WO2020233582A1 - 食物的结算方法、装置和计算机可读存储介质 - Google Patents

食物的结算方法、装置和计算机可读存储介质 Download PDF

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Publication number
WO2020233582A1
WO2020233582A1 PCT/CN2020/091182 CN2020091182W WO2020233582A1 WO 2020233582 A1 WO2020233582 A1 WO 2020233582A1 CN 2020091182 W CN2020091182 W CN 2020091182W WO 2020233582 A1 WO2020233582 A1 WO 2020233582A1
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Prior art keywords
food
image
stored image
image corresponding
settlement
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PCT/CN2020/091182
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English (en)
French (fr)
Inventor
朱雁锋
霍紫健
刘威云
吴志勇
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深圳市恒天伟焱科技有限公司
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Publication of WO2020233582A1 publication Critical patent/WO2020233582A1/zh

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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
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0283—Price estimation or determination
    • 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
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes

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  • This application relates to the technical field of food settlement, and in particular to a food settlement method, device and computer-readable storage medium.
  • the cashier needs to scan the graphic code on the food to know the price of the food, or the cashier recognizes the food to calculate the price, and the labor cost of food settlement is higher.
  • the main purpose of this application is to provide a food settlement method, device, and computer-readable storage medium, aiming to solve the problem of high labor costs in food settlement.
  • the present application provides a food settlement method.
  • the food settlement method includes the following steps:
  • the price of the food is determined according to the target pre-stored image, and the price is output.
  • the step of determining a target pre-stored image corresponding to the food according to the image includes:
  • the pre-stored image corresponding to the largest first degree of similarity is used as the target pre-stored image corresponding to the food, wherein the largest first degree of similarity is greater than a preset threshold.
  • the food settlement method should be set as a food settlement device, and the food settlement device is provided with multiple image acquisition devices, and the angle of the food collected by each image acquisition device is different.
  • the step of determining the target pre-stored image corresponding to the food according to the image includes:
  • the pre-stored image corresponding to the largest degree of similarity is used as the target pre-stored image corresponding to the food, wherein the largest second degree of similarity is greater than a preset threshold.
  • the step of determining the price of the food according to the target pre-stored image includes:
  • the price of the food is determined according to the type of the food.
  • the step of determining a target pre-stored image corresponding to the food according to the image includes:
  • the matched prestored image is used as the target prestored image corresponding to the food.
  • the method further includes:
  • the image does not contain a matching pre-stored image, acquiring a target object from the image, where the target object includes a food dish or food packaging;
  • the price of the food is determined according to the target object, and the step of outputting the price is executed.
  • step of outputting the price it further includes:
  • the user’s food settlement method is determined according to the user information, wherein the food settlement method includes QR code payment, bank card payment, meal card payment, facial recognition payment, eye recognition payment, fingerprint recognition payment, and WeChat payment And at least one of Alipay payment;
  • the method further includes:
  • the food is settled according to the target food settlement method and the price.
  • the present application also provides a food settlement device.
  • the food settlement device includes a processor, a memory, and a food settlement program stored in the memory and running on the processor. When the program is executed by the processor, each step of the food settlement method described above is realized.
  • the present application also provides a computer-readable storage medium, the computer-readable storage medium stores a food settlement program, and when the food settlement program is executed by a processor, each of the food settlement methods described above is implemented. step.
  • the food settlement method, device, and computer readable storage medium provided in the present application.
  • the food settlement device collects the food to be purchased to obtain the image corresponding to the food, and then determines the target pre-stored image corresponding to the food according to the image.
  • the pre-stored image determines the price of the food, and finally outputs the price, so that the user pays for the food according to the output price; because the food settlement device can determine the price of the food directly through the image of the food, saving the labor cost of food settlement.
  • FIG. 1 is a schematic diagram of the hardware structure of a food settlement device according to an embodiment of the application
  • FIG. 3 is a schematic flowchart of a second embodiment of the food settlement method according to the application.
  • FIG. 4 is a schematic flowchart of a third embodiment of the food settlement method according to the application.
  • FIG. 5 is a schematic flowchart of a fourth embodiment of the food settlement method according to the application.
  • FIG. 6 is a schematic flowchart of a fifth embodiment of the food settlement method according to the application.
  • the main solution of the embodiment of the present application is: collecting food to be purchased to obtain an image corresponding to the food; determining the target pre-stored image corresponding to the food according to the image; determining the food according to the target pre-stored image Price and output said price.
  • the food settlement device can directly determine the price of the food through the image of the food, the labor cost of food settlement is saved.
  • the food settlement device can be as shown in FIG. 1.
  • the food settlement device includes a processor 101, such as a CPU, a memory 102, and a communication bus 103.
  • the communication bus 103 is configured to realize connection and communication between these components.
  • the memory 102 may be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a magnetic disk memory. As shown in FIG. 1, the memory 102 as a computer storage medium may include a food settlement program; and the processor 101 may be configured to call the food settlement delivery program stored in the memory 102 and perform the following operations:
  • the price of the food is determined according to the target pre-stored image, and the price is output.
  • the step of determining a target pre-stored image corresponding to the food according to the image includes:
  • the pre-stored image corresponding to the largest first degree of similarity is used as the target pre-stored image corresponding to the food, where the largest first degree of similarity is greater than a preset threshold.
  • the processor 101 may be configured to call a food settlement program stored in the memory 102 and perform the following operations:
  • the pre-stored image corresponding to the largest degree of similarity is used as the target pre-stored image corresponding to the food, wherein the largest second degree of similarity is greater than a preset threshold.
  • the processor 101 may be configured to call a food settlement program stored in the memory 102 and perform the following operations:
  • the price of the food is determined according to the type of the food.
  • the processor 101 may be configured to call a food settlement program stored in the memory 102 and perform the following operations:
  • the matched prestored image is used as the target prestored image corresponding to the food.
  • the processor 101 may be configured to call a food settlement program stored in the memory 102 and perform the following operations:
  • the image does not contain a matching pre-stored image, acquiring a target object from the image, where the target object includes a food dish or food packaging;
  • the price of the food is determined according to the target object, and the step of outputting the price is executed.
  • the processor 101 may be configured to call a food settlement program stored in the memory 102 and perform the following operations:
  • the user’s food settlement method is determined according to the user information, wherein the food settlement method includes QR code payment, bank card payment, meal card payment, facial recognition payment, eye recognition payment, fingerprint recognition payment, and WeChat payment And at least one of Alipay payment;
  • the processor 101 may be configured to call a food settlement program stored in the memory 102 and perform the following operations:
  • the food is settled according to the target food settlement method and the price.
  • the food settlement device collects the food to be purchased to obtain the image corresponding to the food, and then determines the target pre-stored image corresponding to the food according to the image, thereby determining the price of the food according to the target pre-stored image, and finally outputs the price , Allowing the user to pay for the food according to the output price; because the food settlement device can directly determine the price of the food through the image of the food, saving the labor cost of food settlement.
  • Fig. 2 is a first embodiment of the food settlement method of the application.
  • the food settlement method includes the following steps:
  • Step S10 collecting food to be purchased to obtain an image corresponding to the food
  • the execution subject is a food settlement device.
  • the food settlement device is equipped with an image acquisition module.
  • the image acquisition module can be a camera or a camera. After the user selects food, the food can be placed in the food settlement device On the tray, the food settlement device collects the food through the image acquisition module to obtain the image corresponding to the food.
  • the food can be a meal in a restaurant or packaged food.
  • Step S20 determining a target pre-stored image corresponding to the food according to the image
  • Various food images are stored in the food settlement device, and the stored food images are pre-stored images.
  • the food settlement device After the food settlement device obtains the image corresponding to the food, it can determine the pre-stored image that matches the collected food image among the stored pre-stored images, and the pre-stored image that matches the image corresponding to the food is the target pre-stored corresponding to the food image.
  • the food settlement device can determine the pre-stored image that matches the image corresponding to the food in various ways.
  • a corresponding food dish is used for each dish.
  • the food dish can be a ceramic bowl, a stainless steel bowl, or other utensils that can be loaded with food. Different dishes can be set. Set patterns and different shapes. Of course, you can also number the food dishes. A numbered food dish contains the corresponding dishes or rice.
  • Place the image collection module of the food settlement device the food settlement device prompts the user to place food.
  • the food settlement device collects the image of the food, it can obtain the pattern, shape or number of the food dish in the collected image. Thereby quickly find the pre-stored image in the pre-stored image (the pre-stored image contains the same pattern, shape or number of food dishes).
  • the food settlement device can directly collect the food package, that is, the food corresponding to the image contains the food package.
  • the food settlement device is binarized Process the image to identify the text on the package to obtain the name of the food, and then directly find the pre-stored image that matches the image based on the food name (the food name in the pre-stored image is the same as the recognized food name); further, the same There are many types of foods with names. If the search is based only on the name of the food, the image contains multiple corresponding pre-stored images.
  • the food identification device can determine the characteristics of the food type according to the name of the food, such as the same name.
  • the food settlement device determines the pre-stored image matching the image according to the food name and packaging color in the image.
  • different types of food with the same name can also have different packaging patterns
  • the food settlement device determines the pre-stored image that matches the image according to the food name and packaging pattern in the image.
  • Step S30 Determine the price of the food according to the target pre-stored image, and output the price.
  • the food settlement device When the food settlement device stores the food image, it sets the price of the food in the food image, binds the price to the food image, and saves it. Therefore, the food settlement device determines the target pre-stored image corresponding to the food and can obtain it The price corresponding to the target pre-stored image is the price corresponding to the food, and the food settlement device outputs the price for the user to settle.
  • the food settlement device can output multiple payment methods, such as QR code payment, bank card payment, meal card payment, facial recognition payment, eye recognition payment, fingerprint recognition payment, NFC payment (near field communication payment), WeChat payment , Alipay payment, etc., users can choose the payment method to pay for the price to complete the food settlement.
  • payment methods such as meal card payment, facial recognition payment, eye recognition payment, fingerprint recognition payment and other payment methods require users to register as members. When a user registers as a member, the food settlement device will save the user's image, meal card number, phone number, fingerprints and food balance.
  • the food settlement device can obtain the user information of the user when outputting the price of the food.
  • the food settlement device can determine the user through the image acquisition module, and then obtain the user information of the user, thereby determining the food settlement method the user can choose according to the user information .
  • Food settlement methods include the above-mentioned QR code payment, bank card payment, meal card payment, face recognition payment, eye recognition payment, fingerprint recognition payment, NFC payment (near field communication payment), WeChat payment, Alipay payment, food
  • the settlement device then outputs the user’s food settlement method. For example, if the user has activated fingerprint payment, meal card payment, and facial recognition payment, the food settlement device can output fingerprint payment, meal card payment, and facial recognition payment.
  • Payment method for the user to choose after the user performs the selection operation, that is, the food settlement device detects the operation based on the selection of the food settlement method, the target food settlement method can be determined according to the operation, and the target food settlement method can be determined according to the target food The settlement method and the price of the food are used to settle the food.
  • the food settlement device collects the user’s face to identify the user, and then deduct the purchase from the balance in the user account
  • the price of food if the target food settlement method is WeChat payment, the food settlement device will send the food price to the WeChat payment server, so that the WeChat payment server will send the payment request to the user terminal, so that the user can pay for the food based on the user terminal , Thereby completing the food payment.
  • the food settlement device collects the food to be purchased to obtain an image corresponding to the food, and then determines the target pre-stored image corresponding to the food based on the image, thereby determining the price of the food according to the target pre-stored image. Finally, the price is output, so that the user pays for the food according to the output price; because the food settlement device can directly determine the price of the food through the image of the food, which saves the labor cost of food settlement.
  • Fig. 3 is a second embodiment of the food settlement method of this application. Based on the first embodiment, the step S20 includes:
  • Step S21 calculating the first similarity between the image and each pre-stored image
  • Step S22 Use the pre-stored image corresponding to the largest first degree of similarity as the target pre-stored image corresponding to the food, wherein the largest first degree of similarity is greater than a preset threshold.
  • the food settlement device is provided with a similarity calculation program.
  • the food settlement device calculates the first similarity between the collected image and each pre-stored image through the similarity calculation program, and the food settlement device determines the largest For the first similarity, if the maximum similarity is greater than the preset threshold, the pre-stored image corresponding to the maximum similarity is used as the target pre-stored image corresponding to the food.
  • the preset threshold may be any suitable value, for example, 95%.
  • the user needs to align a certain side of the food packaging or the pattern, shape, and number that characterizes the type of the food dish to the image acquisition module.
  • the target pre-stored image corresponding to the food can be determined by the calculation method of similarity, so that the food settlement device can accurately identify the food.
  • the food settlement device determines the target pre-stored image corresponding to the food by calculating the similarity between the image corresponding to the food and each pre-stored image, so that the food settlement device determines the target pre-stored image corresponding to the food Food prices save labor costs for food settlement.
  • Fig. 4 is a third embodiment of the food calculation method of this application. Based on the first embodiment, the step S20 includes:
  • Step S23 constructing a three-dimensional image corresponding to the food according to the images collected by each of the image collection devices and the collection angle of each of the image collection devices;
  • Step S24 calculating a second degree of similarity between the three-dimensional image and each pre-stored image, wherein the dimension of each pre-stored image is the same as the dimension of the three-dimensional image;
  • Step S25 Use the pre-stored image corresponding to the largest second degree of similarity as the target pre-stored image corresponding to the food, wherein the largest second degree of similarity is greater than a preset threshold.
  • the food settlement device may be provided with multiple image acquisition modules, for example, three image acquisition modules may be provided, and each image acquisition module has a different food acquisition angle.
  • each image acquisition module simultaneously collects images of the food, and the food does not move during the collection process.
  • Each image acquisition module has a corresponding image acquisition angle.
  • the food settlement device spatially splices each image according to the image acquisition angle to construct a three-dimensional image corresponding to the food, that is, a three-dimensional image of the food.
  • the food settlement device calculates the three-dimensional image The second degree of similarity with the pre-stored image (the pre-stored image is also a three-dimensional image, that is, the dimension of the pre-stored image is the same as the dimension of the image corresponding to the food), and then determine whether the largest second similarity is greater than the preset threshold, if it is greater than If the threshold is preset, the pre-stored image corresponding to the largest second similarity is used as the target pre-stored image corresponding to the food.
  • the pre-stored image is also a three-dimensional image, that is, the dimension of the pre-stored image is the same as the dimension of the image corresponding to the food
  • the food settlement device constructs a three-dimensional image corresponding to the food through images collected by different image acquisition modules from different angles, and determines the food by calculating the similarity between the three-dimensional image and each pre-stored image
  • the corresponding target pre-stored image enables the food settlement device to determine the food price through the target pre-stored image, saving labor costs for food settlement.
  • Fig. 5 is a fourth embodiment of the food settlement method of this application. Based on any one of the first to third embodiments, the step S30 includes:
  • Step S31 determining the type of the food according to the target pre-stored image
  • Step S32 When the type of the food is a preset type, the price of the food is determined according to the type of the food.
  • the price of some foods is linked to the weight of the food, while the price of some foods is not related to the weight of the food.
  • the price of food such as melon seeds and peanuts is calculated according to weight and unit price, while the price of packaged food is fixed , Has nothing to do with its weight.
  • the food settlement device sets the type of food that is not associated with the weight of the food as a preset type.
  • the food settlement device stores various pre-stored images, and the food in each pre-stored image has a corresponding type.
  • the pre-stored image will be associated with the type of food in the pre-stored image. Therefore, the food settlement device After the target pre-stored image is determined, the type of food can be determined according to the target pre-stored image. If the type of food is a preset type, the food settlement device directly determines the price of the food according to the type of food.
  • the food settlement device determines the type of food according to the target pre-stored image. If the food type is a preset type, the price of the food is directly determined according to the type of food, which saves the labor cost of food settlement.
  • Fig. 6 is a fifth embodiment of the food settlement method of this application. Based on any one of the first to fourth embodiments, the step 20 further includes:
  • Step S26 judging whether the image contains a matching pre-stored image
  • Step S27 when the image contains a matched prestored image, use the matched prestored image as the target prestored image corresponding to the food;
  • Step S28 when the image does not contain a matching pre-stored image, acquire a target object from the image, where the target object includes a food dish or a food package;
  • Step S29 Determine the price of the food according to the target object.
  • the food settlement device can calculate the similarity between the captured image and each pre-stored image, and then determine the maximum similarity. If the maximum similarity is greater than the preset threshold, then the captured image contains a matching pre-stored image , At this time, use the pre-stored image as the target pre-stored image corresponding to the food.
  • the food settlement device can directly recognize the collected images to determine the type of food.
  • the food settlement device can obtain the target object from the image, and the target object is the food containing the food.
  • both the food container and the packaging can characterize the type of food. Therefore, the food settlement device can directly determine the type of food according to the acquired target object, and determine the type of food according to the type of food. price.
  • the food settlement device judges whether the image contains matching pre-stored images, so that different strategies are adopted to determine the type of food for different judgment results, so as to avoid the problem that the food settlement device cannot identify the food type , Thereby saving the time for users to settle food and improving user experience, and the food settlement device is highly intelligent.
  • the present application also provides a food settlement device.
  • the food settlement device includes a processor, a memory, and a food settlement program stored in the memory and running on the processor, the food settlement program being executed by the processor Time to implement each step of the food settlement method as described in the above embodiment.
  • the present application also provides a computer-readable storage medium that stores a food settlement program, and when the food settlement program is executed by a processor, each step of the food settlement method described in the above embodiment is implemented.
  • the method of the above embodiments can be implemented by means of software plus the necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is better. ⁇
  • the technical solution of this application essentially or the part that contributes to the exemplary technology can be embodied in the form of a software product, and the computer software product is stored in a storage medium (such as ROM/RAM) as described above. , Magnetic disk, optical disk), including several instructions to make a terminal device (can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) execute the method described in each embodiment of the present application.

Abstract

本申请公开了一种食物的结算方法，所述食物的结算方法包括以下步骤：对待购买的食物进行采集，以得到所述食物对应的图像；根据所述图像确定所述食物对应的目标预存图像；根据所述目标预存图像确定所述食物的价格，并输出所述价格。本申请还公开了一种食物的结算装置和计算机可读存储介质。

Description

食物的结算方法、装置和计算机可读存储介质
相关申请
本申请要求2019年05月21日申请的，申请号为201910427749.7，名称为“食物的结算方法、装置和计算机可读存储介质”的中国专利申请的优先权，在此将其全文引入作为参考。
技术领域
本申请涉及食物结算技术领域，尤其涉及一种食物的结算方法、装置和计算机可读存储介质。
背景技术
随着人们生活节奏的加快，人们动手做饭的时间越来越少，基本都是在外购买食物解决三餐问题。
人们在购买食物后，需要收银员扫描食物上图形码得知食物价格，或者，由收银人识别食物计算价格，食物结算的人工成本较高。
发明概述
技术问题
问题的解决方案
技术解决方案
本申请的主要目的在于提供一种食物的结算方法、装置和计算机可读存储介质，旨在解决食物结算的人工成本较高的问题。
为实现上述目的，本申请提供的一种食物的结算方法，所述食物的结算方法包括以下步骤：
对待购买的食物进行采集，以得到所述食物对应的图像；
根据所述图像确定所述食物对应的目标预存图像；
根据所述目标预存图像确定所述食物的价格，并输出所述价格。
在一实施例中，所述根据所述图像确定所述食物对应的目标预存图像的步骤包括：
计算所述图像与各个预存图像之间的第一相似度；
将最大的所述第一相似度对应的预存图像作为所述食物对应的目标预存图像，其中，最大的所述第一相似度大于预设阈值。
在一实施例中，所述食物的结算方法应设置为食物的结算装置，所述食物的结算装置设有多个图像采集装置，各个所述图像采集装置采集的食物的角度各不相同，所述根据所述图像确定所述食物对应的目标预存图像的步骤包括：
根据各个所述图像采集装置采集的图像以及各个所述图像采集装置的采集角度，构建所述食物对应的三维图像；
计算所述三维图像与各个预存图像之间的第二相似度，其中，各个预存图像的维度与三维图像的维度相同；
将最大的所述相似度对应的预存图像作为所述食物对应的目标预存图像，其中，最大的所述第二相似度大于预设阈值。
在一实施例中，所述根据所述目标预存图像确定所述食物的价格的步骤包括：
根据所述目标预存图像确定所述食物的类型；
在所述食物的类型为预设类型时，根据所述食物的类型确定所述食物的价格。
在一实施例中，所述根据所述图像确定所述食物对应的目标预存图像的步骤包括：
判断所述图像是否含有匹配的预存图像；
在所述图像含有匹配的预存图像时，将匹配的所述预存图像作为所述食物对应的目标预存图像。
在一实施例中，所述判断所述图像是否含有匹配的预存图像的步骤之后，还包括：
在所述图像不含有匹配的预存图像时，从所述图像中获取目标对象，其中，所述目标对象包括盛放食物的食皿或者食物的包装；
根据所述目标对象确定所述食物的价格，并执行所述输出所述价格的步骤。
在一实施例中，所述输出所述价格的步骤之后，还包括：
获取所述用户对应的用户信息；
根据所述用户信息确定所述用户的食物结算方式，其中，所述食物结算方式包 括二维码支付、银行卡支付、餐卡支付、脸部识别支付、眼睛识别支付、指纹识别支付、微信支付以及支付宝支付中的至少一种；
输出所述食物结算方式。
在一实施例中，所述输出所述食物结算方式的步骤之后，还包括：
在检测到基于所述食物结算方式的选择完成的操作时，根据所述操作确定目标食物结算方式；
根据所述目标食物结算方式以及所述价格对所述食物进行结算。
为实现上述目的，本申请还提供一种食物的结算装置，所述食物的结算装置包括处理器、存储器以及存储在所述存储器并可在所述处理器运行的食物结算程序，所述食物结算程序被处理器执行时实现如上所述的食物的结算方法的各个步骤。
为实现上述目的，本申请还提供一种计算机可读存储介质，所述计算机可读存储介质存储有食物结算程序，所述食物结算程序被处理器执行时实现如上所述的食物结算方法的各个步骤。
本申请提供的食物的结算方法、装置和计算机可读存储介质，食物的结算装置对待购买的食物进行采集，以得到食物对应的图像，再根据图像来确定食物对应的目标预存图像，从而根据目标预存图像确定食物的价格，最后输出价格，使得用户根据输出的价格对食物进行支付；因食物的结算装置直接通过食物的图像即可确定食物的价格，节省了食物结算的人工成本。
发明的有益效果
对附图的简要说明
附图说明
为了更清楚地说明本申请实施例或示例性技术中的技术方案，下面将对实施例或示例性技术描述中所需要使用的附图作简单地介绍。
图1为本申请实施例涉及的食物的结算装置的硬件结构示意图；
图2为本申请食物结算方法的第一实施例的流程示意图；
图3为本申请食物结算方法的第二实施例的流程示意图；
图4为本申请食物结算方法的第三实施例的流程示意图；
图5为本申请食物结算方法的第四实施例的流程示意图；
图6为本申请食物结算方法的第五实施例的流程示意图。
本申请目的的实现、功能特点及优点将结合实施例，参照附图做进一步说明。
发明实施例
本发明的实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本申请的一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
本申请实施例的主要解决方案是：对待购买的食物进行采集，以得到所述食物对应的图像；根据所述图像确定所述食物对应的目标预存图像；根据所述目标预存图像确定所述食物的价格，并输出所述价格。
由于食物的结算装置直接通过食物的图像即可确定食物的价格，节省了食物结算的人工成本。
作为一种实现方案，食物的结算装置可以如图1所示。
进一步的，参照图1，食物的结算装置包括：处理器101，例如CPU，存储器102，通信总线103。其中，通信总线103设置为实现这些组件之间的连接通信。
存储器102可以是高速RAM存储器，也可以是稳定的存储器(non-volatilememory)，例如磁盘存储器。如图1所示，作为一种计算机存储介质的存储器102中可以包括食物结算程序；而处理器101可以设置为调用存储器102中存储的食物结算送程序，并执行以下操作：
对待购买的食物进行采集，以得到所述食物对应的图像；
根据所述图像确定所述食物对应的目标预存图像；
根据所述目标预存图像确定所述食物的价格，并输出所述价格。
在一实施例中，所述根据所述图像确定所述食物对应的目标预存图像的步骤包括：
计算所述图像与各个预存图像之间的第一相似度；
将最大的所述第一相似度对应的预存图像作为所述食物对应的目标预存图像， 其中，最大的所述第一相似度大于预设阈值。
在一实施例中，处理器101可以设置为调用存储器102中存储的食物结算程序，并执行以下操作：
根据各个所述图像采集装置采集的图像以及各个所述图像采集装置的采集角度，构建所述食物对应的三维图像；
计算所述三维图像与各个预存图像之间的第二相似度，其中，各个预存图像的维度与三维图像的维度相同；
将最大的所述相似度对应的预存图像作为所述食物对应的目标预存图像，其中，最大的所述第二相似度大于预设阈值。
在一实施例中，处理器101可以设置为调用存储器102中存储的食物结算程序，并执行以下操作：
根据所述目标预存图像确定所述食物的类型；
在所述食物的类型为预设类型时，根据所述食物的类型确定所述食物的价格。
在一实施例中，处理器101可以设置为调用存储器102中存储的食物结算程序，并执行以下操作：
判断所述图像是否含有匹配的预存图像；
在所述图像含有匹配的预存图像时，将匹配的所述预存图像作为所述食物对应的目标预存图像。
在一实施例中，处理器101可以设置为调用存储器102中存储的食物结算程序，并执行以下操作：
在所述图像不含有匹配的预存图像时，从所述图像中获取目标对象，其中，所述目标对象包括盛放食物的食皿或者食物的包装；
根据所述目标对象确定所述食物的价格，并执行所述输出所述价格的步骤。
在一实施例中，处理器101可以设置为调用存储器102中存储的食物结算程序，并执行以下操作：
获取所述用户对应的用户信息；
根据所述用户信息确定所述用户的食物结算方式，其中，所述食物结算方式包括二维码支付、银行卡支付、餐卡支付、脸部识别支付、眼睛识别支付、指纹 识别支付、微信支付以及支付宝支付中的至少一种；
输出所述食物结算方式。
在一实施例中，处理器101可以设置为调用存储器102中存储的食物结算程序，并执行以下操作：
在检测到基于所述食物结算方式的选择完成的操作时，根据所述操作确定目标食物结算方式；
根据所述目标食物结算方式以及所述价格对所述食物进行结算。
本实施例根据上述方案，食物的结算装置对待购买的食物进行采集，以得到食物对应的图像，再根据图像来确定食物对应的目标预存图像，从而根据目标预存图像确定食物的价格，最后输出价格，使得用户根据输出的价格对食物进行支付；因食物的结算装置直接通过食物的图像即可确定食物的价格，节省了食物结算的人工成本。
基于上述食物的结算装置的硬件构架，提出本申请食物结算方法的实施例。
参照图2，图2为本申请食物结算方法的第一实施例，所述食物结算方法包括以下步骤：
步骤S10，对待购买的食物进行采集，以得到所述食物对应的图像；
在本申请中执行主体为食物的结算装置，食物的结算装置设有图像采集模块，图像采集模块可以是摄像头，也可以是相机，用户在选定食物后，可将食物放置在食物的结算装置的托盘上，使得食物的结算装置通过图像采集模块对食物进行采集，以得到食物对应的图像。食物可以是餐厅内的饭菜，也可以是带有包装的食物。
步骤S20，根据所述图像确定所述食物对应的目标预存图像；
食物的结算装置中存储有各种食物图像，存储的食物图像即为预存图像。在食物的结算装置获得食物对应的图像后，即可以在存储的各个预存图像中确定与采集的食物图像相匹配的预存图像，与食物对应的图像相匹配的预存图像即为食物对应的目标预存图像。食物的结算装置判断与食物对应的图像相匹配的预存图像可有多种方式。
在一实施例中，在食物为饭菜时，对每一种菜采用对应的食皿进行盛放，食皿 可以是陶瓷碗、不锈钢碗等可装载饭菜的器皿，食皿的不同可以设置不同的花纹、不同的造型进行设置，当然，还可对食皿进行编号，一种编号的食皿盛放对应的菜或者饭，在用户购买饭菜后，可将表征器皿的身份的花纹、造型或者编号相对食物的结算装置的图像采集模块放置(食物的结算装置对用户进行食物放置提示)，食物的结算装置采集该食物的图像后，可在采集的图像中获取食皿的花纹、造型或者编号，从而在预存图像中迅速找到与预存图像(预存图像中含有相同花纹、造型或者编号的食皿)。
在另一实施例中，若食物为含有包装的食物，那么食物的结算装置可以直接采集食物的包装，也即食物对应的图像中含有食物的包装，此时，食物的结算装置通过二值化处理图像，从而对包装上的文字进行识别得到食物的名称，进而可以根据食物名称直接查找到与图像相匹配的预存图像(预存图像中食物名称与识别出来的食物名称相同)；进一步地，相同名称的食物有多种种类，若是仅仅根据食物名称进行查找，那么图像含有多个对应的预存图像，对此，食物识别装置可以根据食物名称来确定区别该食物种类的特征，如，同一名称的食物的不同种类是以不同颜色进行区分，那么食物的结算装置根据图像中食物名称以及包装颜色来确定与图像相匹配的预存图像，此外，同一名称的食物的不同种类还可以是以不同包装图案进行区分，那么食物的结算装置根据图像中食物名称以及包装图案来确定与图像相匹配的预存图像。
步骤S30，根据所述目标预存图像确定所述食物的价格，并输出所述价格。
食物的结算装置在存储食物图像时，会设定食物图像中食物的价格，并将价格与食物图像绑定并保存，因此，在食物的结算装置确定食物对应的目标预存图像后，即可获取目标预存图像对应的价格，该价格即为食物对应的价格，食物的结算装置输出价格，以供用户进行结算。
食物的结算装置可以输出多种支付方式，例如，二维码支付、银行卡支付、餐卡支付、脸部识别支付、眼睛识别支付、指纹识别支付、NFC支付(近场通信支付)、微信支付、支付宝支付等，用户可以选择支付方式进行价格的支付以完成食物的结算，需要说明的是，餐卡支付、脸部识别支付、眼睛识别支付、指纹识别支付等支付方式需要用户进行会员注册，用户在注册会员时，食物的结 算装置会将用户的图像、餐卡编号、电话号码、录入的指纹以及食物余额进行保存。
食物的结算装置在输出食物的价格时，可获取用户的用户信息，食物的结算装置可以通过图像采集模块来确定用户，进而获取用户的用户信息，从而根据用户信息确定用户可以选择的食物结算方式，食物结算方式包括上述中的二维码支付、银行卡支付、餐卡支付、脸部识别支付、眼睛识别支付、指纹识别支付、NFC支付(近场通信支付)、微信支付、支付宝支付，食物的结算装置再输出用户的食物结算方式，例如，用户开通了指纹支付、餐卡支付以及脸部识别支付，那么，食物的结算装置可输出指纹支付、餐卡支付、脸部识别支付等三种支付方式，以供用户进行选择；用户在进行选择操作后，也即食物的结算装置在检测到基于食物结算方式的选择完成的操作，即可根据操作来确定目标食物结算方式，从而根据目标食物结算方式以及食物的价格对食物进行结算，例如，目标食物结算方式为脸部识别结算，那么食物的结算装置采集用户的脸部，从而识别出用户，再从用户账号中的余额中扣除购买的食物的价格，若目标食物结算方式为微信支付，那么食物的结算装置会将食物价格发送至微信支付服务器，进而使得微信支付服务器将支付请求发送至用户终端，使得用户基于用户终端对食物进行支付，从而完成食物的支付。
在本实施例提供的技术方案中，食物的结算装置对待购买的食物进行采集，以得到食物对应的图像，再根据图像来确定食物对应的目标预存图像，从而根据目标预存图像确定食物的价格，最后输出价格，使得用户根据输出的价格对食物进行支付；因食物的结算装置直接通过食物的图像即可确定食物的价格，节省了食物结算的人工成本。
参照图3，图3为本申请食物的结算方法的第二实施例，基于第一实施例，所述步骤S20包括：
步骤S21，计算所述图像与各个预存图像之间的第一相似度；
步骤S22，将最大的所述第一相似度对应的预存图像作为所述食物对应的目标预存图像，其中，最大的所述第一相似度大于预设阈值。
在本实施例中，食物的结算装置设有相似度计算程序，食物的结算装置通过相 似度计算程序计算采集的图像与各个预存图像之间的第一相似度，食物的结算装置再确定最大的第一相似度，若是最大的相似度大于预设阈值时，则将最大相似度对应的预存图像作为食物对应的目标预存图像，预设阈值可为任意合适的数值，例如，95％。
进一步地，在一实施例中，用户需要将食物的包装某一面或者表征食皿的类型的花纹、造型以及编号对准图像采集模块，在当用户未将食物的包装或者食皿未对准食物采集模块时，可以通过相似度的计算方式来确定食物对应的目标预存图像，使得食物的结算装置能够准确的识别食物。
在本实施例提供的技术方案中，食物的结算装置通过计算食物对应的图像与各个预存图像之间的相似度，来确定食物对应的目标预存图像，使得食物的结算装置通过目标预存图像来确定食物价格，节省了食物结算的人工成本。
参照图4，图4为本申请食物的计算方法的第三实施例，基于第一实施例，所述步骤S20包括：
步骤S23，根据各个所述图像采集装置采集的图像以及各个所述图像采集装置的采集角度，构建所述食物对应的三维图像；
步骤S24，计算所述三维图像与各个预存图像之间的第二相似度，其中，各个预存图像的维度与三维图像的维度相同；
步骤S25，将最大的所述第二相似度对应的预存图像作为所述食物对应的目标预存图像，其中，最大的所述第二相似度大于预设阈值。
在本实施例中，食物的结算装置可设有多个图像采集模块，例如，可以设置三个图像采集模块，各个图像采集模块对食物的采集角度不同。用户在将食物放置在食物的结算装置上时，各个图像采集模块同时对食物进行图像采集，采集过程中，食物不移动。各个图像采集模块具有对应的图像采集角度，食物的结算装置根据图像采集角度对各个图像进行空间拼接，从而构建成食物对应的三维图像，也即食物的立体图，然后，食物的结算装置计算三维图像与预存图像(预存图像也是三维图像，也即预存图像的维度与食物对应的图像的维度相同)之间的第二相似度，再确定最大的第二相似度是否与大于预设阈值，若是大于预设阈值，则将最大第二相似度对应的预存图像作为食物对应的目标预存图 像。
需要说明的是，食物的结算装置设置的不同角度的图像采集模块越多，构建的食物的三维图像越接近食物的实际立体图，可以理解的是，食物的结算装置设置的不同角度的图像采集模块越多，食物的结算装置识别的食物更为准确。
在本实施例提供的技术方案中，食物的结算装置通过不同的图像采集模块不同角度采集的图像来构建食物对应的三维图像，通过计算三维图像与各个预存图像之间的相似度，来确定食物对应的目标预存图像，使得食物的结算装置通过目标预存图像来确定食物价格，节省了食物结算的人工成本。
参照图5，图5为本申请食物的结算方法的第四实施例，基于第一至第三中任一实施例，所述步骤S30包括：
步骤S31，根据所述目标预存图像确定所述食物的类型；
步骤S32，在所述食物的类型为预设类型时，根据所述食物的类型确定所述食物的价格。
一些食物的价格和食物的重量相挂钩，而一些食物的价格与食物的重量无关联，例如，瓜子、花生等食物是按照重量以及单价来计算价格，而带有包装的食物的价格是固定的，与其重量无关。对此，食物的结算装置将与食物重量无关联的食物的类型设定为预设类型。
食物的结算装置存储有各个预存图像，各个预存图像中食物有对应的类型，在食物的结算装置存储预存图像，会将预存图像与预存图像中食物的类型关联起来，故在当食物的结算装置在确定目标预存图像后，即可以根据目标预存图像来确定食物的类型，若是食物的类型为预设类型，那么食物的结算装置直接根据食物的类型确定食物的价格。
在本实施例提供的技术方案中，食物的结算装置根据目标预存图像确定食物的类型，若食物类型为预设类型，则直接根据食物的类型确定食物的价格，节省了食物结算的人工成本。
参照图6，图6为本申请食物的结算方法的第五实施例，基于第一至第四中任一实施例，所述步骤20还包括：
步骤S26，判断所述图像是否含有匹配的预存图像；
步骤S27，在所述图像含有匹配的预存图像时，将匹配的所述预存图像作为所述食物对应的目标预存图像；
步骤S28，在所述图像不含有匹配的预存图像时，从所述图像中获取目标对象，其中，所述目标对象包括盛放食物的食皿或者食物的包装；
步骤S29，根据所述目标对象确定所述食物的价格。
在本实施例中，食物的结算装置可以根据采集的图像与各个预存图像进行相似度的计算，然后确定最大的相似度，若是最大相似度大于预设阈值，那么采集的图像含有匹配的预存图像，此时，将该预存图像作为食物对应的目标预存图像。
在实际情况中，由于光线、食物相对图像采集模块的相对位置不佳等因素的影响，会使得结算装置采集的图像的不够清晰，进而会使得图像并未含有匹配的预存图像，也即最大相似度小于预设阈值；对此，食物的结算装置可直接对采集的图像进行识别，从而确定食物的类型，具体的，食物的结算装置可以从图像中获取目标对象，目标对象为盛装食物的食皿或者食物的包装，在一实施例中，食皿以及包装均可以表征食物的类型，因此，食物的结算装置可以直接根据获取的目标对象来确定食物的类型，在根据食物的类型确定食物的价格。
在本实施例提供的技术方案中，食物的结算装置判断图像是否含有匹配的预存图像，从而针对不同的判断结果采用不同策略以确定食物的类型，避免食物的结算装置出现无法识别食物类型的问题，进而节省了用户结算食物的时间，提高了用户体验，食物的结算装置的智能化程度高。
本申请还提供一种食物的结算装置，所述食物的结算装置包括处理器、存储器以及存储在所述存储器并可在所述处理器运行的食物结算程序，所述食物结算程序被处理器执行时实现如上实施例所述的食物的结算方法的各个步骤。
本申请还提供一种计算机可读存储介质，所述计算机可读存储介质存储有食物结算程序，所述食物结算程序被处理器执行时实现如上实施例所述的食物结算方法的各个步骤。
上述本申请实施例序号仅仅为了描述，不代表实施例的优劣。
需要说明的是，在本文中，术语“包括”、“包含”或者其任何其他变体意在涵盖 非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者装置不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者装置所固有的要素。在没有更多限制的情况下，由语句“包括一个......”限定的要素，并不排除在包括该要素的过程、方法、物品或者装置中还存在另外的相同要素。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到上述实施例方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件，但很多情况下前者是更佳的实施方式。基于这样的理解，本申请的技术方案本质上或者说对示例性技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在如上所述的一个存储介质(如ROM/RAM、磁碟、光盘)中，包括若干指令用以使得一台终端设备(可以是手机，计算机，服务器，空调器，或者网络设备等)执行本申请各个实施例所述的方法。
以上仅为本申请的可选实施例，并非因此限制本申请的专利范围，凡是利用本申请说明书及附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本申请的专利保护范围内。

Claims (20)

  1. 一种食物的结算方法，其中，所述食物的结算方法包括以下步骤：
    对待购买的食物进行采集，以得到所述食物对应的图像；
    根据所述图像确定所述食物对应的目标预存图像；
    根据所述目标预存图像确定所述食物的价格，并输出所述价格。
  2. 如权利要求1所述的食物的结算方法，其中，所述根据所述图像确定所述食物对应的目标预存图像的步骤包括：
    计算所述图像与各个预存图像之间的第一相似度；
    将最大的所述第一相似度对应的预存图像作为所述食物对应的目标预存图像，其中，最大的所述第一相似度大于预设阈值。
  3. 如权利要求1所述的食物的结算方法，其中，所述食物的结算方法应设置为食物的结算装置，所述食物的结算装置设有多个图像采集装置，各个所述图像采集装置采集的食物的角度各不相同，所述根据所述图像确定所述食物对应的目标预存图像的步骤包括：
    根据各个所述图像采集装置采集的图像以及各个所述图像采集装置的采集角度，构建所述食物对应的三维图像；
    计算所述三维图像与各个预存图像之间的第二相似度，其中，各个预存图像的维度与三维图像的维度相同；
    将最大的所述相似度对应的预存图像作为所述食物对应的目标预存图像，其中，最大的所述第二相似度大于预设阈值。
  4. 如权利要求1所述的食物的结算方法，其中，所述根据所述目标预存图像确定所述食物的价格的步骤包括：
    根据所述目标预存图像确定所述食物的类型；
    在所述食物的类型为预设类型，根据所述食物的类型确定所述食物的价格。
  5. 如权利要求1所述的食物的结算方法，其中，所述根据所述图像确定所述食物对应的目标预存图像的步骤包括：
    判断所述图像是否含有匹配的预存图像；
    在所述图像含有匹配的预存图像时，将匹配的所述预存图像作为所述食物对应的目标预存图像。
  6. 如权利要求5所述的食物的结算方法，其中，所述判断所述图像是否含有匹配的预存图像的步骤之后，还包括：
    在所述图像不含有匹配的预存图像，从所述图像中获取目标对象，其中，所述目标对象包括盛放食物的食皿或者食物的包装；
    根据所述目标对象确定所述食物的价格，并执行所述输出所述价格的步骤。
  7. 如权利要求1所述的食物的结算方法，其中，所述输出所述价格的步骤之后，还包括：
    获取所述用户对应的用户信息；
    根据所述用户信息确定所述用户的食物结算方式，其中，所述食物结算方式包括二维码支付、银行卡支付、餐卡支付、脸部识别支付、眼睛识别支付、指纹识别支付、微信支付以及支付宝支付中的至少一种；
    输出所述食物结算方式。
  8. 如权利要求7所述的食物的结算方法，其中，所述输出所述食物结算方式的步骤之后，还包括：
    在检测到基于所述食物结算方式的选择完成的操作，根据所述操作确定目标食物结算方式；
    根据所述目标食物结算方式以及所述价格对所述食物进行结算。
  9. 如权利要求1所述的食物的结算方法，其中，所述根据所述图像确定所述食物对应的目标预存图像的步骤包括：
    根据所述图像获取盛放所述食物的食皿的花纹，所述食物包括饭菜；
    根据所述花纹确定所述食物对应的目标预存图像。
  10. 如权利要求1所述的食物的结算方法，其中，所述根据所述图像确 定所述食物对应的目标预存图像的步骤包括：
    根据所述图像获取盛放所述食物的食皿的造型，所述食物包括饭菜；
    根据所述造型确定所述食物对应的目标预存图像。
  11. 如权利要求1所述的食物的结算方法，其中，所述根据所述图像确定所述食物对应的目标预存图像的步骤包括：
    根据所述图像获取盛放所述食物的食皿的编号，所述食物包括饭菜；
    根据所述编号确定所述食物对应的目标预存图像。
  12. 如权利要求1所述的食物的结算方法，其中，所述根据所述图像确定所述食物对应的目标预存图像的步骤包括：
    根据所述图像获取盛放所述食物的包装；
    根据所述包装确定所述食物对应的目标预存图像。
  13. 如权利要求1所述的食物的结算方法，其中，所述根据所述图像确定所述食物对应的目标预存图像的步骤包括：
    根据所述图像获取盛放所述食物的包装颜色以及食物名称；
    根据所述包装颜色以及所述食物名称，确定所述食物对应的目标预存图像。
  14. 一种食物的结算装置，其中，所述食物的结算装置包括处理器、
    存储器以及存储在所述存储器并可在所述处理器运行的食物结算程序，所述食物结算程序被处理器执行时实现如下步骤：
    对待购买的食物进行采集，以得到所述食物对应的图像；
    根据所述图像确定所述食物对应的目标预存图像；
    根据所述目标预存图像确定所述食物的价格，并输出所述价格。
  15. 如权利要求14所述的食物的结算装置，其中，所述食物结算程序被处理器执行时实现如下步骤：
    计算所述图像与各个预存图像之间的第一相似度；
    将最大的所述第一相似度对应的预存图像作为所述食物对应的目 标预存图像，其中，最大的所述第一相似度大于预设阈值。
  16. 如权利要求14所述的食物的结算装置，其中，所述食物结算程序被处理器执行时实现如下步骤：
    根据各个所述图像采集装置采集的图像以及各个所述图像采集装置的采集角度，构建所述食物对应的三维图像；
    计算所述三维图像与各个预存图像之间的第二相似度，其中，各个预存图像的维度与三维图像的维度相同；
    将最大的所述相似度对应的预存图像作为所述食物对应的目标预存图像，其中，最大的所述第二相似度大于预设阈值。
  17. 如权利要求14所述的食物的结算装置，其中，所述食物结算程序被处理器执行时实现如下步骤：
    根据所述目标预存图像确定所述食物的类型；
    在所述食物的类型为预设类型，根据所述食物的类型确定所述食物的价格。
  18. 一种计算机可读存储介质，其中，所述计算机可读存储介质存储有食物结算程序，所述食物结算程序被处理器执行时实现如下步骤：
    对待购买的食物进行采集，以得到所述食物对应的图像；
    根据所述图像确定所述食物对应的目标预存图像；
    根据所述目标预存图像确定所述食物的价格，并输出所述价格。
  19. 如权利要求18所述的计算机可读存储介质，其中，所述食物结算程序被处理器执行时实现如下步骤：
    计算所述图像与各个预存图像之间的第一相似度；
    将最大的所述第一相似度对应的预存图像作为所述食物对应的目标预存图像，其中，最大的所述第一相似度大于预设阈值。
  20. 如权利要求18所述的计算机可读存储介质，其中，所述食物结算程序被处理器执行时实现如下步骤：
    根据各个所述图像采集装置采集的图像以及各个所述图像采集装 置的采集角度，构建所述食物对应的三维图像；
    计算所述三维图像与各个预存图像之间的第二相似度，其中，各个预存图像的维度与三维图像的维度相同；
    将最大的所述相似度对应的预存图像作为所述食物对应的目标预存图像，其中，最大的所述第二相似度大于预设阈值。
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