Tea tender sprout grade identification and classification method based on computer vision

Abstract

The invention discloses a tea tender sprout grade identification and classification method based on computer vision. The method comprises the following steps: acquiring an original RGB image of tea on a tea tree; secondly, preprocessing the original RGB images of the tea leaves, and directly identifying and segmenting tender sprouts of the tea leaves on the tea trees by adopting an improved watershed algorithm; then, according to the recognition result of the improved watershed algorithm, carrying out classified picking and grade classified marking on the tender sprouts of the tea according to one bud and one leaf, one bud and two leaves and one bud and multiple leaves; thirdly, shooting a plurality of three types of sample images of one bud and one leaf, one bud and two leaves and one bud and multiple leaves which are subjected to grade classification marking; and finally, putting the plurality of three types of sample images into a LeNet5 convolutional neural network, and carrying out tea tender leaf grade classification training and testing. The method has the advantage of high tea grade classification accuracy.

Description

technical field [0001] The invention relates to the technical field of tea grade recognition and classification, in particular to a method for recognition and classification of tea bud grades based on computer vision. Background technique [0002] Famous tea refers to the tea leaves that are recognized by the society, have a unique and beautiful shape and excellent built-in, and are high-quality teas with a certain reputation, such as Longjing, Biluochun and so on. Famous and high-quality teas have very high requirements for tea tree varieties, and the fresh leaves picked should not contain impurities such as old leaves, broken leaves, and tea stems. According to the number of buds and leaves, fresh leaves can be roughly divided into one bud and one leaf, one bud and two leaves, and one bud with multiple leaves. One bud and one leaf is the best, and one bud with multiple leaves is the worst. [0003] At present, most tea gardens in China have basically realized mechanized p...

AI Technical Summary

Problems solved by technology

However, the above-mentioned existing technologies are all based on the tea leaves after picking, and the processing cost is high, and to obtain finely classified tea leaves, the classification process is also relatively complicated.

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