Grape vine winter shearing point detection algorithm

A vine and point detection technology, applied in the field of target detection, can solve the problems of slow operation, large network volume, unfavorable deep learning model embedding, etc., to reduce misclassification, improve refinement accuracy, and reduce redundant pixels Effect

Pending Publication Date: 2021-07-13
ZHEJIANG UNIV OF TECH
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Problems solved by technology

While the huge number of parameters brings performance improvement, it also brings disadvantages such as huge network volume and slo

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  • Grape vine winter shearing point detection algorithm
  • Grape vine winter shearing point detection algorithm
  • Grape vine winter shearing point detection algorithm

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[0073] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0074] On the contrary, the invention covers any alternatives, modifications, equivalent methods and schemes within the spirit and scope of the invention as defined by the claims. Further, in order to make the public have a better understanding of the present invention, some specific details are described in detail in the detailed description of the present invention below. The present invention can be fully understood by those skilled in the art without the description of these detailed parts.

[0075] like Figure 1-11 Shown, a kind of grapevine winter cut point detection method specifically co...

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Abstract

The invention discloses a grape vine winter shearing point detection algorithm, and belongs to the technical field of target detection. The method comprises the following steps: step 1, segmenting a grape vine area; step 2, refining and vectorizing a grape vine area; step 3, reconstructing a grape vine connection relation; step 4, finding grape vine branches needing pruning; step 5, determining bud points are detected, and pruning points. According to the invention, the SLIC superpixel method is adopted to segment the grape vine region and the background region in the grape vine image, and single pixel points are gathered into pixel blocks, so that the segmentation speed is greatly increased; color information features and texture information features are used as segmentation basis to train a BPNN classifier, so that the segmentation accuracy is improved; a refinement algorithm is adopted, so that the refinement time is shortened, the refinement precision is improved, redundant pixel points are reduced, and the single-pixelation of a refinement result is realized; according to the invention, the branch and trunk connection relation of the refined grape vine skeleton is reconstructed, redundant detection of other grape vine branches which do not need pruning is effectively avoided, and the efficiency is improved.

Description

technical field [0001] The invention belongs to the technical field of target detection, and in particular relates to a target detection method for identifying winter pruning points of grape vines in images. Background technique [0002] Grape pruning is an important part of grape growth management, which has a great impact on grape yield. The functions of grape winter shears are: 1. Prenatal and postnatal care. After a year of growth, each grape has more than a dozen branches, and each grape branch is more than 1 meter long, with more than a dozen buds on it. All the buds will germinate at the same time in the next spring, which will cause nutrient concentration. The tree will inevitably weaken. Winter pruning is to reduce the number of flower buds, remove shriveled buds and waste buds, and save the best flower buds for next spring. 2. Replacement. The old branches are repeatedly cut in winter, leaving one more section every year will inevitably grow longer and longer, ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/32G06K9/34G06K9/62G06N3/04G06N3/08
CPCG06N3/084G06V20/188G06V10/25G06V10/267G06N3/045G06F18/241G06F18/214
Inventor 杨庆华袁宇浩毛芸生荀一
Owner ZHEJIANG UNIV OF TECH
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