CN110910591A - Cash registering method and device based on mobile payment device and applied to scenic spot - Google Patents
Cash registering method and device based on mobile payment device and applied to scenic spot Download PDFInfo
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- CN110910591A CN110910591A CN201811090077.7A CN201811090077A CN110910591A CN 110910591 A CN110910591 A CN 110910591A CN 201811090077 A CN201811090077 A CN 201811090077A CN 110910591 A CN110910591 A CN 110910591A
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07G—REGISTERING THE RECEIPT OF CASH, VALUABLES, OR TOKENS
- G07G1/00—Cash registers
- G07G1/12—Cash registers electronically operated
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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
- 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
- G06K7/146—Methods for optical code recognition the method including quality enhancement steps
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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
- G06Q20/3274—Short range or proximity payments by means of M-devices using a pictured code, e.g. barcode or QR-code, being displayed on the M-device
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/136—Segmentation; Edge detection involving thresholding
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/194—Segmentation; Edge detection involving foreground-background segmentation
Abstract
The utility model provides a cash registering method based on mobile payment equipment applied to scenic spots, which connects the mobile payment equipment laid in the scenic spots, an electronic terminal controlling the mobile payment equipment and a server cluster; after receiving payment information sent by the server cluster, intercepting the payment two-dimensional code as a payment image, and storing the payment image into a picture library; and when the payment event is monitored to be triggered, completing the payment operation. The method can efficiently, accurately and quickly realize image recognition operation aiming at the payment image based on the scenic spot networking environment, and has the advantages of easiness in use and applicability. The present disclosure also provides a cash register device based on mobile payment equipment for scenic spots.
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 registering method and device based on mobile payment equipment and applied to scenic spots.
Background
In the prior art, cash collecting modes applied to scenic spots are pos machine card swiping, cash and other modes. The electronic terminal is opened for the payer in a few scenes, static two-dimensional codes provided by the scene area 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 when the users who are used to consume in multiple modes under different scenes are in the scenic spot, cannot provide a simpler payment mode of 'payment action', and has no diversity and applicability.
Disclosure of Invention
In order to solve technical problems in the prior art, the embodiment of the disclosure provides a cash registering method and device based on a mobile payment device, which are applied to scenic spots, wherein a Dajin algorithm is adopted to perform rough segmentation and secondary segmentation on a payment image, the segmentation operation suitable for the payment image is completed through shape testing on a result obtained after the secondary segmentation operation, a payment two-dimensional code is intercepted as the payment image after payment information sent by a server is received, and the payment operation is completed when a payment event is monitored to be triggered.
In a first aspect, the disclosed embodiment provides a mobile payment device-based cash registering method applied to scenic spots, which includes the following steps: connecting mobile payment equipment arranged in a scenic spot, an electronic terminal for controlling the mobile payment equipment and a server cluster; after receiving payment information sent by the server cluster, intercepting a payment two-dimensional code as a payment image, and storing the payment image in a picture library, wherein the payment information is generated by the server cluster according to the payment information acquired by the mobile payment equipment through controlling the payment two-dimensional code displayed by the electronic terminal of the mobile payment equipment; and when the payment event is monitored to be triggered, completing the payment operation.
In one embodiment, the connecting the mobile payment device deployed in the scenic spot, the electronic terminal controlling the mobile payment device, and the server cluster includes: connecting at least one mobile payment device arranged in a scenic spot with a cloud server cluster through WIFI; and connecting the at least one mobile payment device arranged in the scenic spot with the electronic terminal for controlling the mobile payment device through Bluetooth connection.
In one embodiment, the method further comprises the following steps: 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.
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 when the monitoring that the payment event is triggered, then 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 on the price of the commodity corresponding to the current payment image.
In one embodiment, the method further comprises the following steps: after the payment two-dimensional code is intercepted and used as the payment image, the payment image is divided; 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, the disclosed embodiment provides a mobile payment device based cash register device applied to scenic spots, the device includes: the system comprises a connecting module, a payment module and a payment module, wherein the connecting module is used for connecting mobile payment equipment arranged in a scenic spot, an electronic terminal for controlling the mobile payment equipment and a server cluster; the intercepting module is used for intercepting a payment two-dimensional code as a payment image after receiving payment information sent by the server cluster, and storing the payment image in a picture library, wherein the payment information is generated by the server cluster according to the payment information acquired by the mobile payment equipment through controlling the payment two-dimensional code displayed by the electronic terminal of the mobile payment equipment; and the payment module is used for finishing payment operation when the payment event is monitored to be triggered.
The invention provides a cash registering method and a cash registering device based on mobile payment equipment, which are applied to scenic spots, wherein the mobile payment equipment arranged in the scenic spots, an electronic terminal for controlling the mobile payment equipment and a server cluster are connected; after receiving payment information sent by the server cluster, intercepting the payment two-dimensional code as a payment image, and storing the payment image in a picture library, wherein the payment information is generated by the server cluster according to the payment information acquired by the mobile payment equipment through controlling the payment two-dimensional code displayed by an electronic terminal of the mobile payment equipment; and when the payment event is monitored to be triggered, completing the payment operation. The method comprises the steps of roughly dividing a payment image and secondarily dividing the payment image by adopting an Otsu algorithm, completing the division operation suitable for the payment image according to the result obtained after the secondary division operation through a shape test, intercepting a payment two-dimensional code as the payment image after receiving payment information sent by a server, and completing the 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 based on the scenic spot networking environment, 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 flow chart illustrating steps of a mobile payment device-based cash registering method applied to a scenic spot according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating steps of a mobile payment device-based cash registering method applied to a scenic spot according to another embodiment of the present invention; and
fig. 3 is a schematic structural diagram of a mobile payment device-based cash register device applied to a scenic spot in 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 apparent, the following describes in detail a specific implementation of the mobile payment device-based cashier method and apparatus applied in scenic spots by way of an embodiment 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 scenic spots in most cases is pos machine card swiping, cash payment and the like. The electronic terminal is opened for the payer in the cash registering mode under a few scenes, most of static two-dimensional codes provided for the scene area 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), the information of the two-dimensional codes 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, and only has one active payment method, and it is not easy to collect cash when the user who is used to consume in multiple ways in different scenes is in the scene, and it is unable to provide a payment method with a simpler and more convenient "payment action", and it has no diversity and applicability. Therefore, the method is suitable for realizing rapid recognition and reading of payment images efficiently, accurately and quickly in a scenic spot networking environment, and becomes a work with both academic value and practical significance.
As shown in fig. 1, which is a schematic flow chart of a cash registering method based on a mobile payment device applied to a scenic spot in an embodiment, specifically including the following steps:
and 102, connecting the mobile payment equipment arranged in the scenic spot, the electronic terminal for controlling the mobile payment equipment and the server cluster.
Specifically, connecting the mobile payment device arranged in the scenic spot, the electronic terminal controlling the mobile payment device and the server cluster comprises: connecting at least one mobile payment device arranged in a scenic spot with a cloud server cluster through WIFI; and connecting at least one mobile payment device arranged in the scenic spot with an electronic terminal for controlling the mobile payment device through Bluetooth connection. Therefore, the connection efficiency and accuracy are improved. It should be noted that networking is performed in advance for a scenic spot. Specifically, a wireless network of a scenic spot is designed to be in wireless coverage, namely, the scenic spot is a plurality of WIFI coverage areas with requirements, each area can be provided with two base station type outdoor APs, the APs are provided with omnidirectional antennas, the radius of 150 meters in an open environment can be covered, and the requirement of 120 people for surfing the internet can be supported to the maximum extent; in addition, data is transmitted into each coverage area through an optical fiber, which then converts the optical signal into an electrical signal through an optical-to-electrical device. It should be noted that, in the standard gigabit POE module, a network cable from the optical to electrical equipment is connected to the POE module, and then the POE module is directly connected to the base station type outdoor AP; adopted for the data transfer rate are wireless products supporting IEEE 802.11 n. The throughput rate of IEEE 802.11n theoretical data can reach 300 Mbps; the whole wireless network in the scenic spot must have strong anti-interference capability to avoid the influence of electronic interference on the wireless network. Since wireless signals are not only susceptible to external interference but also channels between wireless APs are susceptible to mutual interference. Preferably, the intelligent wireless AP and the wireless network controller are arranged according to this particular scenario of the scenic spot. The wireless network controller dynamically adjusts the wireless channel in real time according to the actual physical environment and the movement condition of the terminal, so that the smoothness and the efficiency of information transmission are improved.
And 104, after receiving the payment information sent by the server cluster, intercepting the payment two-dimensional code as a payment image, and storing the payment image in a picture library, wherein the payment information is generated by the server cluster according to the payment information acquired by the mobile payment equipment through controlling the payment two-dimensional code displayed by the electronic terminal of the mobile payment equipment.
In one embodiment, the present disclosure relates to a mobile payment device-based cash registering method applied to scenic spots, further comprising: after intercepting the payment two-dimensional code as the payment image, dividing 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 > gammaTAnd then, carrying out secondary rough segmentation operation on the region of interest by the segmentation method of the active contour model based on the gradient vector flow, and completing the segmentation operation suitable for the payment image by shape testing on the result obtained after the secondary rough segmentation operation.
And step 106, when the payment event is monitored to be triggered, completing the payment operation.
Specifically, when it is monitored that the payment event is triggered, the 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 mobile payment device-based cash registering method applied to scenic spots 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 mobile payment device-based cash registering method applied to scenic spots, 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 area, wherein l is the perimeter of the ROI, and the malformation degree is set to have a high threshold value gamma T, when gamma is not more than 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, the ROI is not a good if the test is not passedQuality, directly discarding; 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 registering method based on mobile payment equipment, which is applied to scenic spots, and is used for connecting the mobile payment equipment arranged in the scenic spots, an electronic terminal for controlling the mobile payment equipment and a server cluster; after receiving payment information sent by the server cluster, intercepting the payment two-dimensional code as a payment image, and storing the payment image in a picture library, wherein the payment information is generated by the server cluster according to the payment information acquired by the mobile payment equipment through controlling the payment two-dimensional code displayed by an electronic terminal of the mobile payment equipment; and when the payment event is monitored to be triggered, completing the payment operation. The method comprises the steps of roughly dividing a payment image and secondarily dividing the payment image by adopting an Otsu algorithm, completing the division operation suitable for the payment image according to the result obtained after the secondary division operation through a shape test, intercepting a payment two-dimensional code as the payment image after receiving payment information sent by a server, and completing the 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 based on the scenic spot networking environment, 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 device based on the mobile payment device, which is applied to scenic spots. Because the principle of the device for solving the problems is similar to the cash registering method based on the mobile payment device applied to the scenic spot, 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 mobile payment device-based cash register apparatus applied to a scenic spot in one embodiment. The mobile payment device-based cash register device 10 applied to scenic spots comprises: a connection module 200, an intercept module 400 and a payment module 600.
The connection module 200 is used for connecting the mobile payment equipment arranged in the scenic spot, the electronic terminal for controlling the mobile payment equipment and the server cluster; the intercepting module 400 is configured to intercept a payment two-dimensional code as a payment image after receiving payment information sent by a server cluster, and store the payment image in a picture library, where the payment information is generated by the server cluster according to payment information obtained by a mobile payment device by controlling the payment two-dimensional code displayed by an electronic terminal of the mobile payment device; the payment module 600 is configured to complete the payment operation when it is detected that the payment event is triggered.
The invention provides a cash register device based on mobile payment equipment, which is applied to scenic spots, and is characterized in that the mobile payment equipment arranged in the scenic spots, an electronic terminal for controlling the mobile payment equipment and a server cluster are connected through a connecting module; after receiving payment information sent by the server cluster through the intercepting module, intercepting the payment two-dimensional code as a payment image, and storing the payment image into a picture library, wherein the payment information is generated by the server cluster according to the payment information acquired by the mobile payment equipment through controlling the payment two-dimensional code displayed by an electronic terminal of the mobile payment equipment; and finally, when the payment module detects that the payment event is triggered, completing the payment operation. The device adopts the Otsu algorithm to carry out rough segmentation and secondary segmentation on the payment image, completes the segmentation operation suitable for the payment image through the shape test on the result obtained after the secondary segmentation operation, intercepts the payment two-dimensional code as the payment image after receiving the payment information sent by the server, and completes the payment operation when monitoring that the payment event is triggered. Therefore, the image recognition operation can be efficiently, accurately and quickly realized aiming at the payment image based on the scenic spot networking environment, and the method has the advantages of easiness in use and applicability.
In the foregoing, according to the cash registering method and apparatus based on mobile payment device applied to scenic spots and the computer-readable storage medium of the embodiment of the present disclosure, for a payment image, a great amount of algorithm is adopted to perform rough segmentation on the payment image, the segmentation operation applicable to the payment image is completed through shape testing on a result obtained after the rough segmentation operation, if the test condition passes, an area of interest is the payment image, and the payment image enters the feature extraction module; and testing the region of interest which does not pass the test, namely possibly an impurity image, performing secondary segmentation on the region of interest by using the segmentation method of the active contour model based on the gradient vector flow, and then performing shape test on the secondary segmentation result. Therefore, the image recognition operation can be efficiently, accurately and quickly realized aiming at the payment image under the scenic spot networking environment, 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 mobile payment device-based cash registering method applied to scenic spots is characterized by comprising the following steps:
connecting mobile payment equipment arranged in a scenic spot, an electronic terminal for controlling the mobile payment equipment and a server cluster;
after receiving payment information sent by the server cluster, intercepting a payment two-dimensional code as a payment image, and storing the payment image in a picture library, wherein the payment information is generated by the server cluster according to the payment information acquired by the mobile payment equipment through controlling the payment two-dimensional code displayed by the electronic terminal of the mobile payment equipment;
and when the payment event is monitored to be triggered, completing the payment operation.
2. The mobile payment device-based cashier method applied to the scenic spot according to claim 1, wherein the connecting the mobile payment device arranged in the scenic spot, the electronic terminal for controlling the mobile payment device and the server cluster comprises:
connecting at least one mobile payment device arranged in a scenic spot with a cloud server cluster through WIFI;
and connecting the at least one mobile payment device arranged in the scenic spot with the electronic terminal for controlling the mobile payment device through Bluetooth connection.
3. The mobile payment device-based cashier method applied to scenic spots according to claim 1, further comprising: 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.
4. The mobile payment device-based cashier method applied to scenic spots 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.
5. The mobile payment device-based cashier method applied to the scenic spot according to claim 1, wherein when the payment event is monitored to be triggered, the completing the payment operation comprises: 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 on the price of the commodity corresponding to the current payment image.
6. The mobile payment device-based cashier method applied to scenic spots according to claim 1, further comprising: after the payment two-dimensional code is intercepted and used as the payment image, the payment image is divided;
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 mobile payment device-based cashier method applied to the scenic spot 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 mobile payment device based cashier device for use in a scenic spot, the device comprising:
the system comprises a connecting module, a payment module and a payment module, wherein the connecting module is used for connecting mobile payment equipment arranged in a scenic spot, an electronic terminal for controlling the mobile payment equipment and a server cluster;
the intercepting module is used for intercepting a payment two-dimensional code as a payment image after receiving payment information sent by the server cluster, and storing the payment image in a picture library, wherein the payment information is generated by the server cluster according to the payment information acquired by the mobile payment equipment through controlling the payment two-dimensional code displayed by the electronic terminal of the mobile payment equipment;
and the payment module is used for finishing payment operation when the payment event is monitored to be triggered.
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