Method for automatically identifying rock minerals based on spectral information

An automatic identification and spectral information technology, applied in the field of hyperspectral remote sensing applications, can solve the problems of difficult automatic processing of large amounts of data, low recognition accuracy, low efficiency, etc., to save manpower, improve economic benefits, and achieve good results.

Inactive Publication Date: 2019-01-29
BEIJING RES INST OF URANIUM GEOLOGY
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Problems solved by technology

The traditional identification of minerals based on spectral information is usually manual identification, which is slow, inefficient, and labor-intensive.
Although software such as ENVI currently has some met

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  • Method for automatically identifying rock minerals based on spectral information

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Embodiment Construction

[0021] The present invention is described in further detail below in conjunction with embodiment.

[0022] like figure 1 As shown, a method for automatically identifying rock minerals based on spectral information provided by the present invention comprises the following steps:

[0023] Step 1. Use the hyperspectral scanner to scan the rock minerals to be classified to obtain the spectral data of the rock minerals to be classified; specifically include the following steps: clean the surface of the rock core sample to be classified, and place it on the position where the core hyperspectral scanner detects the sample , turn on the core hyperspectral scanner to scan the core samples to be classified, obtain the spectral data of the samples to be classified at 400nm to 1600nm, and repeat this operation until all the mineral and rock samples to be classified are scanned.

[0024] The rock mineral samples to be classified must be dry and clean, with no other attachments on the surf...

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Abstract

The invention belongs to the field of hyperspectral remote sensing application, and particularly discloses a method for automatically identifying rock minerals based on spectral information. The method comprises the following steps: scanning rock minerals to be classified by using a hyperspectral scanner to obtain mineral spectral data; storing the obtained data in a database to be detected; extracting a part of data from the database; identifying mineral species information corresponding to the extracted spectral data according to features of the mineral spectral data by using manual interpretation, and storing the extracted spectral data and the corresponding mineral species information as a learning sample library; establishing an artificial intelligence learning system, and performinglearning and training by using the learning sample library; and detecting the spectral data in the database to be detected by using the artificial intelligence learning system after training and learning optimization to identify the mineral species information; and storing an identification result in an identification result database. By adoption of the method, the human resource consumption can be reduced, the working automation degree is improved, the spectral scanning data processing efficiency is improved, and the economic efficiency is improved.

Description

technical field [0001] The invention belongs to the application field of hyperspectral remote sensing, and specifically discloses a method for automatically identifying rock minerals based on spectral information. Background technique [0002] Rock minerals have unique diagnostic characteristic absorption bands due to their unique chemical composition and physical structure. These characteristic bands have relatively stable wavelength positions and unique waveforms, and their characteristics include spectral absorption peak positions and absorption peak depths. , Absorption peak width and other characteristic parameters, through these characteristics or their combination, the identification of minerals can be realized. The traditional identification of minerals based on spectral information is usually manual identification, which is slow, inefficient, and labor-intensive. Although software such as ENVI currently has some methods for automatically identifying substances base...

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Application Information

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IPC IPC(8): G01N21/31G01N21/17G06N99/00
CPCG01N21/17G01N21/31G01N2021/1793
Inventor 王建刚邱骏挺叶发旺张川刘洪成孟树
Owner BEIJING RES INST OF URANIUM GEOLOGY
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