Method for quantitatively analyzing maltose mixture based on terahertz spectrum and image information fusion

A quantitative analysis and image information technology, applied in the field of quantitative analysis of maltose mixture, can solve the problems of low prediction accuracy and insufficient information, and achieve the effect of realizing basic model parameters, removing noise, and improving prediction accuracy

Active Publication Date: 2018-06-15
HENAN UNIVERSITY OF TECHNOLOGY
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[0004] The purpose of the present invention is to provide a method for quantitative analysis of maltose mixture based on the fusion of terahe

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  • Method for quantitatively analyzing maltose mixture based on terahertz spectrum and image information fusion
  • Method for quantitatively analyzing maltose mixture based on terahertz spectrum and image information fusion
  • Method for quantitatively analyzing maltose mixture based on terahertz spectrum and image information fusion

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[0041] The present invention will be further described in detail below, so that those skilled in the art can implement it with reference to the description of the polyethylene mixture.

[0042] It should be understood that terms such as "having", "comprising" and "including" as used herein do not entail the presence or addition of one or more other elements or combinations thereof.

[0043] The invention provides a method for quantitative analysis of maltose mixture based on fusion of terahertz spectrum and image information, the steps comprising:

[0044] 1) Feature extraction is performed on the spectrum and image sample data of the maltose mixture, and the extracted data are fused;

[0045] 2) Using the fusion data modeling of spectra and images to quantitatively analyze the maltose mixture.

[0046] The preferred solution is: before step 1, it also includes obtaining sample data of spectra and images of the maltose mixture.

[0047] The preferred scheme is: obtain the sp...

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Abstract

The invention discloses a method for quantitatively analyzing a maltose mixture based on terahertz spectrum and image information fusion. The method includes the following steps: 1) performing featureextraction on the spectrum and image sample data of the maltose mixture, and fusing the extracted data; and 2) modeling the fusion data modeling of spectra and images in order to quantitatively analyze the maltose mixture. The method has the following advantages: 1, the prediction precision in the invention is significantly better than the prediction precision achieved by using a single spectrumor a single image; 2, a PCA algorithm is used to extract individual features from the spectral data and image data in the invention, so noises are effectively removed, and modeling related feature vectors are effectively extracted, thereby the prediction precision of a multi-source information fusion model is effectively improved; and 3, a Boosting iteration termination judgment index is providedaccording to a structural risk minimization theory, so the automatic optimization of base model parameters of a least squares support vector machine is achieved.

Description

technical field [0001] The invention relates to a method for quantitative analysis of maltose mixture based on fusion of terahertz spectrum and image information. Background technique [0002] If food is not stored properly, it is prone to mildew, bud change, hardening, insect erosion, aging and other imaginations, which will cause changes in its smell, color, and composition content. In recent years, electronic noses, machine vision, near-infrared, and Many grain quality detection methods such as X-rays cannot meet the needs of accurate and rapid early detection of grain bud mutation. During the germination process of grain, the main chemical composition change is the conversion of starch into sugars for growth, and maltose molecules have obvious characteristic absorption peaks in the THz band, so the quantitative analysis of maltose molecules in grain particles can To determine the degree of budding of the sample, and then realize the early detection of grain. [0003] A...

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Application Information

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IPC IPC(8): G01N21/3586
CPCG01N21/3586
Inventor 蒋玉英葛宏义张元许德刚王珂任方涛
Owner HENAN UNIVERSITY OF TECHNOLOGY
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