Intelligent extraction of area element information from colored geological map on the basis of BP neural network and mathematical morphology

LIU Suqing; CHEN Jianping; XU Bin; LI Shi; ZHANG Yaguang; YAO Yanjun

2020 Vol. 39, No. 7

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LIU Suqing, CHEN Jianping, XU Bin, LI Shi, ZHANG Yaguang, YAO Yanjun. Intelligent extraction of area element information from colored geological map on the basis of BP neural network and mathematical morphology[J]. Geological Bulletin of China, 2020, 39(7): 1104-1114.

Citation:

LIU Suqing, CHEN Jianping, XU Bin, LI Shi, ZHANG Yaguang, YAO Yanjun. Intelligent extraction of area element information from colored geological map on the basis of BP neural network and mathematical morphology[J]. Geological Bulletin of China, 2020, 39(7): 1104-1114.

Intelligent extraction of area element information from colored geological map on the basis of BP neural network and mathematical morphology

School of Earth Science and Resources, China University of Geosciences, Beijing 100083, China

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Corresponding author: CHEN Jianping, 3s@cugb.edu.cn

Received Date: 16 July 2019

Revised Date: 02 December 2019

Publish Date: 25 July 2020

Abstract

Abstract

As an important result of regional geological research geological map not only belongs to the valuable information left by the previous researchers but also integrates the rich knowledgeof geological experts.The purpose of this study is to extract the color geological map information through new ideas, so that the results can be directly used for data analysis and used for decision-making and analysis. Guided by machine learning and based on the analysis of the characteristics of semi-structured grid geological maps this paper proposes a new idea for extracting the information of colored geological map according to the legend information and exploring the effective technology method for transforming semi-structured data into structured data in combination with mathematical morphology and multilayer feed forward neural network. Therefore the semi-structured geological map can be transformed into structured data available for metallogenic prediction and other researches with the help of image information extraction technology.This innovation will change the structure of traditional geological data and increase the information base and source for geological research therefore it is of important significance to obtain more data sources and information sources and to further carry out geological analysis and research.
- machine learning /
- BP neural network /
- mathematical morphology /
- colored geological map

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References

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