基于裂隙形态特征的煤层图像裂隙识别研究

刘勇C, 崔洪庆

刘勇,崔洪庆.基于裂隙形态特征的煤层图像裂隙识别研究[J].工矿自动化,2017,43(10):59-64.. DOI: 10.13272/j.issn.1671-251x.2017.10.012
引用本文: 刘勇,崔洪庆.基于裂隙形态特征的煤层图像裂隙识别研究[J].工矿自动化,2017,43(10):59-64.. DOI: 10.13272/j.issn.1671-251x.2017.10.012
LIU Yong, CUI Hongqing. Research on coal-bed image fractures identification based on fracture shape characteristics[J]. Journal of Mine Automation, 2017, 43(10): 59-64. DOI: 10.13272/j.issn.1671-251x.2017.10.012
Citation: LIU Yong, CUI Hongqing. Research on coal-bed image fractures identification based on fracture shape characteristics[J]. Journal of Mine Automation, 2017, 43(10): 59-64. DOI: 10.13272/j.issn.1671-251x.2017.10.012

基于裂隙形态特征的煤层图像裂隙识别研究

基金项目: 

国家自然科学基金资助项目(41372160)

河南省高等学校重点科研项目(16A440009)

详细信息
  • 中图分类号: TD67

Research on coal-bed image fractures identification based on fracture shape characteristics

  • 摘要: 针对现有煤层图像裂隙识别方法未较好地考虑裂隙的形态特征或未较好地获取裂隙的整体信息的问题,通过分析煤层图像及其不同灰度阈值下二值图中裂隙的形态特征,定义了煤层裂隙判定系数,并取二值图中区域的长度、宽度和长宽比作为形态参数;同时给出一种基于裂隙形态特征的煤层图像裂隙识别方法,在给定形态参数阈值条件下遍历一定范围内的灰度阈值,对所得煤层图像的二值图进行裂隙识别,并将所有识别的裂隙合并作为最终识别结果。最后通过实例验证了该方法的有效性,得出结论:通过遍历一定范围内的灰度阈值进行煤层图像裂隙识别,可最大程度地获取煤层图像的裂隙信息;合理选取裂隙判定系数中形态参数的阈值,可有效提高煤层图像裂隙识别的准确性。
    Abstract: In view of problems that existing coal-bed image fractures identification method does not take good account of shape characteristics of the fractures or overall information of the fractures is not well obtained, by analyzing coal-bed image and shape characteristics of the fractures in binary image under different gray thresholds, determination coefficient of the coal-bed fractures was defined, and regio's length, width and the ratio of length to width in the coal-bed binary image were defined as shape parameters. At the same time, a method of the coal-bed image fractures identification based on fracture shape characteristics was proposed. Under condition of the given shape parameters, travel a given gray scale threshold range and identify fracture regions in every coal-bed binary image, then merge all the identified fracture regions as the last coal-bed fractures identification result. Finally, an example was given to demonstrate effectiveness of the method. It is concluded that information of the coal-bed image fractures can be acquired to the maximum extent by traveling a certain gray scale threshold range and identify the coal-bed image fractures, and it can effectively improve accuracy of the coal-bed fracture identification by selecting reasonable thresholds of the shape parameters of the fracture determining coefficient.
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    其他类型引用(1)

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出版历程
  • 刊出日期:  2017-10-09

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