A fresh tea leaf recognition method based on contour analysis

Abstract

The invention discloses a fresh tea leaf recognition method based on contour analysis. An existing fresh tea leaf recognition method does not consider the problems of fresh tea leaf damage and shielding. The method comprises the following steps of firstly, acquiring fresh tea leaf images and extracting fresh tea leaf outer contours; carrying out polygon fitting on the contour, extracting contour feature points and judging the concave-convex property of the feature points; secondly, introducing directional outline width characteristics of the fresh tea leaves, and searching petiole points in convex vertexes; cutting out sub-contours from the outer contours of the fresh tea leaves; after fitting the sub-contours by an ellipse fitting method, identifying whether the sub-contours are leaves orbuds by using a trained support vector machine model with a linear kernel function; and finally, grading the fresh tea leaves according to the number of leaves of the fresh tea leaves and the presence or absence of buds, wherein the fresh tea leaves are divided into single buds, one bud and one leaf, one bud and two leaves, one bud and three leaves and unqualified raw material grades. The methodis high in efficiency, high in accuracy and is free of requirements for blade placement; and the identification accuracy of the partially shielded image can also reach a relatively higher level.

Description

technical field [0001] The invention belongs to the technical field of image recognition, and in particular relates to a method for recognizing fresh tea leaves based on contour analysis. Background technique [0002] With the continuous improvement of the quality of life, the consumption demand for tea has been increasing. In recent years, the domestic tea production has also risen steadily, and tea machine picking has become a development trend. Nowadays, tea leaves are picked by double-blade cutting method, and the fresh tea leaves obtained are mixed in various grades. If they are directly processed, the quality and appearance of the finished tea will be seriously affected. Sometimes in order to improve the product appearance, the finished tea needs to be sorted, resulting in a waste of manpower and material resources in the tea making process. It can be seen that the current tea machine harvesting method cannot be popularized and applied in high-end tea production. The...

AI Technical Summary

Problems solved by technology

Although the success rate of these computer recognition methods is high, the algorithm stability and recognition efficiency still need to be improved. The sample images of fresh tea leaves used in the test are also ideal, and the problems of damage and occlusion of fresh tea leaves are not considered, so they cannot be applied Actual Production

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