| 基于颜色特征的数字钻孔图像溶隙结构识别方法 |
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| 引用本文： | 李立,余翠,孙涛,韩增强,唐新建.基于颜色特征的数字钻孔图像溶隙结构识别方法[J].岩土力学,2019,40(8):3274-3281. |
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| 作者姓名： | 李立 余翠 孙涛 韩增强 唐新建 |
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| 作者单位： | 1. 武汉大学 电子信息学院，湖北 武汉 430072；2. 中国科学院武汉岩土力学研究所 岩土力学与工程国家重点实验室，湖北 武汉 430071 |
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| 基金项目： | 中国科学院岩土力学研究所岩土力学与工程国家重点实验室开放研究基金（No. Z0106006）；国家自然科学基金（No.41372317, No.91647109） |
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| 摘 要： | 针对数字全景钻孔摄像系统获取的实测图像，提出了一种基于颜色特征的数字式钻孔图像溶隙结构识别方法。利用岩层中的典型结构，如土质层、溶隙在颜色上与普通岩石具有较大差异性的特点，首先建立了一个自适应HSV颜色空间溶隙结构检测模型，利用该模型获取溶隙结构的二值化图像；对该二值化图像进行滤波处理；然后从处理后的二值化图像进行分区像素密度统计来确定土质层或溶隙区域的深度、面积及方位角等信息，从而实现数字式钻孔图像中溶隙结构的自动识别。通过对大量数字式钻孔图像进行试验并与对应的钻孔雷达图像进行结果对比表明，其方法能对全孔图像的溶隙和土质层进行快速、准确地自动化检测与定位，为钻孔图像岩体结构的自动识别与工程应用提供了一种新的可靠方法。
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| 关 键 词： | 数字式钻孔图像 自适应HSV颜色空间模型 图像识别 溶隙检测 土质层检测 |
| 收稿时间： | 2018-05-15 |
Automatic identification of solution fissure from borehole digital optical image based on color features |
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| LI Li,YU Cui,SUN Tao,HAN Zeng-qiang,TANG Xin-jian.Automatic identification of solution fissure from borehole digital optical image based on color features[J].Rock and Soil Mechanics,2019,40(8):3274-3281. |
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| Authors: | LI Li YU Cui SUN Tao HAN Zeng-qiang TANG Xin-jian |
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| Institution: | 1. School of Electronic Information, Wuhan University, Wuhan, Hubei 430072, China; 2. State Key Laboratory of Geomechanics and
Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan, Hubei 430071, China |
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| Abstract: | Based on the high-resolution borehole image obtained by digital panoramic borehole camera system, a method for recognizing solution fissure based on color features was proposed. Considering the fact that typical rock mass structure, such as soil layer and solution fissure have obvious difference from common rock layer in color, a self-adaptive detection model based on HSV (hue- saturation-value) color space was established. The binarized image of solution fissure was obtained using this model. Secondly, the binary image was filtered to avoid the noise effects. Then, the binarized image of solution fissure was divided and the density of pixels in each segmentation was calculated to determine the depth, area and direction of the soil layer and the solution fissure, so that the identification of solution fissure in the digital borehole image can be achieved. Through verifying this method with many actual borehole images and comparing them with the corresponding borehole radar images, the results indicate that this method can identify all the solution fissure and the soil layer throughout the whole borehole digital optical image automatically and quickly. It provides a new reliable method for the automatic identification of borehole rock structures in practical engineering. |
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| Keywords: | digital borehole image self-adaptive HSV color model image recognition solution fissure recognition soil layer recognition |
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