CN111091017A - Cash register optimization method and device of mobile payment device in high-frequency transaction state - Google Patents
Cash register optimization method and device of mobile payment device in high-frequency transaction state Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/14—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
- G06K7/1404—Methods for optical code recognition
- G06K7/1408—Methods for optical code recognition the method being specifically adapted for the type of code
- G06K7/1417—2D bar codes
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K19/00—Record carriers for use with machines and with at least a part designed to carry digital markings
- G06K19/06—Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code
- G06K19/06009—Record carriers for use with machines and with at least a part designed to carry digital markings characterised by the kind of the digital marking, e.g. shape, nature, code with optically detectable marking
- G06K19/06046—Constructional details
- G06K19/06112—Constructional details the marking being simulated using a light source, e.g. a barcode shown on a display or a laser beam with time-varying intensity profile
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/14—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
- G06K7/1404—Methods for optical code recognition
- G06K7/1439—Methods for optical code recognition including a method step for retrieval of the optical code
- G06K7/1447—Methods for optical code recognition including a method step for retrieval of the optical code extracting optical codes from image or text carrying said optical code
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/30—Payment architectures, schemes or protocols characterised by the use of specific devices or networks
- G06Q20/32—Payment architectures, schemes or protocols characterised by the use of specific devices or networks using wireless devices
- G06Q20/327—Short range or proximity payments by means of M-devices
- G06Q20/3276—Short range or proximity payments by means of M-devices using a pictured code, e.g. barcode or QR-code, being read by the M-device
Abstract
The utility model provides a cash register optimization method for mobile payment equipment in a high-frequency transaction state, which comprises the steps of networking the mobile payment equipment arranged in a plurality of scenes and connecting the mobile payment equipment, an electronic terminal and a server cluster; acquiring data of transaction parameters of the mobile payment equipment sent by the server cluster in real time, and generating a two-dimensional code image; and when the payment event is monitored to be triggered, completing the payment operation. The method comprises the steps of firstly carrying out networking, carrying out rough segmentation and secondary segmentation on a payment image by adopting an Otsu algorithm, intercepting a two-dimensional code image as the payment image after receiving payment information sent by a server, and finishing payment operation when a payment event is monitored to be triggered. Therefore, the image recognition operation can be efficiently, accurately and quickly realized aiming at the payment image, and the payment operation can be quickly and efficiently completed. The present disclosure also provides a cash register optimization device of the mobile payment device in the high frequency transaction state.
Description
Technical Field
The disclosure relates to the technical field of mobile payment and the technical field of image recognition, in particular to a cash register optimization method and device of mobile payment equipment in a high-frequency transaction state.
Background
In the prior art, the cash register modes applied to a plurality of scenes are pos machine card swiping modes, cash modes and the like. The electronic terminal is opened for the payer in a few scenes, static two-dimensional codes provided by a plurality of scenes are scanned (in the process of manufacturing and image acquisition of static payment images, impurities, interference and the like are inevitably mixed in the images, so that the problems of noise, blurring and uneven gray scale exist in the images), information of the two-dimensional codes is read, and payment operation is completed. The cash-collecting mode makes the cash-collecting mode single, is not easy to use for users who are used to multi-mode consumption under different scenes, and cannot provide a payment mode with simpler payment action when multiple times of transactions are carried out at specific time under multiple scene conditions, and the payment stability and the payment efficiency are not high.
Disclosure of Invention
In order to solve technical problems in the prior art, the disclosed embodiment provides a cash register optimization method and device for mobile payment equipment in a high-frequency transaction state, wherein the mobile payment equipment arranged in a plurality of scenes is networked, and the mobile payment equipment arranged in the plurality of scenes, an electronic terminal for controlling the mobile payment equipment and a server cluster are connected; the method comprises the steps of acquiring data of a plurality of parameters, which are sent by a server cluster and are suitable for transaction of the mobile payment equipment, in real time, and generating a two-dimensional code image suitable for the mobile payment equipment according to the data of the plurality of parameters; and within a preset time period, when the payment event is monitored to be triggered, completing the payment operation.
In a first aspect, an embodiment of the present disclosure provides a cash register optimization method for a mobile payment device in a high-frequency transaction state, including the following steps: networking mobile payment equipment arranged in a plurality of scenes, and connecting the mobile payment equipment arranged in the plurality of scenes, an electronic terminal for controlling the mobile payment equipment and a server cluster; acquiring data of a plurality of parameters which are sent by the server cluster and are suitable for transaction of the mobile payment equipment in real time, and generating a two-dimensional code image suitable for the mobile payment equipment according to the data of the plurality of parameters; and within a preset time period, when the payment event is monitored to be triggered, completing the payment operation.
In one embodiment, the connecting the mobile payment devices arranged in a plurality of scenes, the electronic terminal controlling the mobile payment devices, and the server cluster includes: connecting at least one mobile payment device arranged in a plurality of scenes with a cloud server cluster through WIFI; and connecting the at least one mobile payment device arranged in a plurality of scenes with the electronic terminal for controlling the mobile payment device through Bluetooth connection.
In one embodiment, the method further comprises the following steps: acquiring capability values corresponding to a plurality of protocol stacks in the mobile payment equipment and a channel identifier currently bound with the protocol stack with the maximum value of the capability values; selecting a corresponding channel according to the acquired channel identifier; and completing the payment operation applicable to the mobile payment device through the selected channel.
In one embodiment, the method further comprises the following steps: in a preset time period, when the payment event is monitored to be triggered, and when the electronic terminal is charged, deleting the payment image from the picture library, and setting a default picture in a built-in system of the electronic terminal as a prompt image; and when the current electric quantity of the electronic terminal is lower than a preset electric quantity threshold value, setting a default picture in a built-in system of the electronic terminal as a prompt image.
In one embodiment, the method further comprises the following steps: the method comprises the steps of obtaining the illumination intensity of a screen of the electronic terminal and the illumination intensity reflected by the screen of the electronic terminal in a preset time period, and constructing a screen illumination intensity database aiming at the electronic terminal and a screen reflection illumination intensity database aiming at the electronic terminal.
In one embodiment, the method further comprises the following steps: intercepting the generated two-dimensional code image suitable for the mobile payment equipment, and dividing the payment image after the two-dimensional code image is intercepted as the payment image; according to the Dajin algorithm, performing rough segmentation operation on the region of interest in the divided payment image; performing secondary segmentation on the roughly segmented payment image by using an active contour model of a gradient vector flow; and completing the segmentation operation suitable for the payment image by shape testing on the result obtained after the secondary segmentation operation.
In one embodiment, the dividing the payment image includes: selecting a segmentation channel based on statistical rules of the payment image data of training samples; selecting a segmentation threshold value in the segmentation channel, and performing foreground and background segmentation on the payment image; and carrying out communication area analysis according to the segmented foreground pixels and background pixels to obtain a qualified two-dimensional code area, wherein the payment image subblocks are divided in the qualified two-dimensional code area in a preset row and preset column dividing mode, and the preset row and the preset column are equivalent numerical values.
In a second aspect, the disclosed embodiments provide a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements the steps of the method described above.
In a third aspect, the disclosed embodiments provide a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method described above when executing the program.
In a fourth aspect, an embodiment of the present disclosure provides a cash register optimization apparatus for a mobile payment device in a high-frequency transaction state, where the apparatus includes: the networking and connecting module is used for networking the mobile payment devices arranged in a plurality of scenes and connecting the mobile payment devices arranged in the plurality of scenes, the electronic terminal for controlling the mobile payment devices and the server cluster; the acquisition and image generation module is used for acquiring data of a plurality of parameters which are sent by the server cluster and are suitable for the transaction of the mobile payment equipment in real time and completing a two-dimensional code image suitable for the mobile payment equipment according to the data of the parameters; and the payment module is used for finishing payment operation when the payment event is triggered in a preset time period.
The invention provides a cash register optimization method and a cash register optimization device of mobile payment equipment in a high-frequency transaction state, which are used for networking the mobile payment equipment arranged in a plurality of scenes and connecting the mobile payment equipment arranged in the plurality of scenes, an electronic terminal for controlling the mobile payment equipment and a server cluster; the method comprises the steps of acquiring data of a plurality of parameters, which are sent by a server cluster and are suitable for transaction of the mobile payment equipment, in real time, and generating a two-dimensional code image suitable for the mobile payment equipment according to the data of the plurality of parameters; and within a preset time period, when the payment event is monitored to be triggered, completing the payment operation. The method comprises the steps of firstly, networking is carried out, a Dajin algorithm is adopted to carry out rough segmentation and secondary segmentation on a payment image, the segmentation operation suitable for the payment image is completed according to the result obtained after the secondary segmentation operation through shape testing, the two-dimensional code image is intercepted as the payment image after the payment information sent by a server is received, and the payment operation is completed when the payment event is monitored to be triggered. Therefore, the image recognition operation can be efficiently, accurately and rapidly realized aiming at the payment image based on a plurality of scene network distribution environments, so that the payment operation can be rapidly and efficiently completed, and the method has the advantages of easiness in use and applicability.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings needed to be used in the description of the embodiments are briefly introduced as follows:
fig. 1 is a schematic flowchart illustrating steps of a cash register optimization method for a mobile payment device in a high-frequency transaction state according to an embodiment of the present invention;
fig. 2 is a schematic flowchart illustrating steps of a cash register optimization method for a mobile payment device in a high-frequency transaction state according to another embodiment of the present invention; and
fig. 3 is a cash register optimizing apparatus of a mobile payment device in a high frequency transaction state according to an embodiment of the present invention.
Detailed Description
The present application will now be described in further detail with reference to the accompanying drawings and examples.
In the following description, the terms "first" and "second" are used for descriptive purposes only and are not intended to indicate or imply relative importance. The following description provides embodiments of the disclosure, which may be combined or substituted for various embodiments, and this application is therefore intended to cover all possible combinations of the same and/or different embodiments described. Thus, if one embodiment includes feature A, B, C and another embodiment includes feature B, D, then this application should also be considered to include an embodiment that includes one or more of all other possible combinations of A, B, C, D, even though this embodiment may not be explicitly recited in text below.
In order to make the objects, technical solutions and advantages of the present invention more clearly understood, the following describes in detail specific embodiments of a cash register optimization method and apparatus for a mobile payment device in a high frequency transaction state according to embodiments and with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It can be understood that the cash collecting mode applied to a plurality of scenes in most cases is a pos machine card swiping mode, a cash payment mode and the like. The electronic terminal is opened for the payer to receive the cash mode under the few scenes, and scan the most static two-dimensional code (static payment image inevitably mix with some impurities, interference and the like in the image in the process of manufacturing and image acquisition, so that the image has the problems of noise, blurring and uneven gray scale) that is provided, the information of the two-dimensional code is read, and the payment operation is completed. It should be noted that the above-mentioned cash-collecting method makes the cash-collecting form single, only has an active payment method, and is not easy to use for the users who are used to multi-way consumption in different scenes, and when there are multi-frequency transactions in a specific time under a plurality of scenes, it is unable to provide a payment method with a more convenient payment action, and it has no stability and high efficiency of payment. Therefore, the method is suitable for efficiently, accurately and quickly recognizing and reading the payment image under the multi-scene networking environment and further completes payment, and becomes a work with academic value and practical significance.
As shown in fig. 1, a schematic flow chart of a cash registering optimization method of a mobile payment device in a high-frequency transaction state in an embodiment specifically includes the following steps:
102, networking the mobile payment devices arranged in a plurality of scenes, and connecting the mobile payment devices arranged in the plurality of scenes, the electronic terminal for controlling the mobile payment devices and the server cluster. Specifically, connecting the mobile payment device arranged in a plurality of scenes, the electronic terminal controlling the mobile payment device and the server cluster comprises: connecting at least one mobile payment device arranged in a plurality of scenes with a cloud server cluster through WIFI; and connecting at least one mobile payment device arranged in a plurality of scenes with an electronic terminal for controlling the mobile payment device through Bluetooth connection. In addition, at least one mobile payment device arranged in a plurality of scenes can be connected with the electronic terminal for controlling the mobile payment device through wired connection. Therefore, the diversity and the multi-selectivity of the networking layout are improved.
And 104, acquiring data of a plurality of parameters which are sent by the server cluster and are suitable for the transaction of the mobile payment equipment in real time, and generating a two-dimensional code image suitable for the mobile payment equipment according to the data of the plurality of parameters.
It should be noted that the setting information required in the two-dimensional code is acquired; converting the acquired setting information into a binary file; carrying out information segmentation processing required by a structural link mode on the converted binary file to generate a plurality of different binary information with structural link characteristic characters, wherein the number of segments in the information segmentation processing required by the structural link mode on the converted binary file can be set by two-dimensional code numerical values in a range of 2-32 according to the size and application of set information; the binary file is disassembled into a plurality of corresponding parts within the range of 2-32, and corresponding start characters and end characters are respectively added before and after the binary file of each part which is disassembled; providing original binary coding information which is coded one by one for a coding part corresponding to each split part; and carrying out encrypted or non-encrypted two-dimensional code encoding on a plurality of different binary information with structural link characteristic characters one by one, and correspondingly sequencing to form a plurality of two-dimensional code images sequenced according to a certain sequence.
Further, the cashier optimization method for the mobile payment device in the high-frequency transaction state, which is related by the present disclosure, further includes: intercepting the generated two-dimensional code image suitable for the mobile payment equipment, and dividing the payment image after the two-dimensional code image is intercepted as the payment image; according to the Otsu algorithm, performing rough segmentation operation on the region of interest in the divided payment image, wherein the Otsu algorithm is to divide the original image into two images, namely a foreground image and a background image, by using a threshold value. Specifically, the prospect is: points, mass moments and average gray levels of the foreground under the current threshold are represented by n1, csum and m 1; background: the number of points, the mass moment and the average gray level of the background under the current threshold are represented by n2, sum-csum and m 2. When the optimal threshold is taken, the difference between the background and the foreground is the largest, and the key is how to select a standard for measuring the difference, namely an Otsu algorithm, namely the maximum between-class variance, which is represented by sb, and the maximum between-class variance which is represented by fmax. Further, regarding the sensitivity of Otsu's algorithm to noise and target size, it only produces better segmentation effect on images with a single peak between classes variance. When the size ratio of the target to the background is very different, the inter-class variance criterion function may present double peaks or multiple peaks, which is not good, but the greater amount of algorithm is the least time-consuming. Further, the formula for the Otsu algorithm is derived as: recording t as a segmentation threshold of the foreground and the background, wherein the number of foreground points accounts for w0 of the image proportion, and the average gray level is u 0; the number of background points is w1 in the image scale, and the average gray scale is u 1. The total average gray scale of the image is: u-w 0 u0+ w1 u 1. The variance of the foreground and background images can be expressed by the following formula:
g (w 0 (u0-u) (u0-u) + w1 (u1-u) (u1-u) (w 0) w1 (u0-u1) (u0-u 1). It should be noted that the above formula is a variance formula. The formula for g can be referred to in probability theory, i.e. the expression for sb as described below. When the variance g is maximum, the difference between the foreground and the background at this time can be considered as maximum, and the gray level t at this time is the optimal threshold sb — w0 — w1 (u1-u0) (u0-u 1).
Further, performing secondary segmentation on the roughly segmented payment image by using an active contour model of the gradient vector flow; and completing the segmentation operation suitable for the payment image by shape testing on the result obtained after the secondary segmentation operation.
Further, it should be noted that dividing the payment image includes: selecting a segmentation channel based on a statistical rule of payment image data of a training sample; selecting a segmentation threshold value in a segmentation channel, and performing foreground and background segmentation on the payment image; and carrying out communication area analysis according to the segmented foreground pixels and background pixels to obtain a qualified two-dimensional code area, wherein the payment image subblocks are divided in the qualified two-dimensional code area in a preset row and preset column dividing mode, and the preset row and the preset column are equivalent numerical values. Thereby providing the necessary data basis for subsequent rapid recognition of the payment image.
Further, selecting the split channel based on statistical rules of the payment image data of the training samples comprises: based on the statistical rules of the payment image data of the training samples, the distribution conditions of the image values in different color channels are obtained, and the color channel with the largest image value variance is obtained from the distribution conditions to form a segmentation channel. In addition, it should be further noted that selecting a segmentation threshold in a segmentation channel, and performing foreground and background segmentation on the payment image includes: obtaining a segmentation threshold value through a minimization algorithm in the Dajin algorithm; acquiring an image pixel value of a payment image; and performing dichotomy segmentation according to the image pixel value and the segmentation threshold value to obtain the foreground and the background. Further, it should be noted that, performing bisection segmentation according to the image pixel value and the segmentation threshold, and acquiring the foreground and the background includes: acquiring a region of which the image pixel value is higher than a segmentation threshold value as a foreground; and acquiring a region of which the image pixel value is lower than or equal to the segmentation threshold as a background.
Furthermore, performing connected region analysis according to the segmented foreground pixels and background pixels, and acquiring the two-dimensional code regions meeting the conditions includes: clustering the segmented foreground pixels and background pixels to form a communication area; and selecting the area with the largest size and meeting the prior position information in the communication area to form a two-dimensional code area meeting the conditions, and outputting the two-dimensional code area meeting the conditions. Further, it should be noted that the performing of the segmentation operation suitable for the payment image by the shape test on the result obtained after the secondary segmentation operation includes: and completing the graph segmentation operation suitable for the payment image according to the result obtained after the secondary segmentation operation through an area test, wherein the area test is to judge whether the number of the pixel points in the region of interest meets a pixel point threshold interval of a preset normal two-dimensional code area. Furthermore, it should be noted that the performing of the segmentation operation applicable to the payment image by the shape test on the result obtained after the secondary segmentation operation includes: completing the graph segmentation operation suitable for the payment image by a simple malformation degree calculation formula gamma l/N on the result obtained after the rough segmentation operation through a malformation degree testpCalculating the degree of deformity of the region of interest, wherein l is the perimeter of the region of interest, and N ispThe number of pixel points in the region of interest is counted; presetting a high threshold gamma of degree of deformityT(ii) a When gamma is less than or equal to gammaTJudging that the result obtained after the rough segmentation operation passes the deformity degree test; when gamma is larger than gamma T, the segmentation method of the active contour model based on the gradient vector flow carries out secondary rough segmentation operation on the region of interest, and completes the segmentation operation suitable for the payment image through shape testing on the result obtained after the secondary rough segmentation operation.
And step 106, in a preset time period, when the payment event is monitored to be triggered, completing the payment operation.
Specifically, within a preset time period, when it is monitored that a payment event is triggered, completing the payment operation includes: establishing a mapping relation between the characteristics of the cash register commodity and the price of the cash register commodity; according to the mapping relation, the commodity price in each commodity and the price of the commodity corresponding to the current payment image are obtained; and finishing the cash register operation according to the price of the commodity corresponding to the current payment image. And obtaining the commodity price of each commodity according to the mapping relation, accumulating the commodity prices, and obtaining the price of the commodity corresponding to the current payment image. It can be understood that the prices of the accumulated commodities are pre-stored, and the prices of the commodities can be quickly analyzed and obtained through neural network learning according to historical data of user shopping. It should be noted that, in order to increase the user experience, the data of the cash register operation and the completion status are displayed.
In one embodiment, it should be noted that the cash register optimization method for a mobile payment device in a high frequency transaction state according to the present disclosure further includes: after the payment event is monitored to be triggered, when the electronic terminal is charged, deleting the payment image from the picture library, and setting a default picture in a built-in system of the electronic terminal as a prompt image; and when the current electric quantity of the electronic terminal is lower than a preset electric quantity threshold value, setting a default picture in a built-in system of the electronic terminal as a prompt image. The prompt image is a power-off low-power prompt image of the mobile payment device. In addition, the method further comprises the following steps: the method comprises the steps of obtaining the illumination intensity of a screen of the electronic terminal and the illumination intensity reflected by the screen of the electronic terminal in a preset time period, and constructing a screen illumination intensity database aiming at the electronic terminal and a screen reflection illumination intensity database aiming at the electronic terminal. Therefore, payment operation can be completed quickly and accurately by adapting corresponding illumination intensity of different mobile payment equipment models according to different scenes.
In order to more clearly and accurately understand and apply the cash register optimization method of the mobile payment device in the high frequency transaction state according to the present disclosure, the following example is made in conjunction with fig. 2, and it should be noted that the scope of protection of the present disclosure is not limited to the following example.
Specifically, the steps 201 to 208 are sequentially: receiving a plurality of images; dividing N × N subblocks into the image, performing rough segmentation operation through an Otsu algorithm, judging whether the region of interest accords with the basic form of the two-dimensional code, and if the region of interest accords with the basic form of the two-dimensional code, sending the image of the region of interest to a preset feature model to finish feature extraction of the payment image; if the region of interest does not accord with the basic form of the two-dimensional code, performing secondary segmentation operation on the active contour model based on the gradient vector flow, and then judging whether the region of interest accords with the basic form of the two-dimensional code, if so, sending the image of the region of interest to a preset feature model to finish feature extraction of the payment image; and if the region of interest does not conform to the basic form of the two-dimensional code, removing impurities in the payment image.
It is understood that the received payment image is divided; according to the Dajin algorithm, performing rough segmentation operation and secondary segmentation operation on the region of interest in the divided payment image; and completing the segmentation operation suitable for the payment image according to the result obtained after the secondary segmentation operation through shape testing. Specifically, for a payment image, the payment image is roughly segmented by adopting an Otsu algorithm and secondarily segmented by an active contour model of a gradient vector flow to obtain the payment image which is free of noise and convenient to read; the results of the above segmentation were then subjected to shape testing.
It should be noted that the test conditions are: and (6) area testing. Number N Of pixels in ROI (Region Of Interest)pI.e. whether the ROI area conforms to the range of the normal two-dimensional code area [ Nmin,Nmax]Within; and (5) testing the degree of deformity. Calculating the formula gamma as l/N by simple malformation degreepCalculating the malformation degree of the ROI region, wherein l is the perimeter of the ROI and is provided with a high malformation degree threshold value gammaTWhen gamma is less than or equal to gammaTThe test passed. Further, if the test condition passes, the ROI is a payment image and enters a feature extraction module; if the ROI region that does not pass the test condition, i.e., the pay image with noise or foreign matter, is possible, the segmentation method based on the active contour model of the gradient vector flow performs a secondary segmentation on the ROI region, and then performs a shape test on the secondary segmentation result, with the test condition being as described above. Wherein, as will be understood by those skilled in the art, measuringIf the test fails, the ROI is impurities and is directly discarded; and the ROI passing the test is a payment image, and a preset feature extraction module is used for carrying out feature extraction on the payment image.
As will be understood by those skilled in the art, the classical active contour model often has certain disadvantages when selecting an initial contour curve, such as being far away from a target curve and unable to converge on the target curve, and also has a poor convergence effect on a concave edge. Aiming at the problems, the traditional active contour model is improved, and an active contour model based on gradient vector flow is provided. The active contour model based on gradient vector flow replaces a Gaussian potential energy field in a traditional model, and the mathematical theoretical basis of the active contour model is Helmholtz theorem in an electromagnetic field. Compared with a Gaussian potential energy field, the gradient vector diagram of the whole image is obtained based on the field of the gradient vector flow, so that the action range of the external force field is larger. This also means that even if the selected initial contour is far from the target contour, it will eventually converge to the target contour through successive approximation. Meanwhile, after the external force action range is enlarged, the external force action of the concave part at the target contour is enlarged, so that the boundary can be converged to the concave part.
The invention provides a cash register optimization method of mobile payment equipment in a high-frequency transaction state, which comprises the steps of networking the mobile payment equipment arranged in a plurality of scenes, and connecting the mobile payment equipment arranged in the plurality of scenes, an electronic terminal for controlling the mobile payment equipment and a server cluster; the method comprises the steps of acquiring data of a plurality of parameters, which are sent by a server cluster and are suitable for transaction of the mobile payment equipment, in real time, and generating a two-dimensional code image suitable for the mobile payment equipment according to the data of the plurality of parameters; and within a preset time period, when the payment event is monitored to be triggered, completing the payment operation. The method comprises the steps of firstly, networking is carried out, a Dajin algorithm is adopted to carry out rough segmentation and secondary segmentation on a payment image, the segmentation operation suitable for the payment image is completed according to the result obtained after the secondary segmentation operation through shape testing, the two-dimensional code image is intercepted as the payment image after the payment information sent by a server is received, and the payment operation is completed when the payment event is monitored to be triggered. Therefore, the image recognition operation can be efficiently, accurately and rapidly realized aiming at the payment image based on a plurality of scene network distribution environments, so that the payment operation can be rapidly and efficiently completed, and the method has the advantages of easiness in use and applicability.
Based on the same inventive concept, the invention also provides a cash register optimization device of the mobile payment device in the high-frequency transaction state. Because the principle of the device for solving the problems is similar to the cash register optimization method of the mobile payment device in the high-frequency transaction state, the implementation of the device can be realized according to the specific steps of the method, and repeated parts are not repeated.
Fig. 3 is a schematic structural diagram of a cash register optimizing apparatus of a mobile payment device in a high-frequency transaction state in an embodiment. The cashier optimization device 10 of the mobile payment device in the high-frequency transaction state comprises: a networking and connection module 200, an interception and image generation module 400, and a payment module 600.
The networking and connecting module 200 is used for networking mobile payment devices arranged in a plurality of scenes and connecting the mobile payment devices arranged in the plurality of scenes, an electronic terminal for controlling the mobile payment devices and a server cluster; the acquisition and image generation module 400 is used for acquiring data of a plurality of parameters suitable for transaction of the mobile payment device sent by the server cluster in real time and generating a two-dimensional code image suitable for the mobile payment device according to the data of the plurality of parameters; the payment module 600 is configured to complete a payment operation when it is monitored that a payment event is triggered within a preset time period.
The invention provides a cash register optimization device of mobile payment equipment in a high-frequency transaction state, which comprises a networking module, a connecting module, a server cluster and a control module, wherein the networking module is used for networking the mobile payment equipment arranged in a plurality of scenes and connecting the mobile payment equipment arranged in the plurality of scenes, the electronic terminal for controlling the mobile payment equipment and the server cluster; acquiring data of a plurality of parameters suitable for transaction of the mobile payment equipment, which are sent by the server cluster, in real time through the acquisition and image generation module, and generating a two-dimensional code image suitable for the mobile payment equipment according to the data of the plurality of parameters; and finally, the payment module completes payment operation when the payment event is triggered in a preset time period. The device firstly carries out networking, adopts an Otsu algorithm to carry out rough segmentation and secondary segmentation on the payment image, finishes the segmentation operation suitable for the payment image through shape testing on the result obtained after the secondary segmentation operation, intercepts the two-dimensional code image as the payment image after receiving the payment information sent by the server, and finishes the payment operation when monitoring that the payment event is triggered. Therefore, the image recognition operation can be efficiently, accurately and rapidly realized aiming at the payment image based on a plurality of scene network distribution environments, so that the payment operation can be rapidly and efficiently completed, and the method has the advantages of easiness in use and applicability.
In the foregoing, according to the cash register optimization method and apparatus for a mobile payment device in a high-frequency transaction state and the computer-readable storage medium of the embodiment of the disclosure, networking is performed first, a bold algorithm and a quadratic segmentation are performed on a payment image by using an atraumatic algorithm, a segmentation operation suitable for the payment image is completed through a shape test on a result obtained after the quadratic segmentation operation, a two-dimensional code image is intercepted as the payment image after payment information sent by a server is received, and when a payment event is monitored to be triggered, the payment operation is completed. Therefore, the image recognition operation can be efficiently, accurately and rapidly realized aiming at the payment image based on a plurality of scene network distribution environments, so that the payment operation can be rapidly and efficiently completed, and the method has the advantages of easiness in use and applicability. An embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and the computer program is executed by the processor in fig. 1 or fig. 2.
The embodiment of the invention also provides a computer program product containing the instruction. When the computer program product is run on a computer, it causes the computer to perform the method of fig. 1 or fig. 2 described above.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
The foregoing describes the general principles of the present disclosure in conjunction with specific embodiments, however, it is noted that the advantages, effects, etc. mentioned in the present disclosure are merely examples and are not limiting, and they should not be considered essential to the various embodiments of the present disclosure. Furthermore, the foregoing disclosure of specific details is for the purpose of illustration and description and is not intended to be limiting, since the disclosure is not intended to be limited to the specific details so described.
The block diagrams of devices, apparatuses, systems referred to in this disclosure are only given as illustrative examples and are not intended to require or imply that the connections, arrangements, configurations, etc. must be made in the manner shown in the block diagrams. These devices, apparatuses, devices, systems may be connected, arranged, configured in any manner, as will be appreciated by those skilled in the art. Words such as "including," "comprising," "having," and the like are open-ended words that mean "including, but not limited to," and are used interchangeably therewith. The words "or" and "as used herein mean, and are used interchangeably with, the word" and/or, "unless the context clearly dictates otherwise. The word "such as" is used herein to mean, and is used interchangeably with, the phrase "such as but not limited to".
Also, as used herein, the use of "or" in a list of items beginning with "at least one" indicates a separate list, e.g., "A, B or at least one of C" means A or B or C, or AB or AC or BC, or ABC (i.e., A and B and C). Furthermore, the word "exemplary" does not mean that the described example is preferred or better than other examples.
It is also noted that in the systems and methods of the present disclosure, components or steps may be decomposed and/or re-combined. These decompositions and/or recombinations are to be considered equivalents of the present disclosure.
Various changes, substitutions and alterations to the techniques described herein may be made without departing from the techniques of the teachings as defined by the appended claims. Moreover, the scope of the claims of the present disclosure is not limited to the particular aspects of the process, machine, manufacture, composition of matter, means, methods and acts described above. Processes, machines, manufacture, compositions of matter, means, methods, or acts, presently existing or later to be developed that perform substantially the same function or achieve substantially the same result as the corresponding aspects described herein may be utilized. Accordingly, the appended claims are intended to include within their scope such processes, machines, manufacture, compositions of matter, means, methods, or acts.
The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the disclosure. Thus, the present disclosure is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit embodiments of the disclosure to the form disclosed herein. While a number of example aspects and embodiments have been discussed above, those of skill in the art will recognize certain variations, modifications, alterations, additions and sub-combinations thereof.
Claims (10)
1. A cash register optimization method of a mobile payment device in a high-frequency transaction state is characterized by comprising the following steps:
networking mobile payment equipment arranged in a plurality of scenes, and connecting the mobile payment equipment arranged in the plurality of scenes, an electronic terminal for controlling the mobile payment equipment and a server cluster;
acquiring data of a plurality of parameters which are sent by the server cluster and are suitable for transaction of the mobile payment equipment in real time, and generating a two-dimensional code image suitable for the mobile payment equipment according to the data of the plurality of parameters;
and within a preset time period, when the payment event is monitored to be triggered, completing the payment operation.
2. The cash register optimization method for the mobile payment device in the high-frequency transaction state according to claim 1, wherein the connecting the mobile payment device deployed in a plurality of scenes, the electronic terminal controlling the mobile payment device, and the server cluster comprises: connecting at least one mobile payment device arranged in a plurality of scenes with a cloud server cluster through WIFI;
and connecting the at least one mobile payment device arranged in a plurality of scenes with the electronic terminal for controlling the mobile payment device through Bluetooth connection.
3. The cash register optimization method for the mobile payment device in the high-frequency transaction state according to claim 1, further comprising: acquiring capability values corresponding to a plurality of protocol stacks in the mobile payment equipment and a channel identifier currently bound with the protocol stack with the maximum value of the capability values;
selecting a corresponding channel according to the acquired channel identifier;
and completing the payment operation applicable to the mobile payment device through the selected channel.
4. The cash register optimization method for the mobile payment device in the high-frequency transaction state according to claim 1, further comprising: in a preset time period, when the payment event is monitored to be triggered, and when the electronic terminal is charged, deleting the payment image from the picture library, and setting a default picture in a built-in system of the electronic terminal as a prompt image;
and when the current electric quantity of the electronic terminal is lower than a preset electric quantity threshold value, setting a default picture in a built-in system of the electronic terminal as a prompt image.
5. The cash register optimization method for the mobile payment device in the high-frequency transaction state according to claim 1, further comprising: the method comprises the steps of obtaining the illumination intensity of a screen of the electronic terminal and the illumination intensity reflected by the screen of the electronic terminal in a preset time period, and constructing a screen illumination intensity database aiming at the electronic terminal and a screen reflection illumination intensity database aiming at the electronic terminal.
6. The cash register optimization method for the mobile payment device in the high-frequency transaction state according to claim 1, further comprising: intercepting the generated two-dimensional code image suitable for the mobile payment equipment, and dividing the payment image after the two-dimensional code image is intercepted as the payment image;
according to the Dajin algorithm, performing rough segmentation operation on the region of interest in the divided payment image;
performing secondary segmentation on the roughly segmented payment image by using an active contour model of a gradient vector flow;
and completing the segmentation operation suitable for the payment image by shape testing on the result obtained after the secondary segmentation operation.
7. The cash register optimization method for a mobile payment device in a high frequency transaction state according to claim 6, wherein the dividing the payment image comprises: selecting a segmentation channel based on statistical rules of the payment image data of training samples;
selecting a segmentation threshold value in the segmentation channel, and performing foreground and background segmentation on the payment image;
and carrying out communication area analysis according to the segmented foreground pixels and background pixels to obtain a qualified two-dimensional code area, wherein the payment image subblocks are divided in the qualified two-dimensional code area in a preset row and preset column dividing mode, and the preset row and the preset column are equivalent numerical values.
8. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1-7 are implemented when the program is executed by the processor.
10. A cash register optimization device of a mobile payment device in a high-frequency transaction state is characterized by comprising:
the networking and connecting module is used for networking the mobile payment devices arranged in a plurality of scenes and connecting the mobile payment devices arranged in the plurality of scenes, the electronic terminal for controlling the mobile payment devices and the server cluster;
the acquisition and image generation module is used for acquiring data of a plurality of parameters which are sent by the server cluster and are suitable for the transaction of the mobile payment equipment in real time and completing a two-dimensional code image suitable for the mobile payment equipment according to the data of the parameters;
and the payment module is used for finishing payment operation when the payment event is triggered in a preset time period.
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