Method for predicting water content of tea on basis of near-infrared hyperspectral textural feature modeling

A near-infrared hyperspectral and texture feature technology, which is applied in the field of computer image processing, can solve the problem of inability to non-destructively measure the moisture content of tea leaves, and achieves the effects of fast measurement speed, few measurement steps, and stable detection results.

Inactive Publication Date: 2013-11-13
ZHEJIANG UNIV
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Problems solved by technology

[0003] The present invention aims at the shortcomings of the inability to quickly and non-destructively measure the moisture content of tea leaves in the prior art, and provides a new method for predicting the moisture content of tea leaves based on near-infrared hyperspectral texture feature modeling

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  • Method for predicting water content of tea on basis of near-infrared hyperspectral textural feature modeling
  • Method for predicting water content of tea on basis of near-infrared hyperspectral textural feature modeling
  • Method for predicting water content of tea on basis of near-infrared hyperspectral textural feature modeling

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Embodiment 1

[0027] The present invention first proposes a method for simultaneously extracting spectral and texture feature variables from hyperspectral data for establishing a regression model and predicting the moisture content of tea leaves.

[0028] The concrete implementation steps of described method are as follows:

[0029] 1) Tea leaf material preparation:

[0030] The whole plant of a tea variety was randomly sampled, and 30 leaves of different sizes and lengths, distributed in various parts of the plant and of different leaf ages were randomly obtained. Use a dry and clean towel to gently wipe off the dirt and dust on the surface of the leaves to remove the influence of surface impurities on the collection of hyperspectral data. Number the leaves, put them into 30 dry envelopes respectively, and store them in a constant temperature box at 23 degrees Celsius for later use.

[0031] 2) Water content experiment data collection:

[0032] 2.1) Leaf average mass measurement: Use a ...

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Abstract

The invention relates to a computer image processing technology and discloses a method for predicting the water content of tea on the basis of near-infrared hyperspectral textural feature modeling. The method comprises the steps of carrying out hyperspectral data acquisition on tea leaves, extracting textural features and spectral features of acquired data, and brightening a prediction model to finally obtain the predicted water content of the tea leaves. The method disclosed by the invention has the advantages that the computation is convenient and fast, the steps are simplified, and compared with the traditional determination method, the method has higher accuracy rate and determination speed and higher application value.

Description

technical field [0001] The invention relates to computer image processing technology, in particular to a method for predicting the moisture content of tea leaves based on near-infrared hyperspectral texture feature modeling. Background technique [0002] In recent years, the prediction method of tea moisture content has played a key role in tea automation and information production, which has greatly promoted the improvement of tea quality and the reduction of high-quality tea production costs. Originating in China more than two thousand years ago, tea was an important commodity along the Silk Road. Today, there are more than 600 different varieties of tea grown throughout China. Longjing tea is one of the top ten teas in China. "West Lake Longjing" is the commodity, and "Shifeng Longjing" is the most popular among West Lake Longjing. It is a very expensive tea. The roasting process of Longjing tea is very complicated, and usually can only be done manually by skilled tea m...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N5/04G01N21/35G06V20/13
CPCG06V20/13
Inventor 邓水光李浬徐亦飞尹建伟李莹吴健吴朝晖
Owner ZHEJIANG UNIV
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