Image acquisition-analysis method

Abstract

The invention relates to the technical field of image processing and particularly discloses an image acquisition-analysis method. The image acquisition-analysis method includes the steps as follows: step 1. making a plurality of rulers and putting the rulers on every row of supermarket shelf, wherein each ruler is provided with multiple groups of codes; step 2. acquiring images of the shelves on which the rulers are put on; step 3. separating color channels on the collected images and detecting the codes of rulers on the separated channels; step 4. correcting the images according to the detection result of the codes; step 5. dividing out zones including goods in the corrected images according to the detection result on the codes; and step 6. classifying the goods on the zones by utilizingcolor characteristics and local textural characteristics, thus obtaining relevant information of goods arrangement. With the image acquisition-analysis method, the information of the arrangement place, the quantity and the like of the goods on the shelves can be efficiently and correctly obtained. The image acquisition-analysis method is simple, convenient and feasible and saves large amount of manpower and material resources.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method for analyzing collected images and obtaining information on placing commodities on shelves. Background technique [0002] With the development of the retail industry, supermarkets have become the main sales channel for mass commodities. Mastering the placement of commodities in supermarkets is helpful for commodity manufacturers to keep abreast of market trends and adjust marketing strategies in a timely manner. At present, the main way for commodity manufacturers to obtain commodity placement information is to send staff to conduct on-the-spot investigations in supermarkets. After the dispatched staff arrive at the supermarket, they will make statistics on whether the goods are neatly placed and the number of goods placed by visual inspection and manual counting. There are following problems in the method of manual on-site measurement. First of all, the manu...

AI Technical Summary

Problems solved by technology

First of all, it cannot handle the situation of repeated patterns. For supermarket shelves, there are often multiple items of the same type of product. This type of method can usually only determine the category of a certain product detected, but cannot judge the same type of product detected. Whether the products in the category are the same product on the shelf, this may cause double counting during statistics; secondly, this type of method usually has high requirements on lighting conditions, and the lighting conditions of different supermarkets are very different, which makes this type of method not fully accurate. to promote

In general, even with the use of computers, existing methods cannot guarantee high efficiency while maintaining accuracy

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