Sanba street, Yongqiao District, Suzhou City, Anhui Province Patentee before: Pan Yongsen |
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