基于数字图像处理和SVM的岩体裂隙迹线自动检测

Automated Detection of Rock Discontinuity Trace Based on Digital Image Processing and SVM

提出了一种基于线特征检测、SVM裂隙识别和分割迹线自动连接的岩体裂隙迹线自动检测新方法,该方法计算图像光强度函数2阶导数最大值方向上每个像素点的1阶导数,将1阶导数过零点标识为线特征点,按边缘相似性原则连接成线分段。用线分段的光度参数和几何学参数作为描述裂隙迹线的特征参数,采用盒约束的软间隔优化方法实现裂隙迹线的识别分类。实验结果显示,所提出的方法,可从岩体暴露面图像中自动检测识别裂隙迹线,自动生成的迹线图与地质工作人员手工绘制的迹线图基本相符,表明了本文方法的有效性。

A new discontinuity trace automated detection methodology was presented based on automated line feature detection, SVM fracture recognition, and segmentation tracing linking. The line feature point was the zero crossings of the light intensity function＇ s first derivatives, which were calculated at each pixel in the direction where the image light intensity function＇ s second derivative was maxi- mum. All line feature points were linked into line segmentations according to the principle of edge likelihood. These line segmentations were thus characterized by calculating a series of photometric and geometrical parameters. Then, the fracture traces were classified by the soft margin optimization with box constraints. The experimental results showed that the fracture trace in the rock mass exposure im- age can be automated detected and recognized by this new methodology. The discontinuity trace map constructed by the new methodolo- gy is mainly consistent with the map drawn manually. The results demonstrated the effectiveness of the proposed methodology.