Computer vision-based fruit classifying equipment

Abstract

Computer vision-based fruit classifying equipment comprises two supporting frames, wherein the two supporting frames are both rotationally connected with rotating shafts; one end of one rotating shaftis fixedly connected with an output shaft of a driving motor; the rotating shafts are rotationally connected with belt wheels; the two belt wheels are connected through a conveyor belt; a plurality of transportation bodies are uniformly distributed on the conveyor belt; a computer vision identification device is arranged above the supporting frame which is arranged at the left side. The computervision-based fruit classifying equipment disclosed by the invention has the beneficial effects that the computer vision identification device is used for automatically classifying and discriminating fruits, and then a material pushing device is used for pulling the fruits from the transportation bodies to the inner parts of material storage boxes, so that intelligent classification treatment of the fruits is realized, a classification effect of the fruits is effectively increased, the labor is saved, and wide popularization and application value is obtained; rubber gaskets are capable of effectively preventing the loss of the fruits; in addition, springs have an effective buffer function, so that a protection effect on the fruits is further increased.

Description

technical field [0001] The invention relates to the field of fruit technology, in particular to a computer vision-based fruit grading device. Background technique [0002] Berries: strawberry, blueberry, blackberry, mulberry, raspberry, grape, blackcurrant; citrus: tangerine, tangerine, kumquat, mandarin, sweet orange, navel orange, grapefruit, pomelo, grapefruit, lemon, pomelo, Lime; stone fruits: peaches (nectarines, flat peaches, honey peaches, yellow peaches), plums, cherries, apricots, bayberry, prune, ebony plums, jujubes, sand dates, palm dates, candied dates, olives, lychees, longan ( longan). [0003] At present, the grading of fruits only depends on the weight and size. The weight cannot represent the quality and maturity of the fruit. Only by distinguishing the surface color of the fruit can the quality of the fruit be judged. Moreover, due to individual subjective factors, the grading accuracy and consistency are poor, and the grading quality cannot be guarante...

AI Technical Summary

Problems solved by technology

[0003] At present, the grading of fruits only depends on the weight and size. The weight cannot represent the quality and maturity of the fruit. Only by distinguishing the surface color of the fruit can the quality of the fruit be judged. Influenced by personal subjective factors, the grading accuracy and consistency are poor, and the grading quality cannot be guaranteed

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