Online shopping method, device and system based on image recognition technology

Abstract

The invention discloses an online shopping method, device and system based on an image recognition technology. The online shopping method comprises the following steps of obtaining an image of an article to be purchased, wherein the image of the article to be purchased is sent by a client-side; extracting the characteristic of the image of the article to be purchased; matching the extracted characteristic and characteristics of the images of all articles in all shopping websites through cloud computing; seeking out articles within the set matching degree range and the related information of the articles; ranking the articles which are sought out according to the ranking condition; sending the ranked articles and the related information of the articles to the client-side. According to the online shopping method, device and system based on the image recognition technology, the articles to be purchased are sought out in an image characteristic matching mode, the articles which are located on different shopping platforms and meet the requirement of the matching degree are listed, users can compare and select the articles to be purchased in the shopping platforms at different areas, the articles to be purchased can be displayed for the users conveniently and rapidly, and the problem that due to manual classification and selection, the articles to be purchased are difficult to find out is avoided.

Description

technical field [0001] The invention relates to the technical field of computer network shopping, in particular to an image recognition technology-based network shopping method, shopping device and shopping system. Background technique [0002] With the popularization and use of the Internet, the way people shop is also changing, from simply going to traditional retailers to online shopping, and the rapid development of mobile terminal devices in recent years has made shopping such as mobile phones and tablets a new trend. , and gradually become a new trend of shopping. Online shopping is still shopping at the device terminal. The existing modes are roughly divided into two types: one is to select layer by layer in the corresponding classification according to the nature of the type of item known to the user, and finally find the corresponding item; the other is the latest With the launch of the QR code scanning, some products will be generated by the shopping website in th...

AI Technical Summary

Problems solved by technology

But these two methods have certain defects. The first defect is that it is not flexible enough and sometimes hinders consumption.

When users go to buy products, they have to choose layers from large categories to find the items, and when some items are not clearly classified (such as new smart TVs, sometimes it is impossible to determine whether they are in the category of home appliances or computers), users will find them many times. Operation, affecting user experience, especially when encountering items that you don’t know, you have no choice

Moreover, different shopping sites have different products, and users who want specific items have to go to multiple shopping platforms to search layer by layer; the second defect is that the QR code positioning is too precise. Compare with similar products and then consume rationally. At the same time, only some products of some merchants have QR codes, which cannot be selected across shopping platforms, nor can they meet the QR code requirements of all products.

Since the shopping platform includes many merchants, and some items do not have uniform names, different merchants will name them differently. When searching, it is easy to miss some items to be purchased on the shopping platform due to the different names, and the missing The item is likely to be an item with a high degree of matching; in addition, due to the difference in naming, it is easy to cause different products to use the same name, which will inevitably lead to the expansion of the search range, and not all searched items are what the user wants to choose. It is necessary to filter again among the searched items, wasting the user's time and energy

[0004] In many cases, when a user sees a certain item on the road, or sees a certain picture on the Internet, he will have the idea of ​​consuming one of the items, but currently there is no fast and flexible way for the user to find the item conveniently and quickly And meet the needs of comparison on various platforms

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