岩土力学 ›› 2024, Vol. 45 ›› Issue (9): 2621-2632.doi: 10.16285/j.rsm.2024.0476

• 基础理论与实验研究 • 上一篇    下一篇

岩体暴露面图像中裂隙全自动提取方法研究

吴金1,吴顺川1, 2, 3,孙贝贝1   

  1. 1. 北京科技大学 土木与资源工程学院,北京 100083;2. 昆明理工大学 国土资源工程学院,云南 昆明 650093; 3. 自然资源部高原山地地质灾害预报预警与生态保护修复重点实验室,云南 昆明 650093
  • 收稿日期:2024-04-18 接受日期:2024-05-27 出版日期:2024-09-06 发布日期:2024-09-02
  • 通讯作者: 吴顺川,男,1969年生,博士,教授,主要从事采矿工程与岩土工程的教学与科研工作。E-mail: wushunchuan@163.com
  • 作者简介:吴金,男,1995年生,博士研究生,主要从事岩体结构面图像处理等方面的研究工作。E-mail: b20200006@xs.ustb.edu.cn
  • 基金资助:
    国家自然科学基金项目(No.51934003);云南省重大科技专项(No.202102AF080001);云南省创新团队资助项目(No.202105AE160023)。

Research on fully automatic extraction of fractures from images of rock mass exposures

WU Jin1, WU Shun-chuan1, 2, 3, SUN Bei-bei1   

  1. 1. School of Civil and Resources Engineering, University of Science and Technology Beijing, Beijing 100083, China; 2. Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming, Yunnan 650093, China; 3. Key Laboratory of Geohazard Forecast and Geoecological Restoration in Plateau Mountainous Area, Ministry of Natural Resources of the People’s Republic of China, Kunming, Yunnan 650093, China
  • Received:2024-04-18 Accepted:2024-05-27 Online:2024-09-06 Published:2024-09-02
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (51934003), the Major Science and Technology Special Project of Yunnan Province (202102AF080001) and the Program of Yunnan Innovation Team (202105AE160023).

摘要: 裂隙显著影响岩体物理与力学性质,针对从岩体暴露面图像中自动提取裂隙存在的提取结果不完整、信噪比低,以及提取方法经验参数多、鲁棒性差等问题,提出一种全自动裂隙提取优化程序。首先,通过引入广义伽马校正初步提升裂隙与岩壁面对比度;其次,考虑裂隙路径像素间相互影响,设计灰度传递算法提升裂隙连续性;最后,通过改进Frangi滤波器提取裂隙并充分抑制噪音像素响应。结果表明:该程序充分融合了裂隙低灰度和高线型两大特征,图像增强与裂隙提取两阶段协同运作,显著改善了裂隙对比度不均问题,在较完整提取裂隙的同时还能够有效防止噪音与伪裂隙的产生,对多种岩体暴露面图像均具有很高的鲁棒性。将该方法与常用的裂隙识别算法进行比较,展现了该算法流程在处理低对比度、高噪声岩体裂隙图像方面的显著优势。

关键词: 岩体暴露面, 裂隙自动提取, 数字图像处理, 灰度传递算法, Frangi滤波

Abstract: The presence of fractures significantly influences the physical and mechanical properties of rock masses. However, automated extraction of fractures from images of rock mass exposures frequently encounters challenges such as incomplete results, low signal-to-noise ratio, reliance on empirical parameters, and poor robustness. In response to these issues, a fully automated optimization procedure for the extraction of fractures is proposed. Firstly, the introduction of a generalized gamma correction is employed to preliminarily enhance the contrast between fractures and rock wall surfaces. Subsequently, by considering the mutual influence among pixels along fracture paths, a grayscale transmission algorithm is devised to improve the continuity of fractures. Finally, an improved Frangi filter is utilized for fracture extraction while effectively suppressing the response of noise pixels. The results indicate that the proposed procedure cleverly integrates two major characteristics of fractures: low grayscale and high linearity, and the coordination between the stages of image enhancement and fracture extraction significantly ameliorating the issue of uneven fracture contrast. Furthermore, while ensuring complete fracture extraction, it efficiently prevents the generation of noise and pseudo-fractures. The procedure demonstrates high robustness across various images of rock mass exposures. Comparative analysis with commonly used fracture identification algorithms highlights the advantages of the proposed procedure.

Key words: rock mass exposures, automatic fracture extraction, digital image analysis, gray transmission algorithm, Frangi filter

中图分类号: TU443
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