Visual Analysis of Image Processing in the Mining Field Based on a Knowledge Map

被引:3
作者
Qin, Shifan [1 ,2 ,3 ]
Li, Longjiang [1 ,2 ,3 ]
机构
[1] Guizhou Univ, Min Inst, Guiyang 550025, Peoples R China
[2] Natl & Local Joint Engn Lab Efficient Utilizat Exc, Guiyang 550025, Peoples R China
[3] Key Lab Comprehens Utilizat Non Met Mineral Resour, Guiyang 550025, Peoples R China
关键词
image processing; CiteSpace; mining; visualization; cocitation analysis theory; path-finding network algorithm; PARTICLE-SIZE; COMPUTER VISION; ONLINE ANALYSIS; MACHINE-VISION; BIG DATA; FLOTATION; FROTH; EXTRACTION; COAL; CLASSIFICATION;
D O I
10.3390/su15031810
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In machine vision-based image processing, machine vision products are used to convert the image of an object into image signals and then into digital signals for subsequent processing on a computer. Image processing is widely applicable in research fields such as biomedicine, remote sensing, industrial production, military production, and aerospace. This paper provides a detailed overview of the research status of image processing in the mining field and makes a comparative evaluation of some technologies and research directions. First, the application of image processing in the mining field is discussed in detail in the paper. Second, a literature review is conducted, using keywords and citation counts to determine the overall distribution of the published literature on this subject in terms of journals, countries, institutes, and authors. Finally, we analyze this topic in detail, put forward our ideas and what we learned from our analysis, and provide a summary. The analysis shows that image-processing technology is a hot research topic for future development. In addition, this paper proposes future research challenges and directions. The latest progress, development characteristics, and research prospects discussed in this paper will provide a useful reference for scholars who deeply study image processing in the field of mining.
引用
收藏
页数:18
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