An Image Order Management System Without Character Recognition

Abstract

The invention discloses an image order management system that does not require text recognition. The formatted order is first collected through the image acquisition unit, and then the filling area cutout with the filling content is obtained through the filling area extraction unit, and each filling area cutout is included in the formatted order. Finally, the backend order formation unit compares the location information of the formatted order with the location information of the formatted order by filling in the cutout map with the location information of each item of the formatted order stored by itself (the backend order formation unit), and compares each filled in cutout map with its respective location information. The corresponding table item storage contents (i.e. product name, product measurement unit) are combined to generate user orders or delivery stock. In this way, the content of the order, that is, the product name, product measurement unit, and the fill-in area cutout are combined through the location information, and the user order or delivery stock list can be obtained without text recognition. It is accurate, fast, simple and easy to implement, and it also saves a lot of money. labor costs.

Description

Technical field [0001] The invention belongs to the field of distribution, and more specifically, relates to an image order management system without text recognition. Background technique [0002] With the development of contemporary logistics, in the field of distribution, it is necessary to frequently collect order information from a large number of customers. When faced with a large amount of order information, due to the lack of corresponding image order processing tools, the distributor can only use it after receiving the order. Orders are organized by manual copying, which will inevitably cause problems such as heavy workload and error-proneness. [0003] With the development of the contemporary communications industry, distributors can quickly and accurately deliver the demand reports filled out by customers during the demand statistics phase to distributors through smartphones and ordering by taking photos. This has won the favor of more and more purchasers. In the existi...

AI Technical Summary

Problems solved by technology

[0002] With the development of contemporary logistics, in the field of distribution, it is necessary to frequently collect a large number of customer order information. When faced with a large amount of order information, due to the lack of corresponding image order processing tools, the distributor can only use Orders are sorted by manual transcription, which will inevitably lead to problems such as heavy workload and error-prone

[0003] With the development of the contemporary communication industry, distributors can quickly and accurately pass the demand reports filled in by customers in the demand statistics stage to distributors through smart phones and by taking photos to place orders, which has won the favor of more and more purchasers. However, In the existing text recognition technology, because the writing of customers varies from person to person, the number of required fonts varies greatly, and the recognition accuracy is limited. It cannot be directly used to extract the content of the image order. It also requires manual transcription to process the order content. extract

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