Multispectral Feature Fusion Recognition Method Based on pca_lda Analysis

A technology of feature fusion and recognition method, applied in character and pattern recognition, instruments, computer parts and other directions, can solve the problem of not realizing the information fusion of the combined system

Active Publication Date: 2017-02-08
江苏易谱恒科技有限公司
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Problems solved by technology

The spectrum information fusion is not realized within the hyphenated system, let alone the information fusion between different hyphenated systems

Method used

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  • Multispectral Feature Fusion Recognition Method Based on pca_lda Analysis
  • Multispectral Feature Fusion Recognition Method Based on pca_lda Analysis
  • Multispectral Feature Fusion Recognition Method Based on pca_lda Analysis

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Embodiment Construction

[0035] Below in conjunction with accompanying drawing, the present invention will be described in further detail:

[0036] The present invention has designed a kind of multi-spectrum feature fusion recognition method based on PCA_LDA analysis, comprising the following specific steps:

[0037] Step (1): Collect n samples, set n samples to belong to c categories, select m different spectra for each sample, use the PCA_LDA method to extract the spectral features of all samples, and extract the spectra of all samples The graph features are fused into a multispectral fusion feature matrix;

[0038] Step (2): Use the multispectral fusion feature matrix in step (1) to establish a multispectral fusion SVM classifier;

[0039] Step (3): Use the multispectral fusion SVM classifier established in step (2) to identify the samples collected in step (1).

[0040] As shown in Figure 1, as an optimization method of the present invention: the step (1) includes the following specific processi...

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Abstract

The invention discloses a multiple spectrogram characteristic amalgamation and recognition method based on analysis of PCA-LDA. The multiple spectrogram characteristic amalgamation and recognition method based on analysis of the PCA-LDA comprises the following steps: utilizing a PCA-LDA method to extract spectrogram characteristics of all samples; amalgamating the extracted spectrogram characteristics of all the samples to a multiple spectrogram characteristics amalgamation matrix; establishing a multiple spectrogram amalgamation SVM classifier; and utilizing multiple spectrogram amalgamation SVM classifier samples to recognize. The multiple spectrogram characteristic amalgamation and recognition method based on analysis of PCA-LDA can quickly conduct accurate analytical recognition to the integral characteristic of complex mixture.

Description

technical field [0001] The invention relates to a multi-spectrum feature fusion recognition method based on PCA_LDA analysis, in particular to a fast spectrogram analysis method for the overall characteristics of complex mixtures. Background technique [0002] Pattern recognition combined with analytical techniques such as spectroscopy, chromatography, ion mobility spectrometry, mass spectrometry, and nuclear magnetic resonance are widely used in various food quality control. Raman spectroscopy is a type of scattering spectroscopy. Raman spectroscopy is based on the Raman scattering effect discovered by Indian scientist C.V. Raman. It analyzes the scattering spectrum different from the frequency of the incident light to obtain information on molecular vibration and rotation, and is applied to the study of molecular structure. method. The main features of Raman spectroscopy are fast, simple, no sample pretreatment, and good signal repeatability. In addition, because the Ra...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/66
Inventor 王海燕刘军王国祥姜九英
Owner 江苏易谱恒科技有限公司
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