Machine visual identification method for sorting products with corner point characteristics

Abstract

The invention discloses a machine visual identification method for sorting products with corner point characteristics. The method comprises the steps as follows: performing Freeman chain code encoding on the image outlines of known products, detecting the corner points by using the Freeman chain codes, calculating the corner point characteristic three-dimensional column vectors of all the corner points, sequencing the corner point characteristic three-dimensional column vectors and taking the vector sequence as the vector sequence of the known products; performing Freeman chain code encoding on the image outlines of objects to be sorted, detecting the corner points by using the Freeman chain codes, calculating the corner point characteristic three-dimensional column vectors of all the corner points, sequencing the corner point characteristic three-dimensional column vectors and taking the vector sequence as the vector sequence of the objects to be sorted; and judging the vector sequence of the known products and the vector sequence of the objects to be sorted and finishing machine visual identification. According to the method, the shapes of the known products and the objects to be sorted are simply represented by the chain codes; the subsequent calculation quantity is small; the extracted vector sequence has zooming and rotation invariance can be accurately identified; and the algorithm is simple.

Description

technical field [0001] The invention relates to the technical field of on-line sorting by using machine vision, in particular to a method for on-line recognition of products by using a machine vision system at a product sorting site with corner point features. Background technique [0002] Sorting operation is an important link in most assembly lines. Compared with manual sorting operations, automatic sorting based on machine vision is efficient, accurate, and has quality assurance. It can be widely used in machinery, food, medicine, cosmetics and other production fields. [0003] When the sorting system based on machine vision is working, the objects to be sorted are continuously sent into the sorting work area. The object to be sorted refers to the product that has not been determined and will be identified and sorted. The objects to be sorted enter the sorting work area with the conveyor belt. Under the control of the computer, the industrial camera acquires the image c...

AI Technical Summary

Problems solved by technology

[0008] In view of the large amount of calculation existing in the prior art and the difficulty in dealing with the random situation of the

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