Refrigerator shelf commodity statistical method and system based on image processing technology

Abstract

The invention discloses a refrigerator shelf commodity statistics method and system based on an image processing technology, and relates to the field of artificial intelligence, and the method comprises the steps: enabling a terminal controller to splice a first image and a second image into a third image, and enabling a cloud server to segment the third image into a plurality of fourth images; segmenting each fourth image, and performing calculating to obtain the total amount of the first commodities placed in the first row in each storage interlayer in the refrigerator; summing the first commodity total amounts corresponding to all the storage compartments in the refrigerator to obtain a second commodity total amount placed in the first row in the refrigerator and storing the second commodity total amount in a database. The invariant splicing image is rotated according to the circle center; feature point matching errors can be reduced; the image effect obtained through splicing is better, the spliced image is layered into the fourth image, the fourth image is refined and segmented, the commodities placed in the first row in each storage interlayer can be accurately segmented, thestatistical efficiency can be improved, the commodity statistical accuracy can be improved, and the refrigerator commodity management quality can be improved.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence and digital image processing, and more specifically, to a method and system for statisticing commodities on refrigerator shelves based on image processing technology. Background technique [0002] Digital image processing technology is an interdisciplinary field. With the continuous development of computer science and technology, image processing and analysis has gradually formed its own scientific system, and new processing methods emerge in endlessly. widespread attention. [0003] When carrying out product statistics on refrigerator shelves, when the camera cannot capture the products on the entire shelf at close range, although a wide range of images can be obtained by extending the shooting distance, the products in the image may be relatively small, and mosaic phenomenon will appear after zooming in. The effect is poor. Although this problem can be solved by hardware...

AI Technical Summary

Problems solved by technology

[0003] When carrying out product statistics on refrigerator shelves, when the camera cannot capture the products on the entire shelf at close range, although a wide range of images can be obtained by extending the shooting distance, the products in the image may be relatively small, and mosaic phenomenon will appear after zooming in. The effect is poor. Although this problem can be solved by hardware equipment, hardware such as wide-angle lens is expensive, the operation is complicated, and it will cause image edge distortion. Therefore, image stitching and segmentation technology can be used for shelf commodity statistics.

[0004] In the prior art, there are many methods for image stitching and segmentation, but they all have certain defects. For example, the image stitching technology based on the Hough circle detection algorithm has a large error after stitching and registration; the rotation-translation invariance algorithm based on SURF , because there are problems such as reflection and high similarity in the freezer commodity image, the error is large when matching image feature points, resulting in a large error in splicing based on corresponding feature points; adaptive threshold segmentation algorithm, maximum inter-class threshold method, edge Neither the segmentation algorithm nor the region growing algorithm RGSA can accurately segment the commodities in the refrigerator shelves. Therefore, it is necessary to study a statistical method for refrigerator shelves based on image processing technology.

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