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Hyperspectral extraction method for characteristic information of tea leaves

A technology of feature information and extraction method, applied in the direction of color/spectral characteristic measurement, instrument, character and pattern recognition, etc., can solve the problems of high error, strong randomness, time-consuming and labor-intensive in tea leaf information acquisition method, and achieve elimination The effect of random influence, reducing data redundancy, and avoiding errors

Pending Publication Date: 2020-06-09
苏州伙伴实验设备有限公司
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Problems solved by technology

[0003] In order to solve the problems of high error, strong randomness, time-consuming, labor-intensive, and high cost of tea tree leaf information acquisition methods, the present invention provides a hyperspectral extraction method for tea tree leaf feature information

Method used

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  • Hyperspectral extraction method for characteristic information of tea leaves
  • Hyperspectral extraction method for characteristic information of tea leaves
  • Hyperspectral extraction method for characteristic information of tea leaves

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Embodiment Construction

[0033] In order to further understand the content, features and effects of the present invention, the following examples are given, and detailed descriptions are given below with reference to the accompanying drawings.

[0034] The structure of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0035] In this example, the tea spectrum of Fangquan Village tea garden and Longjing 43 in Jianhu Town, Yuecheng District, Shaoxing City was measured on May 1, 2019.

[0036] The tea tree leaf feature information hyperspectral extraction method of the present invention comprises:

[0037] S101. Obtain the tea tree leaf source image through the image acquisition unit, establish a grayscale histogram to count the grayscale distribution of the image, and after enhancing the contrast of the image through the segmented grayscale linear transformation, use Gaussian filtering for smoothing to complete the preprocessing of the image;

[003...

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Abstract

The invention discloses a hyperspectral extraction method for characteristic information of tea leaves. The method comprises the following steps: selecting a feature region on a preprocessed tea leafimage; collecting tea leaf spectral information in the characteristic area; obtaining a main component graph and a gray-scale graph of a characteristic wave band from the hyperspectral image; extracting a texture parameter graph from the grey-scale map of the characteristic wave band; predicting the content of specified elements of the tea tree leaves by using the texture parameters; removing abnormal samples, replacing spectral vectors with feature vectors, segmenting a feature angle cosine average value image, carrying out dissimilarity evaluation on the same extraction feature in spectral information in different sampling samples, and estimating the content of theanine by utilizing multiple linear regression. According to the method, the hyperspectral image segmentation processing efficiency is improved, the data redundancy is reduced, the random influence is eliminated to a certain extent, errors caused by invalid samples are avoided, and the theanine content of the tea leaves canbe accurately, conveniently and economically estimated.

Description

technical field [0001] The invention belongs to the field of crop information extraction, and in particular relates to a hyperspectral extraction method of tea tree leaf feature information. Background technique [0002] The traditional tea leaf information acquisition methods are mainly based on human visual experience and judgment methods and chemical analysis methods based on destructive tests. However, these traditional methods have great shortcomings. The empirical judgment method has high error and strong randomness, while the chemical analysis method is time-consuming, labor-intensive and expensive. Contents of the invention [0003] In order to solve the problems of high error, strong randomness, time-consuming, labor-intensive and high cost in the tea tree leaf information acquisition method, the present invention provides a hyperspectral extraction method for tea tree leaf feature information. [0004] The present invention is achieved in this way, and the hyper...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/46G06K9/34G01N21/25
CPCG01N21/25G06V10/267G06V10/44G06V10/507G06V10/462Y02A40/10
Inventor 张玉龙张玉星沈燕
Owner 苏州伙伴实验设备有限公司
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