A fast scanning payment method and device

Abstract

The embodiment of the present invention is applicable to the payment operation of the payment terminal, and discloses a fast scanning payment method and device, server, and storage medium, including: the payment terminal collects image information in the target area under the first image acquisition parameter setting through the camera to obtain a first acquisition image; the payment terminal identifies the content contained in the first acquisition image, and determines the first payment mode according to the recognition result; the payment terminal adopts the second image acquisition parameter setting corresponding to the determined first payment mode, and collects the image information in the target area under the second image acquisition parameter setting through the camera to obtain the second acquisition image; and executes the payment processing flow corresponding to the determined first payment mode according to the collected second acquisition image. The use of this application can reduce the time spent by the user waiting for the payment device to complete the initialization of the payment mode during the payment process, improve the payment efficiency, and enhance the user experience.

Description

Technical Field

[0001] The present invention relates to the field of image recognition and payment technology, and in particular to a fast scanning payment method and device. Background Art

[0002] With the development of science and technology, payment methods such as face recognition and code scanning have penetrated into every aspect of our lives.

[0003] At present, the facial payment devices on the market have only one camera module to support facial recognition and barcode scanning and swiping devices. In the barcode scanning scenario and face swiping scenario, the payment device has different requirements for the camera's exposure mode. Users need to select the working mode first when using it for payment. The payment device will initialize the mode according to the user's selection result. Only after the initialization is completed can the payment operation be performed. Since the payment device mode initialization requires setting the camera's exposure rate, resolution, backlight compensation and other parameters, it takes a long time for users to wait for the payment device to complete the mode initialization, resulting in low payment efficiency and poor experience. Summary of the invention

[0004] The embodiments of the present invention provide a fast scanning payment method and device, so as to reduce the time spent by a user waiting for a payment device to complete a mode initialization process, improve payment efficiency, and enhance user experience.

[0005] In a first aspect, a fast payment scanning method is provided for an embodiment of the present application, comprising:

[0006] The payment terminal collects image information in the target area through a camera under the first image acquisition parameter setting to obtain a first collected image;

[0007] The payment terminal identifies the content contained in the first collected image, and determines a first payment mode according to the identification result;

[0008] The payment terminal adopts the determined second image acquisition parameter setting corresponding to the first payment mode, and acquires image information of the target area by the camera under the second image acquisition parameter setting to obtain a second acquired image;

[0009] The payment processing flow corresponding to the determined first payment mode is executed according to the collected second collected image.

[0010] The payment terminal identifies the content contained in the first collected image and determines the first payment mode according to the identification result, including:

[0011] The mobile terminal identifies that the first captured image contains first specific content, and determines a first payment mode.

[0012] The payment terminal identifies the content contained in the first collected image and determines the first payment mode according to the identification result, including:

[0013] The mobile terminal determines the first payment mode when it recognizes that the first captured image contains second specific content and the proportion of the display area of ​​the second specific content in the first captured image to the first captured image is greater than or equal to a preset proportion threshold.

[0014] The payment terminal identifies the content contained in the first collected image through a detection algorithm, and determines the first payment mode according to the identification result, further comprising:

[0015] The mobile terminal recognizes that the first captured image contains third specific content, and by comparing changes in the third specific content in multiple consecutive captured images including the first captured image, determines that the change in the third specific content meets a preset change condition, and then determines the first payment mode.

[0016] The third specific content includes a mobile phone, a QR code or a face.

[0017] The preset change condition includes any one or more combinations of the following conditions:

[0018] The increase ratio of the display area of ​​the third specific content in the plurality of consecutive collected images reaches a preset ratio threshold;

[0019] The third specific content is changed from being partially displayed in the plurality of continuous collected images to being fully displayed;

[0020] The third specific content is flipped in the multiple consecutive captured images.

[0021] Wherein, by comparing the changes of the third specific content in a plurality of continuous collected images including the first collected image, determining that the changes of the third specific content meet a preset change condition, and then determining the first payment mode includes:

[0022] By comparing the changes in the position of the mobile phone in a plurality of consecutive captured images including the first captured image, it is determined that the mobile phone is taken out by the user and moved toward the camera, and the first payment mode is determined to be scan code payment;

[0023] or

[0024] By comparing the changes in the position of the mobile phone in a plurality of consecutive captured images including the first captured image, it is determined that the mobile phone is operated by the user and displays the screen to the camera, and then the first payment mode is determined to be scan code payment.

[0025] The payment terminal adopts the determined second image acquisition parameter setting corresponding to the first payment mode, including:

[0026] The payment terminal initializes the camera according to the second image acquisition parameter setting, where the second image acquisition parameter setting includes exposure rate, resolution, and backlight compensation corresponding to the first payment mode.

[0027] After the payment terminal adopts the determined second image acquisition parameter setting corresponding to the first payment mode, the method further includes:

[0028] The first payment mode is displayed to the user through a human-computer interaction interface, and an instruction from the user to confirm the use of the first payment mode is received.

[0029] In a second aspect, a fast payment scanning device is provided for an embodiment of the present application, including:

[0030] A first acquisition unit, configured to acquire image information within a target area through a camera under a first image acquisition parameter setting to obtain a first acquired image;

[0031] an identification and determination unit, configured to identify the content contained in the first collected image, and determine a first payment mode according to the identification result;

[0032] a second acquisition unit, configured to adopt the determined second image acquisition parameter setting corresponding to the first payment mode, and acquire image information of the target area by the camera under the second image acquisition parameter setting to obtain a second acquired image;

[0033] A payment unit is used to execute the payment processing flow corresponding to the determined first payment mode according to the collected second collected image.

[0034] Optionally, the identification and determination unit is specifically used to: identify that the first captured image contains first specific content, and then determine a first payment mode.

[0035] Optionally, the identification and determination unit is specifically used to: identify that the first acquired image contains second specific content, and the proportion of the display area of ​​the second specific content in the first acquired image to the first acquired image is greater than or equal to a first preset proportion threshold, and then determine the first payment mode.

[0036] Optionally, the device further comprises:

[0037] The determination unit is used to identify that the first collected image contains a third specific content, and by comparing the changes of the third specific content in a plurality of consecutive collected images including the first collected image, determine that the change of the third specific content meets a preset change condition, and then determine the first payment mode. The third specific content includes a mobile phone, a QR code or a face. The preset change condition includes any one or more of the following conditions:

[0038] The increase ratio of the display area of ​​the third specific content in the plurality of consecutive collected images reaches a second preset ratio threshold;

[0039] The third specific content is changed from being partially displayed in the plurality of continuous collected images to being fully displayed;

[0040] The third specific content is flipped in the multiple consecutive captured images.

[0041] Optionally, determine the unit, specifically for:

[0042] By comparing the changes in the position of the mobile phone in a plurality of consecutive captured images including the first captured image, it is determined that the mobile phone is taken out by the user and moved toward the camera, and the first payment mode is determined to be scan code payment;

[0043] or

[0044] By comparing the changes in the position of the mobile phone in a plurality of consecutive captured images including the first captured image, it is determined that the mobile phone is operated by the user and displays the screen to the camera, and then the first payment mode is determined to be scan code payment.

[0045] Optionally, the second acquisition unit is specifically used to:

[0046] Initialize the camera according to the second image acquisition parameter setting, where the second image acquisition parameter setting includes exposure rate, resolution, and backlight compensation corresponding to the first payment mode.

[0047] Optionally, the device further comprises:

[0048] The human-computer interaction unit is used to display the first payment mode to the user through the human-computer interaction interface and receive an instruction from the user to confirm the use of the first payment mode.

[0049] In a third aspect, another quick scanning payment device is provided for an embodiment of the present application, comprising a processor and a memory, wherein the processor and the memory are interconnected, wherein the memory is used to store application code for the quick scanning payment device to execute the above method, and the processor is configured to execute the method of the above first aspect.

[0050] In a fourth aspect, a computer storage medium is provided for an embodiment of the present application, wherein the computer storage medium stores a computer program, wherein the computer program includes program instructions; when the program instructions are executed by a processor, the processor executes the method of the first aspect described above.

[0051] In the embodiment of the present application, the payment terminal acquires the image information in the target area by the camera under the first image acquisition parameter setting to obtain the first acquisition image, and identifies the content contained in the first acquisition image, and determines the first payment mode according to the recognition result; the payment terminal adopts the second image acquisition parameter setting corresponding to the determined first payment mode, and acquires the image information in the target area by the camera under the second image acquisition parameter setting to obtain the second acquisition image; and executes the payment processing flow corresponding to the determined first payment mode according to the acquired second acquisition image. In this way, the time spent by the user waiting for the payment device to complete the initialization of the payment mode during the payment process can be reduced, the payment efficiency can be improved, and the user's experience can be enhanced. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0053] Figure 1 This is a schematic diagram of a scenario of a fast scanning payment method provided in an embodiment of the present application;

[0054] Figure 2 It is a flowchart of a fast scanning payment method provided in an embodiment of the present application;

[0055] Figure 3 It is a flowchart of another fast scanning payment method provided in an embodiment of the present application;

[0056] Figure 4 It is a flowchart of another fast scanning payment method provided in an embodiment of the present application;

[0057] Figure 5 is a schematic diagram of a situation in which a first captured image includes content provided by an embodiment of the present application;

[0058] Figure 6a-6f is a schematic diagram of a first acquired image provided in an embodiment of the present application;

[0059] Figure 7a-7f is a schematic diagram of a plurality of continuous acquired images including a first acquired image provided in an embodiment of the present application;

[0060] Figure 8a-8b is a schematic diagram of a human-computer interaction interface provided in an embodiment of the present application;

[0061] Fig. 9 It is a structural schematic diagram of a fast scanning payment device provided by an embodiment of the present invention;

[0062] Fig.10 It is a schematic diagram of the structure of another fast scanning payment device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0063] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0064] See also Figure 1 , is a schematic diagram of a scenario of a fast scanning payment method provided by an embodiment of the present application. Figure 1 As shown, the payment terminal 100 collects the collected image 102 of the target area 101 containing a face, a QR code or a mobile phone through the camera in the default mode, analyzes and processes the collected image, automatically predicts the user's payment mode, and completes the parameter setting of the corresponding payment mode in advance according to the predicted payment mode, performs the payment operation in the predicted payment mode, and finally quickly completes the entire payment process. For example, if the predicted payment mode is the code scanning payment mode, and the default mode of the payment terminal is also the code scanning payment mode, the code scanning process can be directly performed and the subsequent payment process can be completed; and if the predicted payment mode is the face scanning payment mode, and the default mode of the payment terminal is the code scanning payment mode, the parameter setting corresponding to the face scanning payment mode can be automatically adjusted, and after completing the parameter setting adjustment corresponding to the face scanning payment mode, the user is prompted that the mode has been switched, and then the face scanning operation can be directly performed, which can effectively avoid the user from wasting time waiting for the payment mode to switch.

[0065] See also Figure 2 , is a flowchart of a fast scanning payment method provided by an embodiment of the present application. Figure 2 As shown, the method embodiment includes the following steps:

[0066] Step S201: The payment terminal uses a camera to collect image information in a target area under the setting of first image collection parameters to obtain a first collected image.

[0067] Here, the payment terminal (corresponding to the above Figure 1The payment terminal 100 in the corresponding embodiment may include a payment device in a supermarket, subway, restaurant, or other place, such as an automatic vending machine. The first image parameter setting is the exposure rate, resolution, and backlight compensation parameter setting of the camera corresponding to the payment terminal in power saving mode, code scanning payment mode, or other modes.

[0068] Specifically, after setting the exposure rate, resolution and backlight compensation parameters corresponding to the first image acquisition parameter setting, the payment terminal acquires the image information in the target area through the camera under the parameter setting to obtain the first acquired image.

[0069] Step S202: the payment terminal identifies the content contained in the first captured image, and determines a first payment mode according to the identification result.

[0070] In a specific implementation manner, the payment terminal identifies that the first captured image contains first specific content, and then determines a first payment mode.

[0071] Here, the first specific content may include any one of a face, a mobile phone or a QR code, and the first payment mode may include a code scanning payment mode, a face recognition payment mode or other payment modes set by the payment terminal.

[0072] The payment terminal determines the type of the first payment mode by identifying the type of face, mobile phone or QR code in the first collected image, wherein the method of identifying the type of face, mobile phone or QR code in the first collected image is not limited to the first classifier method in this embodiment.

[0073] Optionally, when training the first classifier based on the support vector machine algorithm, the payment terminal may collect a large number of sample images containing mobile phones, QR codes or faces, and then use the attribute category corresponding to the sample image (referring to the type of mobile phone, QR code or face contained in the sample image) to annotate each sample data to obtain an annotated image corresponding to the sample image, and then use the annotated image to train the first classifier model based on the support vector machine algorithm. When the model converges and reaches a certain accuracy (referring to the loss function value in the model is less than the loss threshold and the accuracy is greater than the accuracy threshold), the model is saved. The saved model is the first classifier based on the support vector machine algorithm that can correctly identify the mobile phone, QR code or face in the image.

[0074] For example, the first captured image may include content such as: Figure 5 This is just an example, but it is certainly not limited to this example.

[0075] Specifically, if the payment terminal recognizes that the first captured image satisfies condition 1 and includes a face, the first payment mode is determined to be the face-swiping payment mode; if the payment terminal recognizes that the first captured image satisfies condition 2 and includes a mobile phone or condition 3 and includes a QR code, the first payment mode is determined to be the code scanning payment mode.

[0076] For example, see Figure 6a-6c , is a schematic diagram of a first collected image provided in an embodiment of the present application. The collected first collected image is input into a first classifier to obtain a recognition result of whether the first collected image contains a mobile phone, a QR code or a face. If the payment terminal recognizes the first collected image (such as Figure 6a ) satisfies condition 1 including a face, then the first payment mode is determined to be a face payment mode; if the payment terminal recognizes the first collected image (such as Figure 6b ) satisfies situation 2 including a mobile phone, then the first payment mode is determined to be a code scanning payment mode; if the payment terminal recognizes the first captured image (such as Figure 6c If condition 3 is satisfied and includes a QR code, the first payment mode is determined to be a scan code payment mode.

[0077] If the payment terminal recognizes that the first captured image satisfies condition 4 and includes both a mobile phone and a QR code, the first payment mode is determined to be the code scanning payment mode; if the payment terminal recognizes that the first captured image satisfies condition 5 and includes both a mobile phone and a face, the first payment mode can be determined based on the orientation of the front of the mobile phone, whether the mobile phone is in the screen-on state, and the proportion of the display areas of the mobile phone and the face in the entire first captured image.

[0078] For the first captured image that satisfies situation 5 and includes both a mobile phone and a face, the payment terminal determines the type of the first payment mode by identifying the orientation of the front of the mobile phone in the first captured image, whether the mobile phone is in a screen-on state, or the size of the display areas of the mobile phone and the face in the entire first captured image, wherein the method of identifying the orientation of the front of the mobile phone in the first captured image, whether the mobile phone is in a screen-on state, or the size of the display areas of the mobile phone and the face in the entire first captured image is not limited to the second classifier and the third classifier method in the present embodiment.

[0079] Optionally, when training the second classifier based on the support vector machine algorithm, the payment terminal can collect a large number of sample images containing the front and back sides of the mobile phone, the screen on, and the locked screen status, and then use the attribute category corresponding to the sample image (referring to the type of mobile phone screen status contained in the sample image) to annotate each sample data to obtain the annotated image corresponding to the sample image, and then use the annotated image to train the second classifier model based on the support vector machine algorithm. When the model converges and reaches a certain accuracy (referring to the loss function value in the model is less than the loss threshold and the accuracy is greater than the accuracy threshold), save the model. The saved model is the second classifier based on the support vector machine algorithm that can correctly identify the front and back sides, the screen on, and the locked screen status of the mobile phone in the image.

[0080] Optionally, when training the third classifier based on the support vector machine algorithm, the payment terminal can collect a large number of sample images containing mobile phones, QR codes or faces, and then use the attribute category corresponding to the sample image (referring to the type of mobile phones, QR codes or faces in the sample image, and the area and proportion of the above three types of areas in the sample image) to annotate each sample data to obtain the annotated image corresponding to the sample image, and then use the annotated image to train the third classifier model based on the support vector machine algorithm. When the model converges and reaches a certain accuracy (referring to the loss function value in the model is less than the loss threshold and the accuracy is greater than the accuracy threshold), save the model. The saved model is the third classifier based on the support vector machine algorithm that can obtain the area and proportion of the mobile phone, QR code or face area in the image.

[0081] For example, see Figure 6d-6f , is a schematic diagram of a first collected image provided in an embodiment of the present application. The payment terminal inputs the collected first collected image into the first classifier to obtain a recognition result of whether the first collected image contains a mobile phone, a QR code or a face. If the payment terminal recognizes that the first collected image (such as Figure 6d ) in which case 4 includes both a mobile phone and a QR code, the first payment mode is determined to be a scan code payment mode; if the payment terminal recognizes the first captured image (such as Figure 6e ) satisfies condition 5 including both a mobile phone and a face, the first collected image is input into the second classifier, and the output result of the second classifier is that the mobile phone appears in the first collected image in a light-screen state, then the first payment mode is the code scanning payment mode; if the payment terminal recognizes the first collected image (as Figure 6f As shown in the figure, condition 5 includes both a mobile phone and a face. The first captured image is input into the third classifier, and the output result of the third classifier is that the proportion of the display area of ​​the mobile phone in the first captured image is 3%, which is smaller than the proportion of the display area of ​​the face 22%. Then the first payment mode is the face-swiping payment mode.

[0082] Step S203: the payment terminal adopts the determined second image acquisition parameter setting corresponding to the first payment mode, and acquires image information in the target area through the camera under the second image acquisition parameter setting to obtain a second acquired image.

[0083] Optionally, the payment terminal adopts the determined second image acquisition parameter setting corresponding to the first payment mode, including:

[0084] The payment terminal initializes the camera according to the second image acquisition parameter setting, where the second image acquisition parameter setting includes exposure rate, resolution, and backlight compensation corresponding to the first payment mode.

[0085] Here, when the first payment mode is a code scanning payment mode, and the first image acquisition parameter is a parameter corresponding to the code scanning payment mode, the second image acquisition parameter setting is consistent with the first image acquisition parameter, and the payment terminal does not need to be initialized repeatedly. The second image acquisition parameter is set to the exposure rate, resolution and backlight compensation parameter setting of the camera corresponding to the code scanning payment mode of the payment terminal; when the first payment mode is a face recognition payment mode, and the first image acquisition parameter is a parameter corresponding to the code scanning payment mode or other modes, the second image acquisition parameter setting is inconsistent with the first image acquisition parameter, and the payment terminal needs to initialize the camera parameter settings according to the face recognition payment mode, and the second image acquisition parameter is set to the exposure rate, resolution and backlight compensation parameter setting of the camera corresponding to the face recognition payment mode of the payment terminal.

[0086] In one possible implementation, if the payment terminal determines through step S202 that the first payment mode is a code scanning payment mode, since the first image acquisition parameters are parameters corresponding to the code scanning payment mode, the payment terminal does not need to be initialized repeatedly, and directly acquires image information of the target area through the camera to obtain the second acquired image.

[0087] If the payment terminal obtains through step S202 that the first payment mode is the face recognition payment mode, since the first image acquisition parameters are parameters corresponding to the code scanning payment mode, which are different from the parameter settings of the camera corresponding to the face recognition payment mode, the payment terminal needs to initialize the exposure rate, resolution and backlight compensation parameter settings of the camera according to the face recognition payment mode to complete the conversion from the code scanning payment mode to the face recognition payment mode, and then directly collect image information of the target area through the camera to obtain the second collected image.

[0088] Optionally, after the payment terminal adopts the determined second image acquisition parameter setting corresponding to the first payment mode, the method further includes:

[0089] The first payment mode is displayed to the user through a human-computer interaction interface, and an instruction from the user to confirm the use of the first payment mode is received.

[0090] Specifically, after the payment terminal initializes the exposure rate, resolution and backlight compensation parameters of the camera using the first payment mode, the first payment mode is displayed to the user through the human-computer interaction interface. If the first payment mode is a code scanning payment mode, and the second captured image captured by the camera includes a QR code, it means that the user confirms to use the code scanning payment mode; if the first payment mode is a face recognition payment mode, and the second captured image captured by the camera includes a face, it means that the user confirms to use the face recognition payment mode.

[0091] Further, in another possible implementation, if the payment terminal obtains through step S202 that the first payment mode is the code scanning payment mode, since the first image acquisition parameter is a parameter corresponding to the code scanning payment mode, the payment terminal does not need to be initialized repeatedly, and directly displays the first payment mode to the user through the human-computer interaction interface 801, such as Figure 8a As shown, the human-computer interaction interface 801 displays to the user "The current payment mode is the scan code payment mode" and the prompt information "If the scan code payment mode is adopted, please bring the QR code close to the camera, otherwise please click the return key". If the user chooses to adopt the scan code payment mode, the QR code part in the mobile phone is brought close to the camera, and the camera directly collects the image information of the target area to obtain the second collected image; if the user chooses not to adopt the current scan code payment mode, the user returns to the human-computer interaction interface 802 by clicking the return key in the human-computer interaction interface 801.

[0092] If the payment terminal obtains that the first payment mode is the face-scanning payment mode through step S202, since the first image acquisition parameters are parameters corresponding to the code scanning payment mode, which are different from the parameter settings of the camera corresponding to the face-scanning payment mode, the payment terminal needs to initialize the exposure rate, resolution and backlight compensation parameter settings of the camera according to the face-scanning payment mode to complete the conversion from the code scanning payment mode to the face-scanning payment mode, and then display the first payment mode to the user through the human-computer interaction interface 802, such as Figure 8b As shown, the human-computer interaction interface 802 displays to the user "The current payment mode is the face-scanning payment mode" and the prompt message "If the face-scanning payment mode is adopted, please put the face into the frame, otherwise please click the return key". If the user chooses to adopt the face-scanning payment mode, the distance between himself and the camera is moved so that the entire face is in the frame, and the camera collects image information of the target area to obtain a second collected image; if the user chooses not to adopt the current face-scanning payment mode, he returns to the human-computer interaction interface 801 by clicking the return key in the human-computer interaction interface 802.

[0093] S204: Execute the payment processing flow corresponding to the determined first payment mode according to the collected second collected image.

[0094] Specifically, the payment terminal performs different processing on the second collected image to complete different payment processes according to whether the first payment mode determined is a code scanning payment mode or a face recognition payment mode. If the first payment mode is a code scanning payment mode, the payment terminal performs preprocessing, positioning, tilt correction and code word extraction on the second collected image, obtains the QR code payment information, triggers the payment link, and reads the QR code payment information to complete the payment process; or if the first payment mode is a face recognition mode, the payment terminal performs preprocessing, block feature extraction, calculates the positional relationship between features, and compares the face database on the second collected image, obtains the face payment information, triggers the payment link, and reads the face payment information to complete the payment process.

[0095] See also Figure 3 , provides a flow chart of another fast scanning payment method for the embodiment of the present application. Figure 3 As shown, the method embodiment includes the following steps:

[0096] S301: The payment terminal uses a camera to collect image information in a target area under the setting of first image collection parameters to obtain a first collected image.

[0097] Here, the payment terminal (corresponding to the above Figure 1 The payment terminal 100 in the corresponding embodiment may include a payment device in a supermarket, subway, restaurant, or other place, such as an automatic vending machine. The first image parameter setting is the exposure rate, resolution, and backlight compensation parameter setting of the camera corresponding to the payment terminal in power saving mode, code scanning payment mode, or other modes.

[0098] Specifically, after setting the exposure rate, resolution and backlight compensation parameters corresponding to the first image acquisition parameter setting, the payment terminal acquires the image information in the target area through the camera under the parameter setting to obtain the first acquired image.

[0099] S302: The payment terminal identifies that the first collected image contains second specific content, and the proportion of the display area of ​​the second specific content in the first collected image to the first collected image is greater than or equal to a first preset proportion threshold, then determines a first payment mode.

[0100] Here, the second specific content may include any one or more combinations of face, mobile phone or QR code, and the first payment mode includes the code scanning payment mode, face recognition payment mode or other payment mode set by the payment terminal.

[0101] The payment terminal determines the first payment mode based on the proportion of the display area of ​​the face, mobile phone or QR code included in the first acquired image to the entire first acquired image, wherein the method of identifying the proportion of the display area of ​​the face, mobile phone or QR code in the first acquired image to the entire first acquired image is not limited to the third classifier method in this embodiment.

[0102] Optionally, when training the third classifier based on the support vector machine algorithm, the payment terminal can collect a large number of sample images containing mobile phones, QR codes or faces, and then use the attribute category corresponding to the sample image (referring to the type of mobile phones, QR codes or faces in the sample image, and the area and proportion of the above three types of areas in the sample image) to annotate each sample data to obtain the annotated image corresponding to the sample image, and then use the annotated image to train the third classifier model based on the support vector machine algorithm. When the model converges and reaches a certain accuracy (referring to the loss function value in the model is less than the loss threshold and the accuracy is greater than the accuracy threshold), save the model. The saved model is the third classifier based on the support vector machine algorithm that can obtain the area and proportion of the mobile phone, QR code or face area in the image.

[0103] For example, the first captured image may include content such as: Figure 5 This is just an example, but it is certainly not limited to this example.

[0104] Specifically, if the payment terminal recognizes that the first collected image satisfies situation 1 and includes a face, by calculating the percentage of the display area of ​​the face in the first collected image in the entire first collected image, and comparing the obtained percentage result with the first preset ratio threshold, if the percentage result of the display area of ​​the face in the first collected image in the first collected image is greater than or equal to the first preset ratio threshold, then the first payment mode is the face-swiping payment mode; if the payment terminal recognizes that the first collected image satisfies situation 2 and includes a mobile phone or situation 3 and includes a QR code, by calculating the percentage of the display area of ​​the mobile phone or the QR code in the first collected image in the entire first collected image, and comparing the obtained percentage result with the first preset ratio threshold, if the percentage result of the display area of ​​the mobile phone or the QR code in the first collected image in the first collected image is greater than or equal to the first preset ratio threshold, then the first payment mode is the code scanning payment mode; If the payment terminal recognizes that the first captured image satisfies condition 4 and includes both a mobile phone and a QR code, by calculating the percentage of the display area of ​​the mobile phone and the QR code in the first captured image respectively in the entire first captured image, and comparing the obtained percentage result with the first preset ratio threshold, if the percentage result of the display area of ​​the mobile phone or the QR code in the first captured image in the first captured image is greater than or equal to the first preset ratio threshold, then the first payment mode is the scan code payment mode; if the payment terminal recognizes that the first captured image satisfies condition 5 and includes both a mobile phone and a face, by calculating the percentage of the display area of ​​the mobile phone and the face in the first captured image respectively in the entire first captured image, and comparing the obtained percentage result with the first preset ratio threshold, if the percentage result of the display area of ​​the face in the first captured image in the first captured image is greater than or equal to the first preset ratio threshold, then the first payment mode is the face-swiping payment mode. For example, please refer to Figure 6f , is a schematic diagram of a first captured image provided by an embodiment of the present application. Figure 6f As shown, the first acquired image satisfies situation 5 and includes both a mobile phone and a face. The first acquired image is input into the third classifier, and the percentage results of the display area of ​​the mobile phone and the face in the first acquired image in the entire first acquired image are 3% and 22% respectively, and compared with the first preset ratio threshold value 20%. Obviously, the percentage result of the display area of ​​the face in the first acquired image in the first acquired image is 22%, which is greater than or equal to the first preset ratio threshold value 20%, then the first payment mode is the face-swiping payment mode.

[0105] S303: The payment terminal adopts the determined second image acquisition parameter setting corresponding to the first payment mode, and acquires image information in the target area through the camera under the second image acquisition parameter setting to obtain a second acquired image.

[0106] S304: Execute the payment processing flow corresponding to the determined first payment mode according to the collected second collected image.

[0107] Specifically, the payment terminal performs different processing on the second collected image to complete different payment processes according to whether the first payment mode determined is a code scanning payment mode or a face recognition payment mode. If the first payment mode is a code scanning payment mode, the payment terminal performs preprocessing, positioning, tilt correction and code word extraction on the second collected image, obtains the QR code payment information, triggers the payment link, and reads the QR code payment information to complete the payment process; or if the first payment mode is a face recognition mode, the payment terminal performs preprocessing, block feature extraction, calculates the positional relationship between features, and compares the face database on the second collected image, obtains the face payment information, triggers the payment link, and reads the face payment information to complete the payment process.

[0108] See also Figure 4 , provides a flow chart of another fast scanning payment method for the embodiment of the present application. Figure 4 As shown, the method embodiment includes the following steps:

[0109] S401: The payment terminal uses a camera to collect image information in a target area under the setting of first image collection parameters to obtain a first collected image.

[0110] Here, the payment terminal (corresponding to the above Figure 1 The payment terminal 100 in the corresponding embodiment may include a payment device in a supermarket, subway, restaurant, or other place, such as an automatic vending machine. The first image parameter setting is the exposure rate, resolution, and backlight compensation parameter setting of the camera corresponding to the payment terminal in power saving mode, code scanning payment mode, or other modes.

[0111] Specifically, after setting the exposure rate, resolution and backlight compensation parameters corresponding to the first image acquisition parameter setting, the payment terminal acquires the image information in the target area through the camera under the parameter setting to obtain the first acquired image.

[0112] S402, the payment terminal recognizes that the first captured image contains third specific content, and determines that the change of the third specific content meets a preset change condition by comparing the change of the third specific content in multiple consecutive captured images including the first captured image, and then determines the first payment mode.

[0113] Here, the third specific content may include a mobile phone, a QR code or a face, and the first payment mode includes a code scanning payment mode, a face recognition payment mode or other payment modes set by the payment terminal.

[0114] The preset change condition includes any one or more combinations of the following conditions:

[0115] The increase ratio of the display area of ​​the third specific content in the plurality of consecutive collected images reaches a second preset ratio threshold;

[0116] The third specific content is changed from being partially displayed in the plurality of continuous collected images to being fully displayed;

[0117] The third specific content is flipped in the multiple consecutive captured images.

[0118] Specifically, the payment terminal first identifies whether the first collected image includes a mobile phone, a QR code or a human face. If the first collected image includes a mobile phone, a QR code or a human face, the payment terminal may determine the first collected image based on whether the increase ratio of the display area of ​​the mobile phone, the QR code or the human face in a plurality of consecutive collected images including the first collected image reaches a second preset ratio threshold, or based on whether the mobile phone, the QR code or the human face changes from partial display to full display in a plurality of consecutive collected images including the first collected image, or based on whether the mobile phone, the QR code or the human face undergoes a flip change in a plurality of consecutive collected images including the first collected image. Payment mode, wherein the type of face, mobile phone or QR code included in the first collected image is identified, the area of ​​the mobile phone, QR code or face display area in multiple consecutive collected images including the first collected image is identified and calculated in the entire collected image, whether the mobile phone, QR code or face in multiple consecutive collected images including the first collected image has changed from partial display to full display, and whether the mobile phone, QR code or face in multiple consecutive collected images including the first collected image has flipped is identified, which is not limited to the first classifier, third classifier, fourth classifier and fifth classifier in the present embodiment.

[0119] Optionally, when training the first classifier based on the support vector machine algorithm, the payment terminal may collect a large number of sample images containing mobile phones, QR codes or faces, and then use the attribute category corresponding to the sample image (referring to the type of mobile phone, QR code or face contained in the sample image) to annotate each sample data to obtain an annotated image corresponding to the sample image, and then use the annotated image to train the first classifier model based on the support vector machine algorithm. When the model converges and reaches a certain accuracy (referring to the loss function value in the model is less than the loss threshold and the accuracy is greater than the accuracy threshold), the model is saved. The saved model is the first classifier based on the support vector machine algorithm that can correctly identify the mobile phone, QR code or face in the image.

[0120] Optionally, when training the third classifier based on the support vector machine algorithm, the payment terminal can collect a large number of sample images containing mobile phones, QR codes or faces, and then use the attribute category corresponding to the sample image (referring to the type of mobile phones, QR codes or faces in the sample image, and the area and proportion of the above three types of areas in the sample image) to annotate each sample data to obtain the annotated image corresponding to the sample image, and then use the annotated image to train the third classifier model based on the support vector machine algorithm. When the model converges and reaches a certain accuracy (referring to the loss function value in the model is less than the loss threshold and the accuracy is greater than the accuracy threshold), save the model. The saved model is the third classifier based on the support vector machine algorithm that can obtain the area and proportion of the mobile phone, QR code or face area in the image.

[0121] Optionally, when training the fourth classifier based on the support vector machine algorithm, the payment terminal may collect a large number of sample images containing partial and full display of mobile phones, QR codes or faces, and then use the attribute category corresponding to the sample image (referring to the display type of the mobile phone, QR code or face in the sample image) to annotate each sample data to obtain the annotated image corresponding to the sample image, and then use the annotated image to train the fourth classifier model based on the support vector machine algorithm. When the model converges and reaches a certain accuracy (referring to the loss function value in the model is less than the loss threshold and the accuracy is greater than the accuracy threshold), the model is saved. The saved model is the fourth classifier based on the support vector machine algorithm that can correctly identify the change from partial display to full display of mobile phones, QR codes or faces in multiple consecutive collected images.

[0122] Optionally, when training the fifth classifier based on the support vector machine algorithm, the payment terminal may collect a large number of sample images containing the entire process of flipping a mobile phone, a QR code or a face, and then use the attribute category corresponding to the sample image (referring to the type of action in which the mobile phone, QR code or face in the sample image changes) to annotate each sample data to obtain an annotated image corresponding to the sample image, and then use the annotated image to train the fifth classifier model based on the support vector machine algorithm. When the model converges and reaches a certain accuracy (referring to the loss function value in the model is less than the loss threshold and the accuracy is greater than the accuracy threshold), save the model. The saved model is the fifth classifier based on the support vector machine algorithm that can correctly identify the flipping changes of mobile phones, QR codes or faces in multiple consecutive captured images. For example, the first captured image contains content such as Figure 5 This is just an example, but it is certainly not limited to this example.

[0123] For example, see Figures 7a-7d, is a schematic diagram of a plurality of continuous collected images including a first collected image provided in an embodiment of the present application. Figure 7a As shown, the three consecutive collected images including the first collected image include the face area, and as time goes by, the display area of ​​the face in the entire collected image gradually increases. The payment terminal inputs the first collected image into the first classifier, and obtains the recognition result that the first collected image satisfies situation 1 and includes the face. The three consecutive collected images including the first image are input into the third classifier, and the areas of the face display areas in the three consecutive collected images collected in chronological order are 20, 32 and 48 respectively. By calculation, the first increase ratio of the face display area in the first collected image relative to the face display area in the collected image before the first collected image is 5%, and the second increase ratio of the face display area in the collected image after the first collected image relative to the face display area in the first collected image is 6%. Compared with the second preset ratio threshold of 5%, it is obvious that the first increase ratio of 5% and the second increase ratio of 6% are both greater than or equal to the second preset ratio threshold of 5%, and the first payment mode is the face payment mode.

[0124] like Figure 7b As shown, the three consecutive captured images including the first captured image include both the mobile phone and the QR code, and as time goes by, the display area of ​​the mobile phone in the entire captured image changes from the initial mobile phone receiver part to the entire mobile phone display, and the display area of ​​the QR code in the entire captured image changes from not existing at the beginning to partially displayed and then fully displayed. The payment terminal inputs the first captured image into the first classifier, and obtains the recognition result that the first captured image satisfies the situation 4 and includes both the mobile phone and the QR code. The three consecutive captured images including the first captured image are input into the fourth classifier, and the detection result is that the mobile phone and the QR code change from partially displayed to fully displayed in the three consecutive captured images, and the first payment mode is the scan code payment mode.

[0125] like Figure 7c As shown, the three consecutive captured images including the first captured image include the mobile phone and the QR code, and as time goes by, the mobile phone changes from initially facing the camera with its entire back to facing the camera with its entire front. The payment terminal inputs the first captured image into the first classifier, and obtains the recognition result that the first captured image satisfies condition 4 and includes both the mobile phone and the QR code. The three consecutive captured images including the first captured image are input into the fifth classifier, and the detection result is that the three consecutive captured images contain a flip change of the entire mobile phone from facing the camera with its back to facing the camera with its front, and the first payment mode is the code scanning payment mode.

[0126] like Figure 7dAs shown, the three consecutive captured images including the first captured image include the mobile phone and the QR code, and as time goes by, the mobile phone changes from initially partially facing the camera with its back to facing the camera with its entire front. The payment terminal inputs the first captured image into the first classifier, and obtains the recognition result that the first captured image satisfies situation 4 and includes both the mobile phone and the QR code. The three consecutive captured images including the first captured image are respectively input into the fourth classifier and the fifth classifier, and the detection result is that there is a change in the mobile phone from partial display to full display in the three consecutive captured images, and the mobile phone flips from facing the camera with its back to facing the camera with its front, then the first payment mode is the code scanning payment mode.

[0127] In one achievable manner, the payment terminal determines that the mobile phone is taken out by the user and moved toward the camera by comparing changes in the position of the mobile phone in multiple consecutive captured images including the first captured image, and then determines that the first payment mode is scan code payment.

[0128] Specifically, the payment terminal determines the first payment mode based on identifying whether the actions of taking out a mobile phone, clicking the mobile phone, flipping the mobile phone, and moving the mobile phone toward the camera are present in multiple consecutive captured images including the first captured image, wherein the method of identifying whether the actions of taking out a mobile phone, clicking the mobile phone, flipping the mobile phone, and moving the mobile phone toward the camera are present in multiple consecutive captured images including the first captured image is not limited to the sixth classifier method in this embodiment.

[0129] Optionally, when training the sixth classifier based on the support vector machine algorithm, the payment terminal can collect a large number of sample images containing the entire action process of taking out the mobile phone, clicking the mobile phone, flipping the mobile phone, and moving the mobile phone toward the camera, and then use the attribute category corresponding to the sample image (referring to the type of action of the mobile phone being operated in the sample image) to annotate each sample data to obtain the annotated image corresponding to the sample image, and then use the annotated image to train the sixth classifier model based on the support vector machine algorithm. When the model converges and reaches a certain accuracy (referring to the loss function value in the model is less than the loss threshold and the accuracy is greater than the accuracy threshold), save the model. The saved model is the sixth classifier based on the support vector machine algorithm that can correctly identify the type of mobile phone operation in multiple consecutive collected images.

[0130] For example, see Figure 7e , is a schematic diagram of a plurality of continuous collected images including a first collected image provided in an embodiment of the present application. Figure 7eAs shown, three consecutive captured images including the first captured image include a face and a mobile phone, and as time goes by, it is found that in the three consecutive captured images including the first captured image, the user does not have a mobile phone in the hand at the beginning, and then takes out the mobile phone from the handbag, and the mobile phone changes from facing the camera from the back to facing the camera from the front. The payment terminal inputs the first captured image into the first classifier, and obtains the recognition result that the first captured image satisfies condition 5 and includes both a mobile phone and a face. The three consecutive captured images including the first captured image are respectively input into the sixth classifier, and the detection result is that there are changes in the action of taking out the mobile phone, flipping the mobile phone, and moving the mobile phone toward the camera in the three consecutive captured images, and the first payment mode is the code scanning payment mode.

[0131] In another achievable manner, the payment terminal determines that the mobile phone is operated by the user and displays the screen to the camera by comparing the changes in the position of the mobile phone in multiple consecutive captured images including the first captured image, and then determines that the first payment mode is scan code payment.

[0132] For example, see Figure 7f , is a schematic diagram of a plurality of continuous collected images including a first collected image provided in an embodiment of the present application. Figure 7f As shown, in the three consecutive captured images including the first captured image, the user initially holds the mobile phone in a vertical arm posture, then faces the front of the mobile phone to the camera and gradually moves toward the camera, until the user shows the front of the mobile phone to the camera with the arm stretched horizontally. The payment terminal inputs the first captured image into the first classifier, and obtains the recognition result that the first captured image satisfies condition 5 and includes both the mobile phone and the face. The three consecutive captured images including the first captured image are respectively input into the sixth classifier, and the detection result is that there are changes in the actions of clicking the mobile phone, flipping the mobile phone, and moving the mobile phone toward the camera in the three consecutive captured images, and the first payment mode is the code scanning payment mode.

[0133] S403: The payment terminal adopts the determined second image acquisition parameter setting corresponding to the first payment mode, and acquires image information in the target area through the camera under the second image acquisition parameter setting to obtain a second acquired image.

[0134] S404: Execute the payment processing flow corresponding to the determined first payment mode according to the collected second collected image.

[0135] Specifically, the payment terminal performs different processing on the second collected image to complete different payment processes according to whether the first payment mode determined is a code scanning payment mode or a face recognition payment mode. If the first payment mode is a code scanning payment mode, the payment terminal performs preprocessing, positioning, tilt correction and code word extraction on the second collected image, obtains the QR code payment information, triggers the payment link, and reads the QR code payment information to complete the payment process; or if the first payment mode is a face recognition mode, the payment terminal performs preprocessing, block feature extraction, calculates the positional relationship between features, and compares the face database on the second collected image, obtains the face payment information, triggers the payment link, and reads the face payment information to complete the payment process.

[0136] In the embodiment of the present application, the payment terminal acquires the image information in the target area by the camera under the first image acquisition parameter setting to obtain the first acquisition image, and identifies the content contained in the first acquisition image, and determines the first payment mode according to the recognition result; the payment terminal adopts the second image acquisition parameter setting corresponding to the determined first payment mode, and acquires the image information in the target area by the camera under the second image acquisition parameter setting to obtain the second acquisition image; and executes the payment processing flow corresponding to the determined first payment mode according to the acquired second acquisition image. In this way, the time spent by the user waiting for the payment device to complete the initialization of the payment mode during the payment process can be reduced, the payment efficiency can be improved, and the user's experience can be enhanced.

[0137] See also Fig. 9 , the present application embodiment provides a schematic diagram of the structure of a fast scanning payment device. Fig. 9 As shown, the fast scanning payment device includes a first collection unit 901 , an identification and determination unit 902 , a second collection unit 903 , a payment unit 904 , a determination unit 905 and a human-computer interaction unit 906 .

[0138] The first acquisition unit 901 is used to acquire the image information in the target area by a camera under the setting of the first image acquisition parameter to obtain a first acquired image;

[0139] An identification and determination unit 902, configured to identify the content contained in the first collected image, and determine a first payment mode according to the identification result;

[0140] The second acquisition unit 903 is used to adopt the determined second image acquisition parameter setting corresponding to the first payment mode, and acquire the image information of the target area by the camera under the second image acquisition parameter setting to obtain a second acquired image;

[0141] The payment unit 904 is configured to execute the payment processing flow corresponding to the determined first payment mode according to the collected second collected image.

[0142] Optionally, the identification and determination unit 902 is specifically configured to: identify that the first captured image contains first specific content, and then determine a first payment mode.

[0143] Optionally, the identification and determination unit 902 is specifically used to: identify that the first acquired image contains second specific content, and the proportion of the display area of ​​the second specific content in the first acquired image to the first acquired image is greater than or equal to a first preset proportion threshold, and then determine the first payment mode.

[0144] Optionally, the device further comprises:

[0145] The determination unit 905 is used to identify that the first collected image contains a third specific content, and by comparing the changes of the third specific content in a plurality of consecutive collected images including the first collected image, determine that the change of the third specific content meets a preset change condition, and then determine the first payment mode. The third specific content includes a mobile phone, a QR code or a face. The preset change condition includes any one or more of the following conditions:

[0146] The increase ratio of the display area of ​​the third specific content in the plurality of consecutive collected images reaches a second preset ratio threshold;

[0147] The third specific content is changed from being partially displayed in the plurality of continuous collected images to being fully displayed;

[0148] The third specific content is flipped in the multiple consecutive captured images.

[0149] Optionally, the determining unit 905 is specifically configured to:

[0150] By comparing the changes in the position of the mobile phone in a plurality of consecutive captured images including the first captured image, it is determined that the mobile phone is taken out by the user and moved toward the camera, and the first payment mode is determined to be scan code payment;

[0151] or

[0152] By comparing the changes in the position of the mobile phone in a plurality of consecutive captured images including the first captured image, it is determined that the mobile phone is operated by the user and displays the screen to the camera, and then the first payment mode is determined to be scan code payment.

[0153] Optionally, the second acquisition unit 903 is specifically used to initialize the camera according to the second image acquisition parameter setting, where the second image acquisition parameter setting includes exposure rate, resolution and backlight compensation corresponding to the first payment mode.

[0154] Optionally, the device further comprises:

[0155] The human-computer interaction unit 906 is used to display the first payment mode to the user through the human-computer interaction interface, and receive an instruction from the user to confirm the use of the first payment mode.

[0156] See also Fig.10 , the present application embodiment provides a structural diagram of another fast scanning payment device. The device can be Figure 2-Figure 4 A portion of the payment terminal in the embodiment shown, such as Fig.10 As shown, the device 1000 includes a processor 1001 and a memory 1002. The processor 1001 and the memory 1002 are connected via a bus 1003.

[0157] The processor 1001 is configured to support the fast scanning payment device to execute Figure 2-Figure 4 The corresponding functions of the payment terminal in the fast scanning payment method. The processor 1001 can be a central processing unit (CPU), a network processor (NP), a hardware chip or any combination thereof. The above-mentioned hardware chip can be an application-specific integrated circuit (ASIC), a programmable logic device (PLD) or a combination thereof. The above-mentioned PLD can be a complex programmable logic device (CPLD), a field programmable gate array (FPGA), a generic array logic (GAL) or any combination thereof.

[0158] The memory 1002 memory is used to store program codes, etc. The memory 1002 may include a volatile memory (VM), such as a random access memory (RAM); the memory 1002 may also include a non-volatile memory (NVM), such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD); the memory 1002 may also include a combination of the above-mentioned types of memory. In an embodiment of the present invention, the memory 1002 is used to store a first acquired image, a second acquired image, etc.

[0159] The processor 1001 may call the program code to perform the following operations:

[0160] The camera acquires image information within the target area under the first image acquisition parameter setting to obtain a first acquired image;

[0161] Recognize the content contained in the first captured image, and determine the first payment mode according to the recognition result;

[0162] The determined second image acquisition parameter setting corresponding to the first payment mode is adopted, and image information of the target area is acquired by the camera under the second image acquisition parameter setting to obtain a second acquired image;

[0163] The payment processing flow corresponding to the determined first payment mode is executed according to the collected second collected image.

[0164] The embodiment of the present invention further provides a computer storage medium, wherein the computer storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes the method as described in the above embodiment, and the computer may be a part of the above-mentioned fast scanning payment device, such as the above-mentioned processor 1001.

[0165] The terms "first", "second", "third" and "fourth" etc. in the specification and claims of the present application and the drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units inherent to these processes, methods, products or devices.

[0166] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0167] The method and related apparatus provided by the embodiment of the present application are described with reference to the method flow chart and / or structural diagram provided by the embodiment of the present application. Specifically, each process and / or box in the method flow chart and / or structural diagram, as well as the combination of the processes and / or boxes in the flow chart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the process in the process. Figure 1 A process or multiple processes and / or structures Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or structures Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process in the process. Figure 1 A flow or multiple flows and / or structures illustrate the steps of the functions specified in one block or multiple blocks.

[0168] The above disclosure is only the preferred embodiment of the present invention, which certainly cannot be used to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. A fast scanning payment method, characterized in that: include: The payment terminal collects image information in the target area through a camera under the first image acquisition parameter setting to obtain a first collected image; The first image acquisition parameter is a corresponding setting of the payment terminal in a default payment mode; The payment terminal identifies the content contained in the first collected image, and determines a first payment mode according to the identification result; the first payment mode is the same as or different from the default payment mode; The payment terminal adopts the determined second image acquisition parameter setting corresponding to the first payment mode, and acquires image information of the target area by the camera under the second image acquisition parameter setting to obtain a second acquired image; executing the payment processing flow corresponding to the determined first payment mode according to the collected second collected image; The payment terminal adopts the determined second image acquisition parameter setting corresponding to the first payment mode, including: if the first payment mode is the same as the default payment mode, the payment terminal directly acquires image information in the target area through the camera to obtain a second acquired image; if the first payment mode is different from the default payment mode, the payment terminal initializes the camera according to the second image acquisition parameter setting; The payment terminal identifies the content contained in the first collected image, and determines a first payment mode according to the recognition result, including: if the payment terminal identifies that the first collected image includes both a mobile phone and a face, the first payment mode is determined according to the orientation of the front of the mobile phone, whether the mobile phone is in a bright screen state, and the proportion of the display areas of the mobile phone and the face in the entire first collected image; if the payment terminal identifies that the first collected image includes a mobile phone, a QR code or a face, the first payment mode is determined according to whether the increase ratio of the display area of ​​the mobile phone, the QR code or the face in multiple consecutive collected images including the first collected image reaches a second preset ratio threshold, or according to whether the mobile phone, the QR code or the face changes from partial display to full display in multiple consecutive collected images including the first collected image, or according to whether the mobile phone, the QR code or the face undergoes a flip change in multiple consecutive collected images including the first collected image.

2. The method according to claim 1, characterized in that The payment terminal identifies the content contained in the first collected image, and determines the first payment mode according to the identification result, including: The payment terminal identifies that the first captured image contains first specific content, and determines a first payment mode.

3. The method according to claim 1, characterized in that By comparing the changes in the position of the mobile phone in a plurality of consecutive captured images including the first captured image, it is determined that the mobile phone is taken out by the user and moved toward the camera, and the first payment mode is determined to be scan code payment; or By comparing the changes in the position of the mobile phone in a plurality of consecutive captured images including the first captured image, it is determined that the mobile phone is operated by the user and displays the screen to the camera, and then the first payment mode is determined to be scan code payment.

4. The method according to claim 1, characterized in that: The second image acquisition parameter setting includes exposure rate, resolution and backlight compensation corresponding to the first payment mode.

5. The method according to claim 1, characterized in that After the payment terminal adopts the determined second image acquisition parameter setting corresponding to the first payment mode, the following further comprises: The first payment mode is displayed to the user through a human-computer interaction interface, and an instruction from the user to confirm the use of the first payment mode is received.

6. A fast scanning payment device, characterized in that: include: A first acquisition unit, configured to acquire image information within a target area through a camera under a first image acquisition parameter setting to obtain a first acquired image; The first image acquisition parameter is set correspondingly in the default payment mode; an identification and determination unit, configured to identify the content contained in the first collected image, and determine a first payment mode according to the identification result; the first payment mode is the same as or different from the default payment mode; a second acquisition unit, configured to adopt the determined second image acquisition parameter setting corresponding to the first payment mode, and acquire image information of the target area by the camera under the second image acquisition parameter setting to obtain a second acquired image; The adopting of the determined second image acquisition parameter setting corresponding to the first payment mode includes: if the first payment mode is the same as the default payment mode, directly acquiring image information in the target area through the camera to obtain a second acquired image; if the first payment mode is different from the default payment mode, initializing the camera according to the second image acquisition parameter setting; a payment unit, configured to execute a payment processing flow corresponding to the determined first payment mode according to the collected second collected image; The identification and determination unit is specifically used to determine the first payment mode according to the orientation of the front of the mobile phone, whether the mobile phone is in a bright screen state, and the proportion of the display areas of the mobile phone and the face in the entire first collected image if it is identified that the first collected image includes both a mobile phone and a face; if it is identified that the first collected image includes a mobile phone, a QR code or a face, the first payment mode is determined according to whether the increase ratio of the display area of ​​the mobile phone, the QR code or the face in multiple consecutive collected images including the first collected image reaches a second preset ratio threshold, or according to whether the mobile phone, the QR code or the face changes from partial display to full display in multiple consecutive collected images including the first collected image, or according to whether the mobile phone, the QR code or the face undergoes a flip change in multiple consecutive collected images including the first collected image.

7. A fast scanning payment device, comprising a processor and a memory, wherein the processor and the memory are connected to each other, wherein: The memory is used to store program codes, and the processor is used to call the program codes to execute the method according to any one of claims 1 to 5.

8. A computer storage medium, characterized in that: The computer storage medium stores a computer program, wherein the computer program includes program instructions; when the program instructions are executed by a processor, the processor executes the method according to any one of claims 1 to 5.

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