Fruit intelligent identification method applicable to self-checkout system in supermarket

A self-checkout and intelligent recognition technology, applied in the field of image recognition, can solve the problems that fruit weighing machines cannot realize intelligent recognition, and achieve the effects of saving manpower investment, speeding up checkout efficiency, and low operation difficulty

Inactive Publication Date: 2018-11-23
SOUTHWEAT UNIV OF SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The technical problem to be solved by the present invention is to provide a fruit intelligent identification method that can be applied to the supermarket self-checkout system, and solve the problem that the existing fruit weighing machine cannot realize intelligent identification

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  • Fruit intelligent identification method applicable to self-checkout system in supermarket
  • Fruit intelligent identification method applicable to self-checkout system in supermarket
  • Fruit intelligent identification method applicable to self-checkout system in supermarket

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Embodiment Construction

[0049] The principles and features of the present invention are described below in conjunction with the accompanying drawings, and the examples given are only used to explain the present invention, and are not intended to limit the scope of the present invention.

[0050] like figure 1 As shown, a fruit intelligent identification method that can be applied to the supermarket self-checkout system includes the following steps:

[0051] S1, take C fruit images under different angles for B individuals of A fruit with a digital camera;

[0052] S2. Preprocessing the fruit image;

[0053] S3. Establish an image database with the preprocessed A*B*C fruit images;

[0054] S4, extracting the HSV information of the fruit image in the fruit image database to generate a gray-scale co-occurrence matrix, using the gray-scale co-occurrence matrix as a training set feature library, and calculating the mean vector of the gray-scale co-occurrence matrix in the training set feature library;

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Abstract

The invention relates to a fruit intelligent identification method applicable to self-checkout system in supermarket. According to the invention, fruit image identification is carried out through a K-nearest neighbor classification method based on a HSV information co-occurrence matrix. Identification results are high as 98.1%, and the fruit intelligent identification method does not require training time, the process is simple and fast, the operation difficulty is low, the identification is accurate, and the promotion is great. Applying the fruit intelligent identification method to the self-checkout system in each supermarket can automatically identify different varieties of fruits, and then automatically calculate the price, which speed up the checkout efficiency of the supermarket andsave manpower investment.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to an intelligent fruit recognition method applicable to a supermarket self-checkout system. Background technique [0002] The existing fruit weighing equipment in supermarkets mainly includes traditional weighing and coding scales and integrated weighing and checkout equipment. Weighing and coding scales manually input the product numbers corresponding to fruit products and use traceability codes to collect payments, which requires the cooperation of staff. Complete weighing and coding, wasting manpower and time costs. Weighing and checkout integrated equipment, such as SelfCheckout / Scanasyoushop, independently selects the type of fruit when weighing, and weighs with an induction machine. It can scan the barcode of the fruit on the middle screen, and then perform self-checkout, but it cannot meet large-scale and high-efficiency fruit weighing. demand, resulting in slow w...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/10G06F18/24147
Inventor 龙强范怡薇
Owner SOUTHWEAT UNIV OF SCI & TECH
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