基于动态蛇形-膨胀卷积模型的矿区地裂缝提取  

Extracting crack in mining areas based on dynamic snake-dilation convolution model

作　　者：王晓宇 蔡音飞[1] 胡海峰[1] WANG Xiaoyu;CAI Yinfei;HU Haifeng(College of Mining Engineering,Taiyuan University of Technology,Taiyuan 030024,China;Shanxi Coal Geological Investigation and Research Institute Co.,Ltd.,Taiyuan 030006,China)

机构地区：[1]太原理工大学矿业工程学院,山西太原030024 [2]山西省煤炭地质勘查研究院有限公司,山西太原030006

出　　处：《测绘通报》2024年第10期144-150,共7页Bulletin of Surveying and Mapping

基　　金：国家自然科学基金(52074133);教育部产学合作协同育人项目(220905458233959)。

摘　　要：采动裂缝是煤矿地下开采造成的破坏形式之一。针对矿区地表环境复杂、无人机图像裂缝提取方法精度较低的问题,本文融合动态蛇形卷积和膨胀卷积构建了全新的动态蛇形-膨胀卷积,并将其添加到现有分割模型的编码、解码结构,以优化整体网络模型结构;构建了矿区裂缝数据集,并在该自制数据集上进行裂缝提取精度验证。结果表明,加入动态蛇形-膨胀卷积,可使模型的分割精度(平均交并比)提高14.96%,对于实现地裂缝准确提取具有实践价值。Mining cracks are a common type of damage that occurs in coal mines due to underground mining.Aiming at the problems of complex surface environment in mining areas and low accuracy of crack extraction methods in UAV images,this studyfused the dynamic snake convolution and dilation convolution to construct a new dynamic snake-dilation convolution.The proposed convolution is added to the encoding and decoding structure of the reference model to optimize the overall network structure;In addition,constructed a crack dataset of the mining area,and verified the accuracy of the crack extraction on this custom dataset.The results show that the addition of dynamic snake-dilation convolution can improve the segmentation accuracy(mean intersection over union) of the model by 14.96%,which is of practical value for achieving accurate extraction of ground cracks.

关 键 词：地下开采 地裂缝 无人机 裂缝提取 动态蛇形-膨胀卷积 精度评价 

分 类 号：P23[天文地球—摄影测量与遥感]